WO2020137101A1

WO2020137101A1 - Embedded object detection device and embedded object detection method

Info

Publication number: WO2020137101A1
Application number: PCT/JP2019/040656
Authority: WO
Inventors: 曜岡本; 雅思佐藤
Original assignee: オムロン株式会社
Priority date: 2018-12-28
Filing date: 2019-10-16
Publication date: 2020-07-02
Also published as: JP2020106491A; JP6984582B2

Abstract

An embedded object detection device (1) that moves over the surface of a target object and detects embedded objects in the target object using data about waves that are the reflection of electromagnetic waves that have been radiated at the target object. The embedded object detection device comprises a reception part (61), an embedded object detection part (64), and a scanning error determination part (65). The reception part (61) receives data about reflected waves at timing that is associated with movement. The embedded object detection part (64) detects embedded objects using data about reflected waves for reciprocal movement along the same route over the surface of the target object. The scanning error determination part (65) compares data about reflected waves in a range S that is for first movement during which an embedded object was detected and data about reflected waves in a range T that corresponds to range S and is for second movement that is after the first movement and thereby determines whether scanning is being performed such that reciprocal movement is occurring along the same route.

Description

Buried object detection device and buried object detection method

The present invention relates to a buried object detection device and a buried object detection method.

As a device for searching for an embedded object in concrete, an embedded object detection device is used that detects an embedded object from a reflected wave of an electromagnetic wave emitted toward the concrete while moving the surface of the concrete (for example, Patent Document 1). reference).
The presence or absence of an embedded object can be detected by repeatedly operating the embedded object detection device so as to reciprocate between two points on the same path while scanning. By scanning between one point and the other point, the distance information is acquired by the encoder installed in the embedded object detection device, and the signal intensity is displayed in color on a plane having two axes in the road direction and the depth direction. be able to. When the position of the buried object is detected each time the scanning between these two points is repeated, the certainty of the position of the buried object can be improved based on the positions of the buried object detected a plurality of times.

Japanese Patent No. 5789088

However, in the case of the conventional embedded object detection device, if the embedded object is detected and then deviated from the route when further scanning, the embedded object is detected at a position different from the position of the embedded object detected by the previous scanning. Therefore, the certainty of the position of the buried object is reduced.
An object of the present invention is to provide an embedded object detection device and an embedded object detection method capable of improving the certainty of the position of an embedded object.

An embedded object detection apparatus according to a first aspect of the present invention is an embedded object detection apparatus that detects an embedded object in an object by using data regarding a reflected wave of an electromagnetic wave emitted toward the object while moving on the surface of the object. Therefore, it is provided with a receiving unit, an embedded object detecting unit, and a scanning error determining unit. The receiving unit receives the data regarding the reflected wave at each timing accompanying the movement. The embedded object detection unit detects the embedded object by using the data regarding the reflected wave when the object reciprocates along the same path on the surface of the object. The scanning error determination unit corresponds to the data regarding the reflected wave of the predetermined first range in the first movement when the embedded object is detected, and the first range in the second movement after the first movement. The data regarding the reflected waves in the second range are compared with each other to determine whether or not scanning is performed so as to reciprocate along the same path.

In this way, it is possible to determine that the vehicle has deviated from the same path. For example, by clearing the position of the embedded object that was detected before the determination, it is possible to restart the detection of the position of the embedded object from the beginning. Alternatively, by notifying the user that he/she is out of the same route, the user can erase the detected position of the buried object. Alternatively, it is possible to erase only the position of the buried object detected when the vehicle deviates from the same path.

As described above, it is possible to improve the certainty of the position of the buried object by detecting the deviation from the same path.
Further, for example, if the difference between the data regarding the reflected wave in the first range and the data regarding the reflected wave in the second range is within a predetermined error range, it is assumed that similar data is received and the same route is reciprocated. You can judge that you are doing. On the other hand, when the difference between the data regarding the reflected wave in the first range and the data regarding the reflected wave in the second range is larger than the predetermined error range, it is determined that different data is received, and the vehicle reciprocates along the same route. You can determine that you have not.

An embedded object detection device according to a second aspect of the present invention is the embedded object detection device according to the first aspect of the present invention, wherein the scanning error determination unit includes an embedded object position erasing unit. When it is determined that the embedded object position erasing unit is not reciprocating along the same path, the embedded object position erasing unit deletes the detected position of the embedded object detected by the movement of the path before the determination.
As a result, the position of the buried object can be detected again from the beginning, so that the accuracy of the position of the buried object can be improved.

The embedded object detection device according to a third aspect of the present invention is the embedded object detection device according to the first aspect of the present invention, wherein the scanning error determination unit has a notification unit. The notification unit notifies the user that a scanning error has occurred when it is determined that the user is not moving back and forth on the same route.

An embedded object detection device according to a fourth aspect of the present invention is the embedded object detection device according to the first aspect of the present invention, wherein the first range is a range including a detection position where the embedded object is detected, or a range near the detection position. Is.
At the position of the buried object, a large change occurs in the data on the reflected wave, so by comparing the data on the reflected wave in the first range with the data on the reflected wave in the second range, it can be determined whether or not the same path is reciprocating. Can be detected more accurately.

An embedded object detection device according to a fifth aspect of the present invention is the embedded object detection device according to the first or fourth aspect of the present invention, wherein the first range and the second range are the same distance from the folding position in the reciprocating movement.
Here, the distance is obtained by converting the timing associated with the movement. In the range of the same distance from the turn-back position, when following the same route, it is possible to detect data regarding similar reflected waves. Therefore, by comparing the data regarding reflected waves in the first range and the second range, the same route is reciprocated. Whether or not it can be detected.

An embedded object detection device according to a sixth aspect of the present invention is the embedded object detection device according to the fourth aspect of the present invention, in which the first range includes a detection position and is a range before the detection position in the second movement.
This makes it possible to determine that the vehicle is not following the same route as quickly as possible.

An embedded object detection apparatus according to a seventh aspect of the present invention is the embedded object detection apparatus according to the first aspect of the present invention, in which the embedded object detection unit includes a signal intensity peak detection unit and an embedded object position detection unit. The signal intensity peak detector detects the peak of the signal intensity in the depth direction of the object at each timing. The embedded object position detection unit detects the position of the embedded object based on the peak of the signal intensity detected at each timing.
Thereby, the position of the buried object can be detected based on the signal strength.

An embedded object detection apparatus according to an eighth aspect of the present invention is the embedded object detection apparatus according to the seventh aspect of the present invention, wherein the scanning error determination unit detects the signal strength at the depth position in the depth direction for each timing in the first range. , And the signal intensity at the depth position in the depth direction for each timing in the second range is compared to determine whether or not scanning is performed so as to reciprocate along the same path.
For example, if the difference between the signal intensity at the depth position for each timing in the first range and the signal intensity at the depth position for each timing in the second range is within a predetermined error range, similar data is received. Therefore, it can be judged that they are moving back and forth along the same route. On the other hand, when the difference between the signal intensity at the depth position for each timing in the first range and the signal intensity at the depth position for each timing in the second range is larger than the predetermined error range, different data is received. Therefore, it can be determined that the vehicle is not moving back and forth on the same route.

An embedded object detection apparatus according to a ninth aspect of the present invention is the embedded object detection apparatus according to the eighth aspect of the present invention, wherein the first range includes a plurality of first positions specified by timing and depth position. The second range includes a plurality of second positions specified by timing and depth position. The scanning error determination unit has a difference calculation unit, a counting unit, and a determination unit. The difference calculator calculates the difference between the signal strength of each first position and the signal strength of the second position corresponding to each first position. The counting unit counts the number of differences equal to or larger than the first threshold. The determination unit determines whether or not the count number is equal to or larger than the second threshold value, and when the count number is equal to or larger than the second threshold value, determines that the scanning error occurs.
As a result, if the difference between the signal intensity in the first range and the signal intensity in the second range is within the predetermined error range, it is determined that similar data is received, and it is determined that the same route is reciprocating. can do.

An embedded object detection apparatus according to a tenth aspect of the present invention is the embedded object detection apparatus according to the seventh aspect of the present invention, wherein the embedded object detection unit further includes a difference processing unit. The difference processing unit detects a difference in change in signal intensity at a predetermined depth position from the signal intensity at a preceding depth position in the depth direction or the surface direction opposite thereto.
This makes it possible to extract a change in signal intensity due to the influence of the buried object.

An embedded object detection apparatus according to an eleventh aspect of the present invention is the embedded object detection apparatus according to the tenth aspect of the present invention, wherein the signal intensity peak detection unit has a depth position at which the difference changes from decrease to increase and a difference decreases from increase. At least one of the depth positions that changes to is detected as a peak of the signal intensity.
In this way, the peak of the signal strength can be detected using the data of the increase and decrease of the signal strength.

An embedded object detection apparatus according to a twelfth aspect of the present invention is the embedded object detection apparatus according to the eleventh aspect of the present invention, in which the embedded object detection unit includes a grouping unit and a depth position peak detection unit. The grouping unit sets, as one group, the depth positions at a plurality of signal intensity peaks that are consecutive within a predetermined interval in the moving direction among the depth positions at the signal intensity peaks detected at each timing. .. The depth position peak detection unit detects a peak at the depth position of the group on the plane in the moving direction and the depth direction.
In this way, the position of the buried object can be detected by defining the continuous peaks as one group and detecting the peak at the depth position in the group.

An embedded object detection apparatus according to a thirteenth invention is the embedded object detection apparatus according to the twelfth invention, in which the embedded object detection unit further includes an embedded object position determination unit. The buried object position determination unit sets the position of the buried object based on the detected peak of the depth position.
Thereby, the position of the buried object can be determined.

An embedded object detection device according to a fourteenth invention is the embedded object detection device according to the thirteenth invention, in which the embedded object position determination unit is a group of peaks of signal strength that change from decrease to increase within a predetermined range. One of the peaks at the depth position in the group and the peak at the depth position in the group of the peaks of the signal strength changing from increasing to decreasing is detected, and the peaks at other depth positions exist within the predetermined range from the peak. If not, the detected peak is not set as the position of the buried object.
As a result, the position of the buried object can be set for one detected peak.

An embedded object detection apparatus according to a fifteenth invention is the embedded object detection apparatus according to the thirteenth invention, in which the embedded object position determining unit determines the depth position in the group of the peaks of the signal intensity that changes from decrease to increase. When the peak and the peak at the depth position in the group of the peaks of the signal intensity changing from the increase to the decrease exist adjacent to each other within the predetermined range, the position of the shallower peak is set to the position of the buried object.
This allows the position of the shallower peak to be the position of the buried object.

An embedded object detection apparatus according to a sixteenth invention is the embedded object detection apparatus according to the thirteenth invention, wherein the embedded object position determination unit is the depth position in a group of peaks of signal intensity changing from decrease to increase. And the peaks at the depth positions in the group of the peaks of the signal intensity changing from increasing to decreasing are alternately present in the predetermined range by three or more, the position of the shallowest peak is set to the position of the buried object. Set to position.
This allows the position of the shallowest peak to be the position of the buried object.

An embedded object detection device according to a seventeenth aspect of the present invention is the embedded object detection device according to the thirteenth aspect, wherein the embedded object position determination unit has a large number of peaks at adjacent depth positions in reciprocating movement. Adopt the position of the buried object.
Thereby, the accuracy of the position of the buried object can be improved.

An embedded object detection device according to an eighteenth invention is the embedded object detection device according to the twelfth invention, wherein the depth position peak detection unit has a group having a predetermined shape in a plane in the moving direction and the depth direction. If it is, it is determined that there is an embedded object, and if it is not the predetermined shape, it is determined that no embedded object exists.
In this way, when the peak continues in the moving direction and the shape is a predetermined shape, it can be determined that the buried object exists. The predetermined shape may be, for example, a mountain shape.

An embedded object detection apparatus according to a nineteenth invention is the embedded object detection apparatus according to the first invention, wherein the embedded object detection unit further includes an averaging processing unit. The averaging processing unit averages the signal strength in the depth direction of the object at each timing during the reciprocating movement with the signal strength in the depth direction of the object at each timing received before that. ..
As a result, the certainty of the position of the buried object can be improved by scanning the same path a plurality of times.

An embedded object detection device according to a twentieth invention is the embedded object detection device according to the first invention, further including a display unit. In the reciprocating movement, the display unit displays the signal strength on a plane in the movement direction and the depth direction for each movement. When an embedded object is detected, the display section displays the detected position of the embedded object together with the display.
By displaying the detected position of the embedded object in this way, the user can easily recognize the position of the embedded object.

An embedded object detection device according to a twenty-first aspect of the invention is the embedded object detection device according to the twentieth aspect of the present invention, wherein the display section detects the embedded object detection position when it is determined that the display unit is not reciprocating along the same path. Erase.
By deleting the detection position of the embedded object when the scanning error is detected, it is possible to prevent the embedded object from being displayed at a position that does not exist during the movement when the scanning error is detected, and the user is not confused.

A buried object detecting method according to a twenty-second aspect of the present invention is a buried object detecting method for detecting a buried object in an object using data on a reflected wave of an electromagnetic wave emitted toward the object while moving on the surface of the object. Therefore, it includes a receiving step, a buried object detecting step, and a scanning error determining step. The receiving step receives data regarding the reflected wave at each timing associated with the movement. The buried object detecting step corresponds to data regarding a reflected wave in a predetermined first range in the first movement when the buried object is detected, and the first range in the second movement after the first movement. The data regarding the reflected waves in the second range are compared with each other to determine whether or not scanning is performed so as to reciprocate along the same path.
In this way, it is possible to determine that the vehicle has deviated from the same path, and therefore, for example, by clearing the position of the embedded object detected before the determination, the position of the embedded object can be detected again from the beginning. Alternatively, by notifying the user that he/she is out of the same route, the user can erase the detected position of the buried object. Alternatively, it is possible to erase only the position of the buried object detected when the vehicle deviates from the same path.

The buried object detecting method according to the twenty-third invention is the buried object detecting method according to the twenty-second invention, further comprising a buried object position erasing step. The embedded object position erasing step erases the detected position of the embedded object detected by the movement of the path before the movement of the path when it is determined that the path is not reciprocating along the same path.
As a result, the position of the buried object can be detected again from the beginning, so that the accuracy of the position of the buried object can be improved.

(Effect of the invention)
According to the present invention, it is possible to provide a buried object detection apparatus and a buried object detection method capable of improving the certainty of the position of a buried object.

The perspective view which shows the structure of the buried object detection apparatus in embodiment concerning this invention. The block diagram which shows the structure of the embedded object detection apparatus of FIG. The block diagram which shows the structure of the pulse control module of FIG. The figure which shows the data of the reflected wave which the MPU of FIG. 3 acquires. FIG. 3 is a block diagram showing a configuration of a main control module of FIG. 2. 6A to 6C are views for explaining processing by the averaging processing unit in FIG. FIG. 6 is a block diagram showing a configuration of an embedded object detection unit in FIG. 5. (A) The figure which shows the image data before performing the gain adjustment, (b) The figure which shows the image data after the gain adjusting process. (A) The figure which shows the image data before performing difference processing, (b) The figure which shows the image data after difference processing. (A) The figure which shows the image data after performing a moving average process, (b) The figure which shows the signal strength of RF data of the line L1 of FIG. 10 (a). The enlarged view between P10 and P3 of FIG.10(b). The figure for demonstrating the process by a primary differential process part. The figure which shows the image data after preprocessing. 6A to 6D are views for explaining processing by the grouping unit. The figure which shows the position of the some grouped peak. No. shown in FIG. 1 to No. The figure which shows the change of the position of the adjacent peak to 15th. The figure which shows the pattern of the detected peak. (A) The figure which shows the image data in which three adjacent peaks were detected, (b) The figure which shows the example of the position of the determined buried object. (A) The figure which shows the image data in which two adjacent peaks were detected, (b) The figure which shows the example of the position of the determined buried object. (A) The figure which shows the image data in which the adjacent peak was not detected but one peak was detected, (b) The figure which shows the state in which the position of the buried object is not determined. The figure which shows a buried object data transition table. (A)-(c) The figure which shows the transition of the buried object data according to the buried object data transition table of FIG. The figure for demonstrating the state (position displaced) in which the embedded object detection device is not reciprocating along the same path. FIG. 6 is a block diagram showing the configuration of a scanning error determination unit in FIG. 5. (A), (b) The figure for demonstrating the range setting by the range setting part of FIG. (A), (b) The figure for demonstrating the range setting by the range setting part of FIG. The flowchart which shows the process of the buried object detection apparatus 1. The flowchart which shows the data acquisition process of FIG. FIG. 28 is a flowchart showing the waveform data averaging process of FIG. 27. FIG. 28 is a flowchart showing the scanning error determination processing of FIG. 27. FIG. 31 is a flowchart showing the positional shift amount acquisition processing of FIG. 30. FIG. 31 is a flowchart showing the processing at the time of position shift in FIG. 30. FIG. 28 is a flowchart showing the embedded object detection process of FIG. 27. The flowchart which shows the pre-processing of FIG. FIG. 34 is a flowchart showing the gain adjustment processing of FIG. 33. The flowchart which shows the difference process of FIG. FIG. 34 is a flowchart showing first-order differentiation processing of the difference result of FIG. 33. The flowchart which shows the peak detection process of FIG. FIG. 34 is a flowchart showing the buried object determination process of FIG. 33. FIG. 40 is a flowchart showing the grouping process of FIG. 39. FIG. 40 is a flowchart showing the vertex detection processing of FIG. 39. FIG. 40 is a flowchart showing the buried object acquisition process of FIG. 39. The block diagram which shows the scanning error determination part in the modification of embodiment of this invention.

An embedded object detection device according to an embodiment of the present invention will be described below with reference to the drawings.
<Structure>
(Outline of buried object detection device 1)
FIG. 1 is a perspective view showing a state in which an embedded object detection device 1 according to an embodiment of the present invention is placed on concrete 100. FIG. 2 is a block diagram showing a schematic configuration of the embedded object detection device 1 according to the present embodiment.

The embedded object detection device 1 of the present embodiment radiates an electromagnetic wave to the concrete 100 while moving on the surface 100a of an object such as concrete 100, receives the reflected wave, and analyzes the electromagnetic wave, thereby burying in the concrete 100. The positions of the

objects

101a, 101b, 101c, 101d are detected. The embedded object detection device 1 reciprocates the same path (see arrows A1 and A2) to increase the certainty of the positions of the embedded

objects

101a, 101b, 101c, and 101d.

In FIG. 1, the buried

objects

101a, 101b, 101c, 101d are reinforcing bars, and are buried at depths of 20 cm, 15 cm, 10 cm, and 5 cm in order from the surface 100a, for example. The depth direction is indicated by arrow B, and the surface direction is indicated by arrow C.
The embedded object detection device 1 includes a main body 2, a handle 3, wheels 4, an impulse control module 5, a main control module 6, an encoder 7, and a display unit 8.

A handle 3 is provided on the upper surface of the main body 2. Four wheels are rotatably attached to the bottom of the main body 2. When detecting an embedded object inside the concrete 100, the operator moves the embedded object detection device 1 on the surface 100 a of the concrete 100 while holding the grip 3 and rotating the wheels 4.
The impulse control module 5 controls the timing of emitting an electromagnetic wave toward the concrete 100, the timing of receiving a reflected wave of the emitted electromagnetic wave, and the like.

The encoder 7 is provided on the wheel 4 and transmits a signal for controlling the reception timing of the reflected wave to the impulse control module 5 based on the rotation of the wheel 4.
The main control module 6 receives the data regarding the reflected wave received by the impulse control module 5, and detects the buried object.
The display unit 8 is provided on the upper surface of the main body unit 2 and displays an image showing the positions of the embedded

objects

101a, 101b, 101c, and 101d.

(Impulse control module 5)
FIG. 3 is a block diagram showing the configuration of the impulse control module 5.
The impulse control module 5 has a control unit 10, a transmission antenna 11, a reception antenna 12, a pulse generation unit 13, a delay unit 14, and a gate unit 15.
The control unit 10 is configured by an MPU (Micro Processing Unit) or the like, and instructs the pulse generation unit 13 to generate a pulse by using an encoder input as a trigger. The pulse generator 13 generates a pulse based on a command from the MPU and sends it to the transmitting antenna 11. The transmitting antenna 11 radiates an electromagnetic wave at a constant cycle based on the pulse cycle. The input timing of the encoder 7 corresponds to an example of the timing.

The receiving antenna 12 receives the reflected wave of the radiated electromagnetic wave. When the gate unit 15 receives the pulse from the delay unit 14, the gate unit 15 captures the reflected wave received by the reception antenna 12 and transmits the reflected wave to the control unit 10. The delay unit 14 transmits a pulse to the gate unit 15 at a predetermined interval to capture a reflected wave. The predetermined interval is, for example, 2.5 mm pitch.
As a result, the impulse control module 5 triggers the input from the encoder or 7 to output the electromagnetic wave from the transmitting antenna 11 multiple times. Then, the impulse control module 5 can acquire the reception data for each distance to the reception antenna 12 by delaying the reception timing by using the delay IC of the delay unit 14.

FIG. 4 is a diagram showing data of reflected waves acquired by the MPU. The vertical axis represents the intensity of the received signal in −4096 to +4096 gradations with the axis O as the center, and the arrow direction indicates the negative side. The horizontal axis indicates the distance from the receiving antenna 12, and the direction of the arrow B (corresponding to the depth direction) indicates that the distance from the receiving antenna 12 is long. In addition, a long distance corresponds to a deep depth.

As will be described later in detail, since the waveform W1 shown in FIG. 4 also includes the reflected wave reflected by the antenna without being irradiated into the concrete 100 (p1 etc.), the difference from the reference waveform is calculated. The change in the data of the reflected wave from inside the concrete 100 is extracted.
Further, the data shown in FIG. 4 is data from when the encoder 7 is input until when the encoder 7 is next input. By gradually delaying the reception timing, the reflected wave from the position where the distance from the reception antenna 12 is long is received. However, if there is an input from the encoder 7, the reception timing delay is restored and the reception timing is changed again. Delay gradually. That is, the reflected wave in the depth direction (the direction of arrow B) at a predetermined measurement position (the position where the encoder 7 has input) in the direction of arrow A indicating the moving direction is received. The data of the reflected wave from after the input of the encoder 7 shown in FIG. 4 to the input of the next encoder is called one line of data. The control unit 10 transmits the RF (Radio Frequency) data for one line to the main control module 6 every time the data for one line is accumulated.

Since the embedded object detection device 1 is moved, the measurement positions are not exactly the same position, and the direction of the arrow B indicating the depth direction is not strictly perpendicular to the surface 100a of the concrete 100.

(Main control module 6)
FIG. 5 is a block diagram showing the configuration of the main control module 6. The main control module 6 includes a reception unit 61, an RF data management unit 62, an averaging processing unit 63, an embedded object detection unit 64, a scanning error determination unit 65, and a display control unit 66.
The receiver 61 receives RF data for one line each time it is transmitted from the impulse control module 5.
The RF data management unit 62 stores the RF data for one line received by the reception unit 61.
The averaging processing unit 63 averages the 1-line waveform data when the averaging processing unit 63 moves twice or more along the path. For example, when the route is moved to the arrow A1 shown in FIG. 1 for the first time and then turned back and moved to the direction of the arrow A2 for the second time, the distance from the turnaround point becomes the first time and the second time. An average of signal intensities at the same measurement position and the same position in the depth direction is calculated.

The embedded object detection unit 64 detects a peak of signal intensity for each averaged line of data, determines the presence or absence of the embedded object 101 using the peak of signal intensity, and detects the position of the embedded object 101. ..
The scanning error determination unit 65 determines whether or not scanning is performed so as to reciprocate along the same path.
The display control unit 66 controls the display unit 8 to display an image in which the signal intensity is gradation-processed by color on the plane in the direction of arrow A indicating the movement direction and the direction of arrow B indicating the depth direction. The display control unit 66 also controls the display unit 8 to display the position of the buried object 101.

(Averaging processing unit 63)
The averaging processing unit 63 performs averaging processing of RF data. 6A to 6C are diagrams for explaining the averaging process.

The third drawing from the right end of FIGS. 6A to 6C is a view of the wall (an example of the object) viewed from the front, and the reinforcing bars as the buried object 101 are buried along the vertical direction. ..
Here, it is assumed that the embedded object detection device 1 is reciprocated between the points E and F so as to traverse the embedded object 101. As shown in FIG. 6A, when the embedded object detection device 1 is moved from the point E to the point F for the first time, the receiving unit 61 moves from the point E to the point F along the arrow A1 indicating the moving direction. Each time the encoder 7 receives an input, the RF data for one line is received, and the received RF data for a plurality of lines is stored in the RF data management unit 62. The rightmost diagrams of FIGS. 6A to 6C are intensity signals on an XY coordinate plane in which the position in the scanning direction converted from the input of the encoder 7 is the X axis and the position in the depth direction is the Y axis. It is a figure which shows the intensity|strength of a black and white gradation.

Next, as shown in FIG. 6B, when the point F is moved to the point E for the second time, the receiving unit 61 causes the plurality of lines from the point F to the point E along the arrow A2 indicating the moving direction. Minute RF data is received, and the received RF data for a plurality of lines is stored in the RF data management unit 62.
The averaging processing unit 63 averages the first and second RF data for each line. The averaging processing unit 63 calculates the average of the signal intensities of the same XY coordinate values at the first and second times for all the XY coordinate values on the XY plane from the point E to the point F, and the RF data managing unit 62 stores the average. Remembered.

Next, as shown in FIG. 6C, when the point E is moved to the point F for the third time, the receiving unit 61 causes the plurality of lines from the point E to the point F along the arrow A1 indicating the moving direction. Minute RF data is received, and the received RF data for a plurality of lines is stored in the RF data management unit 62.
The averaging processing unit 63 averages the first, second and third RF data for each line, and stores the averaged RF data in the RF data management unit 62.
By repeatedly scanning the same path a plurality of times in this manner, the RF data can be averaged, noise can be reduced, and the position of the buried object described later can be detected more accurately.

(Buried object detection unit 64)
FIG. 7 is a block diagram showing the configuration of the embedded object detection unit 64.
The embedded object detection unit 64 includes a preprocessing unit 23, an embedded object determination unit 24 (an example of an embedded object position detection unit), and a determination result registration unit 25.

The pre-processing unit 23 detects a peak of signal intensity for each averaged line of data.
The embedded object determination unit 24 determines the presence or absence of an embedded object using the peak of the signal intensity for each line of RF data detected by the preprocessing unit 23. Further, the embedded object determination unit 24 detects the position of the embedded object 101.
The determination result registration unit 25 registers the position of the buried object detected by the buried object determination unit 24 in the RF data management unit 62.

(Preprocessing unit 23)
As shown in FIG. 7, the preprocessing unit 23 includes a gain adjusting unit 31, a difference processing unit 32, a moving average processing unit 33, a first-order differentiation processing unit 34, a peak detection unit 35 (of a signal intensity peak detection unit). One example) and.

(Gain adjuster 31)
The gain adjusting unit 31 performs gain adjustment on the RF data averaged for each line. As the distance from the transmission antenna 11 and the reception antenna 12 increases (the delay time increases), the reception sensitivity decreases, so that the density of white and black decreases when an image described later is displayed. Therefore, the gain adjusting unit 31 increases the gain value (×1 to ×20) by which the signal strength is multiplied (amplified) as the depth position is deeper.

FIG. 8A is a diagram showing image data before the gain adjustment. In the detected image shown in FIG. 8A, the horizontal axis (X axis) indicates the moving distance, and the direction of arrow A1 indicates the moving direction. The vertical axis (Y axis) indicates the depth position, and the arrow direction indicates the deep side. In the diagram shown in FIG. 8A, the signal intensity for each line shown in FIG. 4 is shown in black and white gradation in the vertical axis direction, and the black and white gradation data of all lines is shown in the horizontal axis direction. It is an image. In the present embodiment, for example, the gradation process is performed such that the greater the intensity of the received signal is, the whiter it is, and the smaller the intensity of the received signal is, the more black it is.

Therefore, the shading shown in FIG. 8A indicates the signal strength. In addition, the intensity signal of one line which is subjected to black and white gradation is shown surrounded by a dotted line. FIG. 8B is a diagram showing image data obtained by performing gain adjustment processing on the image data of FIG. 8A. As shown in FIG. 8B, the tone adjustment becomes stronger by the gain adjustment. Further, since the gain value in the deeper part becomes higher, the value of the RF data becomes larger. Therefore, the image data in the lower part becomes whitish as a whole. The whitish part is shown surrounded by a dotted line.

(Differential processing unit)
The difference processing unit 32 extracts the RF data of the changed portion by calculating the difference from the reference point from the gain-adjusted RF data. FIG. 9A is a diagram showing the image data before the difference process is performed, and FIG. 9B is a diagram showing the image data after the difference process is performed. FIG. 9A shows the same image data as FIG. 8B.

Here, the reference point is the average value of the data acquired so far. For example, in the RF data, when calculating the difference from the reference point of the signal intensity of the depth n (mm) (Y coordinate value Y _n ) of the m-th (X coordinate value X _m ) line, 1 to m An average value of the signal intensities of the line depths Y _n (mm) up to the -1st (X coordinate values X ₁ to X _m-1 ) is calculated, and the average value is calculated as the depth n of the m-th line. Subtract from the signal strength in (mm). By performing this calculation for all depth positions of all lines, it is possible to clarify changes in the RF data signal as shown in FIG. 9B.

(Moving average processing unit)
The moving average processing unit 33 performs the moving average processing for each line for the RF data subjected to the difference processing. In the present embodiment, for example, the moving average process can be performed by averaging 8 points.
FIG. 10A is a diagram showing the image data subjected to the moving average processing, and FIG. 10B is a diagram showing the signal intensity of the RF data of the line L1 of FIG. 10A. The horizontal axis of FIG. 10B indicates the depth position, which is deeper along the arrow direction. The vertical axis of FIG. 10B shows the signal intensity, and the signal intensity increases along the arrow direction.

Note that, in the present embodiment, the one with the higher signal strength is grayed out in white, and the one with the weaker signal strength is grayed out in black. Further, in the present embodiment, the downward peak, that is, the position where the black color is the darkest, and the upward peak, that is, the position where the white color is the thinnest are detected. For example, the position of a downward peak indicates the position of a reinforcing bar or the like in concrete, and the position of an upward peak indicates the position of a cavity or resin in concrete.

Since the principle of detecting the downward peak and the upward peak is the same, in the following description, the detection of the downward peak (the position where black is the darkest) will be specifically described.
Black portions on the line L1 in FIG. 10A are indicated by P1 to P5. These P1 to P5 are also shown in FIG. 10(b). Further, in FIG. 10B, one of the upward peaks between P2 and P3 is shown as P10.

(First derivative processing unit 34)
The primary differential processing unit 34 performs primary differential processing on the data subjected to the differential processing in order to detect the downward peak. The first-order differentiation processing unit 34 calculates the difference from the signal strength at the predetermined depth position to the signal strength at the next depth position.
FIG. 11 is an enlarged view between P10 and P3 in FIG. FIG. 12 is a diagram showing a table 150 of the signal strength of the graph of FIG. 11 and the result of the first derivative processing.

Sequence numbers are shown in the leftmost column of the table 150 shown in FIG. The position becomes deeper as the sequence number increases. The second column from the left shows the signal strength at each sequence number. The third column from the left shows the difference calculated by the primary differential processing unit 34.
The difference of the sequence number n is a value obtained by subtracting the signal intensity of the sequence number n from the signal intensity of the sequence number n+1. For example, the difference with the sequence number 7 is a value (-9) obtained by subtracting the 7th signal strength (431) from the 8th signal strength (422).
In this way, the primary differential processing unit 34 performs the primary differential processing on all the data of one line.

(Peak detection unit 35)
The peak detection unit 35 detects the peak of the RF data of one line after the primary differential processing. For example, when detecting a downward peak (black peak), the peak detection unit 35 detects, as a peak, a point at which the change after the first-order differentiation process changes from a negative change to a positive change. Specifically, as shown in Table 150 of FIG. 12, the change in sequence number 33 is a negative (-) change, and the change in sequence number 34 is a positive (+) change. The peak detection unit 35 detects that the signal intensity has a downward peak at the depth position of the sequence number 34.
In addition, when detecting the upward peak (the position where the whitest color is the thinnest), the peak detection unit 35 determines the point at which the change after performing the first derivative process changes from a positive change to a negative change. Detect as a peak. For example, in the table 150 of FIG. 12, it is detected that the signal intensity has an upward peak at the depth position of the sequence number 5.

(Embedded object determination unit 24)
As shown in FIG. 7, the buried object determination unit 24 includes a grouping unit 51, a shape determination unit 52 (an example of a depth position peak detection unit), a buried object position determination unit 53, and a buried object data integration unit 54. With. The grouping unit 51 detects, as a group, peaks that are continuous with respect to the moving distance (X-axis coordinate) among the plurality of peaks detected by the peak detection unit 35. The shape determination unit 52 determines the presence/absence of an embedded object based on whether or not the group has a mountain shape, and when it determines that the embedded object exists, determines the apex (an example of a peak at the depth position) in the group. Detect and use as the position of the buried object.

(Grouping part 51)
The grouping unit 51 groups the peak detection results by the peak detection unit 35. The grouping unit 51 confirms the presence or absence of the peak detection result in order from the past line. With the result as a starting point, the presence or absence of continuous peak detection in the traveling direction is checked. FIG. 13 is a diagram showing image data after preprocessing by the preprocessing unit 23. In FIG. 13, the line L2 acquired this time is shown. 14A to 14D are diagrams for explaining the processing by the grouping unit 51.

The grouping unit 51 uses the position QS of the first found peak as a starting point (indicated by ● in FIG. 13) and has a peak of the next line within 5 pixels in the direction of arrow B indicating the moving direction and within 5 pixels above and below. Confirm whether to do. The line in which the peak position Q is found is the current line.
FIG. 14A shows a state where the peak position QS is found. FIG. 14B shows a case where the position Q2 of the next peak exists within 5 pixels of the direction of arrow A1 indicating the moving direction of the position QS of the peak of the current line and within 5 pixels of the upper side. In FIG. 14B, the peak position is rising (moving to the shallow side) in the moving direction. FIG. 14C shows the case where the peak position Q2 of the next line exists within 5 pixels and below 5 pixels in the direction of arrow A1 indicating the moving direction of the peak position QS of the current line. In FIG. 14C, the position of the peak is descending (moving to the deep side) in the moving direction.

Then, with the line having the peak position Q2 as the current line, whether the peak of the next line exists within 5 pixels in the direction of arrow A1 indicating the moving direction of the peak position Q2 and within 5 pixels above and below Check if In this way, each time the RF data of a line is received, the current line is shifted in the moving direction to check the continuity of peaks.
Then, as shown in FIG. 14D, when the peak of the next line does not exist within 5 pixels in the direction of arrow B indicating the moving direction of the peak position of the current line and within 5 pixels above and below , The peak position Qe is the end point of the group (indicated by ▪ in FIG. 13).
As described above, the grouping unit 51 performs grouping of peak positions. In FIG. 13, a group (for example, group G1) in which a black circle and a black square are connected by a line is shown.
In addition, similarly, the grouping of the upward peak position (the position where the whitest color is the thinnest) is also performed.

(Shape determination unit 52)
The shape determination unit 52 determines whether the shape of the group is a predetermined mountain shape. FIG. 15 is a diagram showing the positions of a plurality of grouped peaks. Further, FIG. 15 also shows conditions for determining the mountain shape. The shape determination unit 52 determines that the group has a mountain shape when the three conditions of the first condition, the second condition, and the third condition are satisfied.

As shown in FIG. 15, the first condition is that the direction of movement is increased by 5 pixels or more in the upward direction (shallow direction) in the direction of the arrow A1, and the second condition is that the movement direction is changed. The third condition is that the difference in the depth direction is 10 pixels or more as the third condition is continuously descending by 5 pixels or more in the direction of arrow A1.
When the three conditions are satisfied, the shape determination unit 52 determines that the shape of the group is a mountain shape, and determines that an embedded object exists.

On the other hand, if any one of the first to third conditions is not satisfied, the shape determination unit 52 does not determine that the embedded object exists.
The shape determination unit 52 also detects an upward peak of the position of the group when performing the determinations of the first to third conditions.
The shape determination unit 52 sets the shallowest position as the apex of the group and stores the position.

The shape determination unit 52 sets the point where the change in position changes from increase to decrease as the apex of the group. For example, in FIG. 16, since the 7th to 8th changes are positive (+) and the 8th to 9th changes are negative (−), as shown in FIG. 15, the 8th position is the vertex. Is determined.
Note that, similarly to the above, the shape determination unit 52 determines the shape of the group at the position of the upward peak (the position where the white color is the thinnest), and detects the shallowest position of the group as the vertex position. To do.

(Embedded object position determination unit 53)
The embedded object position determination unit 53 determines the position of the embedded object 101 based on the position and the number of peaks detected by the shape determination unit 52.
The buried object position determination unit 53 determines whether or not adjacent peaks in the plurality of detected peaks are within a predetermined range.

Specifically, the buried object position determination unit 53 determines whether or not the adjacent peaks are within ±10 pixels on the X axis and ±40 pixels on the Y axis. The buried object position determination unit 53 determines whether or not there is another peak within ±10 pixels of the X axis and within ±40 pixels of the Y axis from the predetermined peak, and when another peak exists, the other peak is determined. It is determined whether or not there is another peak within ±10 pixels on the X-axis and within ±40 pixels on the Y-axis from the peak in (1), and the determination is performed for the peaks in the entire range in which the RF data is acquired.

As a result, the buried object position determination unit 53 detects five patterns of peaks, as shown in Table 1 of FIG.
The pattern A1 is composed of white (upward peak position) group vertices, black (downward peak position) group vertices, and white (upward peak position) adjacent to each other in order from the shallowest. The pattern in which the vertices of the group are detected is shown.

The pattern A2 is, in order from the shallowest, a vertex of a group of black (downward peak position), a vertex of a group of white (upward peak position), and a black (downward peak position) which are adjacent to each other. The pattern in which the vertices of the group are detected is shown.
The pattern B1 shows a pattern in which the vertices of the white (upward peak position) group and the black (downward peak position) group vertex, which are adjacent to each other, are detected in order from the shallow side.

The pattern B2 is a pattern in which the vertices of the black (downward peak position) group and the vertices of the white (upward peak position) group, which are adjacent to each other, are detected in order from the shallow side.
Pattern C is a pattern other than the above-mentioned patterns A1, A2, B1, and B2, and has only one vertex of a white (upward peak position) group or a black (downward peak position) group vertex. The detected pattern is shown.

FIG. 18A is a diagram showing image data in which three adjacent peaks are detected, and FIG. 18B is a diagram showing an example of the determined position of the buried object.
In FIG. 18A, the position P1 of the apex of the group G1 of black (the position of the downward peak), the position P2 of the apex of the group G2 of the white (the position of the upward peak), and the black (the downward direction) in order from the shallow side. The position P3 of the apex of the group G3 (the position of the peak of 1) is detected, and is indicated by a cross.

Here, the difference between the X-axis values of the vertex position P1 and the vertex position P2 is within 10 pixels, the difference between the X-axis values of the vertex position P2 and the vertex position P3 is within 10 pixels, and the vertex position The difference between the Y-axis values of P1 and the vertex position P2 is within 40 pixels, and the difference between the Y-axis values of the vertex position P2 and the vertex position P3 is within 40 pixels.
In the case of the pattern A1, the embedded object position determining unit 53 shows the position P1 (black apex), P2 (white apex), and P3 (black apex) of three adjacent apexes as shown in FIG. Thus, the position P1 of the shallowest vertex is determined as the position Pd of the buried object.

That is, the embedded object position determination unit 53 determines whether the vertex position P1, the vertex position P2, and the vertex position P3 are provided in the vicinity, respectively. It is determined that the apex is detected from the object, and it is determined that the embedded object is arranged at the shallowest position.
Also in the case of the pattern A1, the embedded object position determination unit 53 determines the shallowest vertex as the position Pd of the embedded object.

The detected positions of the vertices P2 and P3 are only stored in the RF data management unit 62 and are not displayed, and only the position Pd of the vertices determined to be the position Pd of the buried object is shown in FIG. As shown in, the display control unit 66 displays it on the display unit 8.
FIG. 19A is a diagram showing image data in which two adjacent vertices are detected, and FIG. 19B is a diagram showing an example of the determined position of the buried object.

FIG. 19A shows images of a white (upward peak position) group G2 and a black (downward peak position) group G3 in order from the shallow side. Then, the position P2 of the apex of the group G2 and the position P3 of the apex of the group G3 are detected, which is indicated by a cross.
The difference between the X-axis values of the vertex position P2 and the vertex position P3 is within 10 pixels, and the difference between the Y-axis values of the vertex position P2 and the vertex position P3 is within 40 pixels.

In the case of the pattern B1, the buried object position determination unit 53 determines the shallower peak P2 as the position of the buried object as shown in FIG. 19(b). That is, the buried object position determination unit 53 determines whether the vertex position P2 and the vertex position P3 are provided in the vicinity, respectively, and when they are provided in the vicinity, they are detected from one buried object. It is determined that the embedded object is placed at the position of the shallower apex.

Also in the case of the pattern B2, the embedded object position determination unit 53 determines the position of the apex in the shallow direction as the position of the embedded object.
20A is a diagram showing an example in which adjacent vertices are not detected and one vertice is detected, and FIG. 20B is a diagram showing a state in which the position of the buried object is not determined. Is.
In FIG. 20A, the position P2 of the apex of the white (upward peak position) group G2 is detected in order from the shallower side, and is indicated by a cross.

There are no other peaks within ±10 pixels on the X axis and ±40 pixels on the Y axis from the vertex position P2. In the case of such a pattern C, the embedded object position determination unit 53 does not determine the position of the embedded object, as shown in FIG.

(Buried object data integration unit 54)
As described with reference to FIGS. 6A to 6C, the buried object data integration unit 54 updates the detected position of the buried object when the same path is moved multiple times.
The buried object data integration unit 54 changes the buried object data based on the buried object data transition table shown in FIG. 22A to 22C are diagrams for explaining the transition of the buried object data.
FIG. 22A is a diagram showing the scanning direction, the detection result of the apex, and the embedded object position determination result when the embedded object detection device 1 is scanned from the point E to the point F for the first time. FIG. 22B is a diagram showing the scanning direction, the vertex detection result, and the embedded object position determination result when the embedded object detection device 1 is scanned for the second time from the point E to the point F. FIG. 22C is a diagram showing a scanning direction, a vertex detection result, and an embedded object position determination result when the embedded object detection device 1 is scanned for the third time from point E to point F.

As shown in FIG. 22A, when a pattern C (see the second image from the right end) is detected when the embedded object detection device 1 is scanned for the first time from point E to point F, the above-described operation is performed. Thus, the buried object position determination unit 53 does not determine the position of the buried object (see the image on the right end).
Next, as shown in FIG. 22B, when the pattern B1 is detected when the embedded object detection device 1 is scanned from point F to point E for the second time, the embedded object position is determined as described above. The unit 53 determines the position of the buried object to be the position P2 of the apex (see the image at the right end).

At this time, since the buried object data integration unit 54 has the first result (before the change) as the pattern C and the second result (after the change) as the pattern B1, B2 is adopted according to the transition table of FIG. To be done.
Next, as shown in FIG. 22C, when the pattern A2 is detected when the embedded object detection device 1 is scanned for the third time from the point E to the point F, the embedded object position determination is performed as described above. The unit 53 determines the position of the buried object to be the position P1 of the apex (see the image at the right end).
At this time, the buried object data integration unit 54 uses the pattern B1 as the second result (before the change) and the pattern A2 as the second result (after the change). Then, the position Pd of the buried object is determined as the position P1 of the apex.

(Judgment result registration unit 25)
The determination result registration unit 25 registers the result (group, peak position, determined position of the buried object, etc.) judged by the buried object judgment unit 24 in the RF data management unit 62.

(Scanning error determination unit 65)
The scanning error determination unit 65 determines whether or not scanning is performed so as to reciprocate along the same path.
Here, a problem that occurs when the same path is not reciprocally moved (also referred to as a position shift) will be described in detail. FIG. 23 is a diagram for explaining a state in which the embedded object detection device is not reciprocating along the same path.

For example, when the user moves the embedded object detection device 1 from the position J to the turning point O so as to cross the embedded object 101 (for example, a reinforcing bar) and scans, the embedded object 101 is embedded at the position K. Can be detected. The image data at this time is shown in FIG. The position K is a position separated from the folding origin O by a distance L.
It is assumed that when the embedded object detection device 1 is moved to the folding origin O and then folded back at the folding origin O to move the embedded object detection device 1 toward the position J, the route is shifted to the position R. In this case, the embedded object 101 cannot be detected at the position of the distance L from the folding origin O. The image data at this time is shown in FIG. FIG. 23C shows the data when the image data from the folding origin O to the position K is folded and moved, and the remaining data is the data of FIG. 23B and the previous position J. The position P1 (Pd) of the embedded object 101 during the movement from the origin to the turn-back origin O is shown.

In this way, when the embedded object detection device deviates from the same path when scanning, the position P1 of the embedded object detected previously may be displayed in the place where the embedded object does not exist.
Therefore, the embedded object detection apparatus 1 of the present embodiment determines a scanning error, and when a scanning error is determined, the previously detected position P1 of the embedded object is erased. As a result, the embedded object can be displayed at a position that should be originally displayed on the shifted route.

FIG. 24 is a block diagram showing the configuration of the scanning error determination unit 65. As shown in FIG. 24, the scanning error determination unit 65 includes a range setting unit 71, a difference calculation unit 72, a counting unit 73, a determination unit 74, and an embedded object position erasing unit 75.
The range setting unit 71 includes a predetermined range S (one example of the first range) in the RF data when scanning along a predetermined path, and a range T (the second range) in the RF data when the RF data is subsequently moved back. Example) is set. The range T and the range S are corresponding ranges.

FIG. 25A and FIG. 25B are diagrams for explaining the setting of the range by the range setting unit 71. FIG. 25A is a diagram for explaining the range S when moving from the position J to the folding origin O. FIG. 25B is a diagram for explaining the range T when moving from the folding origin O toward the position R.
The range S is set to a range of the distance L1 from the detected position K of the buried object toward the folding origin O. Here, it is assumed that the X coordinate value of the position K is X1, and the X coordinate value of the position moved by the distance L1 from X1 toward the folding origin O is X2. In this way, the range S indicates the range of the X coordinate values X1 to X2.

The range T corresponding to the range S is set to the range of the distance L from the folding origin O to the position K, and the distance L1 from the position P moved in the direction of the position R toward the folding origin O. Here, since the distance from the folding origin O is the same, the X coordinate value of the position P is X1 which is the same as the X coordinate value of the position K. Further, the X coordinate value of the position moved by the distance L1 from the coordinate value X1 toward the folding origin O is X2. In this way, the range T also indicates the range of the X coordinate values X1 to X2, and is a range corresponding to the range S.
By setting the range S and the range T from the X-coordinate X1 of the detected position K of the buried object in this way, it is possible to compare in a range in which the change in signal strength is large, and it is easy to determine whether or not the road has deviated. ..

The difference calculation unit 72 compares the signal intensities at the same distance and the same depth position from the folding origin O, as shown in FIGS. As shown in FIGS. 25A and 25B, the range S is divided into a line (X coordinate) and a point sn (an example of the first position) at the depth position (Y coordinate), and the range T is a line. And a point tn at the depth position (an example of the second position). For example, the difference calculation unit 72 determines the difference between the signal intensity fs1 of the point s1 closest to the X coordinate value X1 in the range S and the signal intensity ft1 of the point t1 closest to the X coordinate value X1 in the range T. The absolute value of |fs1-ft1| is calculated.

In this way, the difference calculation unit 72 calculates the absolute value Dn (=|fsn−ftn|) of the difference between the signal intensity fsn of the point sn of the range S and the signal intensity ftn of the point tn of the range T. , Calculate the absolute value of the difference between all corresponding points.
The counting unit 73 counts the number m of points at which the absolute value Dn of the difference calculated by the difference calculation unit 72 is larger than the positional deviation comparison value D0.

When the counted number m is larger than the positional deviation comparison number v, the determination unit 74 determines that the second route that has passed in FIG. 25(b) is the first route that has passed in FIG. 25(a). Since it is out of alignment, it is determined that a scanning error has occurred. On the other hand, when the counted number m is equal to or less than the positional deviation comparison number v, it is determined that a scanning error has not occurred because the first and second paths are not out of alignment.

When the determination unit 74 determines that a scanning error has occurred, the embedded object position erasing unit 75 determines the position P1 (Pd) of the embedded object determined by the first scanning from the RF data management unit 62. It is also deleted from the display of the display unit 8.
As a result, as shown in FIG. 23D, the position P1 of the buried object displayed at the position P is deleted on the display unit 8, and the position Q detected by the scanning from the folding origin O to the position R is deleted. The position P1′ of the buried object is displayed in (see FIG. 23A).

Generally, when the buried object 101 is detected by using the buried object detection apparatus 1, the same route is repeated a plurality of times to reciprocate, so that the averaging processing unit 63 averages the RF data and integrates the buried object data. By updating the position of the buried object in the portion 54, the certainty of the position of the buried object is improved. The embedded object detection apparatus 1 of the present embodiment deletes the position of the embedded object acquired by the scanning up to that time when the road is out of the way during this repetition. This prevents the buried object from being displayed at the previous position when the vehicle is off the road.

As shown in FIGS. 25(a) and 25(b), for example, when determining the deviation of the path from the first movement in the direction of arrow A1, when determining the scanning error of the movement in the direction of arrow A2, A range S of the distance L1 on the folding origin O side from the position K where the embedded object is detected is set as a range for comparison. Further, as shown in FIG. 25B, the range of the distance L1 from the position P of the distance L from the folding origin O (distance from the folding origin O to the position K) when the scanning error is determined to the folding origin O side. R is set as a range corresponding to the range S. In this way, the range on the opposite side to the moving direction when determining the scanning error of the position of the buried object is set as the range S to be compared.

On the other hand, as shown in FIGS. 26(a) and 26(b), for example, when determining the deviation of the path from the first movement in the arrow A1 direction, when determining the scanning error of the movement in the arrow A1 direction, The range S of the distance L1 from the position K where the embedded object is detected to the side opposite to the folding origin O is set as a range to be compared. Further, as shown in FIG. 26B, from the position P of the distance L (distance from the folding origin O to the position K) from the folding origin O during the movement for determining the scanning error to the opposite side of the folding origin O. The range R of the distance L1 is set as the range corresponding to the range S. In this way, the range on the opposite side to the moving direction when determining the scanning error of the position of the buried object is set as the range S to be compared.
The scanning direction can be detected by using a plurality of encoders.

(Display control unit 26)
The display control unit 26 indicates a group, a peak position, and the like on the data image and causes the display unit 8 to display the data image. For example, like the image data on the right side of FIG. 22C, image data obtained by performing grayscale gradation on RF data and the determined position Pd (P1) of the buried object are displayed on the display unit 8.

<Operation>
Next, the operation of the embedded object detection device 1 according to the embodiment of the present invention will be described.
FIG. 27 is a flowchart showing the processing of the embedded object detection device 1.
(Overview of the whole process)
In step S11, the embedded object detection device 1 is first initialized. In the initialization processing, clearing of each data is executed.

Next, when the user moves the embedded object detection device 1, in step S12, the RF data is acquired by using the input from the encoder 7 as a trigger.
Next, in step S13, the averaging processing of the waveform data (RF data) acquired by the averaging processing unit 63 is performed.
Next, in step S14, the scanning error determination unit 65 performs a scanning error determination process. The scanning error determination process is not determined during the first movement. Further, the fact that the robot is continuously and repeatedly moved can be determined by, for example, the encoder being input.

Next, in step S15, the embedded object detection unit 64 performs an embedded object detection process.
Next, step S12 to step S15 will be described in detail.

(Data acquisition process)
FIG. 28 is a flowchart showing the data acquisition process of step S12.
When the data acquisition process is started, the input from the encoder 7 is performed in step S1, and the impulse output control is started in step S2. Based on the pulse from the pulse generation unit 13, the transmission antenna 11 transmits a constant period (for example, Electromagnetic wave pulse is output at 1 MHz).
Next, in step S3, the delay unit 14 sets the Delay time in the DelayIC. For example, the delay time can be set in units of 10 psec from 0 to 5120 psec.

Next, in step S4, the control unit 10 AD-converts the RF data received from the receiving antenna 12 via the gate unit 15.
Next, in step S5, it is determined whether or not the delay time is maximum (for example, 5120 psec), and if not, the control returns to step S3. By repeating steps S3, S4, and S5, data for one line can be acquired.

Next, in step S6, the AD-converted RF data is transmitted to the main control module 6. These steps S1 to S6 are processes performed in the impulse control module 5.
Next, when the worker moves the embedded object detection device 1 in the direction of the arrow A indicating the moving direction, there is an input from the encoder 7, the control of steps S2 to S7 is performed, and the next one line The data is acquired and transmitted to the main control module 6.

Next, in step S7, the receiver 61 waits until it receives RF data for one line from the impulse control module 5, and when the RF data is received, the data acquisition process ends.

(Waveform data averaging process)
Next, the waveform data averaging process in step S13 will be described. FIG. 29 is a flowchart showing the waveform data averaging process.
When the waveform data averaging process is started, in step S171, the averaging processing unit 63 detects whether 1-line RF data exists at the same X coordinate value of the scanning X axis.
Then, if the 1-line RF data acquired so far exists at the same X coordinate value, the averaging processing unit 63, in step S172, the 1-line RF data acquired this time and the 1-line RF acquired so far. The average of the data is calculated and recorded in the RF data management unit 62. More specifically, when the depth direction is the Y axis and the depth position is the Y coordinate value, the averaging processing unit 63 compares the 1 line RF data acquired this time and the 1 line RF data acquired so far. The data of one line is averaged by calculating the average of the signal intensities of the same XY coordinate values.

(Scan error determination process)
Next, the scanning error determination processing will be described. FIG. 30 is a flowchart showing the scanning error determination processing.
When the scanning error determination process is started, first in step S181, the range setting unit 71 determines whether or not there is comparison reference data. Here, the reference data for comparison is data acquired by scanning a predetermined route, and is data in which an embedded object is detected. That is, it is detected whether or not the scan for acquiring the current RF data is a scan further performed to improve the certainty of the position of the buried object after the position of the buried object is detected at least once. If the reference data for comparison does not exist, that is, if the position of the buried object has not been detected yet, the scanning error determination process ends.

Next, in step S182, the range setting unit 71 determines whether or not the X-axis coordinate value at which the detected position of the embedded object exists and the current X-axis coordinate value are within the comparison range. That is, to explain using the example of FIG. 23, the range setting unit 71 causes the X coordinate value of the RF data of one line currently acquired in FIG. 23C to be within the range (L−L1) to L from the folding origin O. It is determined whether or not

Next, in step S183, the range setting unit 71 has the X coordinate value of the 1-line RF data acquired at the input timing of the encoder 7 which is one before the present time smaller than the X coordinate value of the detected position of the embedded object. Or not.
Then, if it is smaller, in step S183, the range setting unit 71 determines whether or not the X coordinate value of the currently acquired 1-line RF data is greater than or equal to the X coordinate value of the detected value of the embedded object. This indicates that the X-coordinate value of the current 1-line RF data is equal to or more than the X-coordinate value X1 of the detection position of the embedded object in the state of scanning in the direction of arrow A1. That is, it is detected whether or not the X coordinate value X1 of the detection position of the embedded object is reached in the scan in the direction of the arrow A1.

On the other hand, if it is not smaller in step S183, the range setting unit 71 determines in step S185 whether the current X-axis coordinate value is equal to or less than the embedded object X coordinate value. This detects whether or not the current X-coordinate value of the 1-line RF data has reached the X-coordinate value x1 of the detected position of the embedded object in the state of scanning in the arrow A2 direction.
In this way, in steps S183 to S185, it is possible to detect whether the X coordinate value x1 of the detected position of the embedded object has been reached in both the scanning in the arrow A1 direction and the scanning in the arrow A2 direction.

In this way, when the X coordinate value of the current 1-line RF data reaches the X coordinate value x1 of the detected position of the embedded object, the range setting unit 71 sets the position shift determination range. Specifically, the range setting unit 71 sets the range S shown in FIG. 23(b) and the range T shown in FIG. 23(c). It should be noted that the range S and the range T can be appropriately changed within a range where the positional deviation can be determined, and are not particularly limited.

Next, in step S187, the positional deviation amount acquisition process is performed by the difference calculation unit 72 and the counting unit 73.
FIG. 31 is a flowchart showing the positional shift amount acquisition processing.
When the positional shift amount acquisition process is started, in step S191, the count unit 73 clears the comparative number to zero.

Next, the difference calculation unit 72 substitutes the position shift search start position in the position shift search counter in step S192. For example, the value of the X coordinate value X1 shown in FIGS. 25(a) and 25(b) is substituted into the misregistration search counter.
Next, in step S193, the difference calculation unit 72 determines whether or not the position shift search counter is smaller than the search end position. Here, the search end position can be the X coordinate value X2 shown in FIGS. 25(a) and 25(b). That is, in steps S192 and S193, it is determined whether or not the difference calculation is performed up to the X coordinate values X1 to X2 (range T), and when the value of the position shift search counter reaches the search end position, the position shift amount acquisition is performed. The process ends.

If the position shift search counter has not reached the search end position in step S193, the difference calculation unit 72 determines in step S194 whether there is one-line latest data of the position shift search counter position. The difference calculation unit 72 detects, for example, whether the latest 1-line RF data exists at the X coordinate value X1.
If the latest 1-line RF data exists, the difference calculation unit 72 sets the 1-line counter number to zero in step S195.

Next, in step S196, the difference calculation unit 72 determines whether or not the 1-line counter number is smaller than the 1-line size. Here, it is detected whether or not the calculation for calculating the difference has been performed for all the data of one line.
Next, in step S197, the difference calculation unit 72 causes the signal intensities of the current misalignment search counter (X1) of the 1-line RF data and the 1-line counter (zero) and the same misalignment search counter of the comparison reference data ( X1) and the absolute value of the difference from the signal strength of the same one-line counter (zero).

Then, when the absolute value of the difference is not within the positional deviation comparison value, in step S199, the counting unit 73 increments the value of the comparison number by +1. This is because the absolute value of the difference between the intensity signal at the point s1 and the intensity signal at the point t1 shown in FIGS. 25A and 25B is calculated, and whether the absolute value of the difference is within the displacement comparison value. It is to judge whether or not.
Next, in step S200, the difference calculation unit 72 increments the 1-line counter value by +1. The control proceeds from step S200 to step S196, and when the 1-line counter number is smaller than the 1-line size, in step S197, the difference computing unit 72 causes the current 1-line RF data misregistration search counter (X1). And the absolute value of the difference between the signal strength of the 1-line counter (1) and the signal strength of the same misregistration search counter (X1) and the same 1-line counter (1) of the reference data for comparison. Here, when the 1-line counter is 1, the signal intensities at points on the deeper side than the previous time are compared. That is, the difference calculator 72 calculates the absolute value of the difference between the intensity signal at the point s2 and the intensity signal at the point t2 shown in FIGS. 25(a) and 25(b), and the absolute value of the difference is compared with the positional deviation. It is determined whether it is within the value.

In this way, when the calculation of the absolute value of the difference and the comparison with the position shift comparison value are completed for all the RF data for one line, the control proceeds from step S196 to step S198, and the difference calculation unit 72 causes the position shift. Increment the search count value by +1. Thereby, the calculation of the absolute value of the difference and the comparison with the positional deviation comparison value (first threshold value) are performed for the data of one line at the X coordinate value next to the X coordinate value X1. As a result, the differences in the signal intensities at all the points in the range S and the range T are calculated, and the number of comparisons whose absolute value of the difference exceeds the positional deviation comparison value is counted. Note that, in step S194, if the latest RF data of one line does not exist at the position shift search counter position, the control proceeds to step S98.

Next, in step S188 of FIG. 30, the determination unit 74 determines whether or not the comparison number is larger than the positional deviation comparison number (an example of the second threshold value). Determine that
When it is determined that the positional deviation has occurred, the positional deviation processing is performed in step S189.

FIG. 32 is a flowchart showing the processing at the time of displacement.
When the position shift processing is started, the embedded object position erasing unit 75 erases the position of the embedded object detected so far in step S110.
Next, in step S111, the latest RF data is registered in the RF data management unit 62 as reference data for comparison.

(Buried object detection process)
FIG. 33 is a flowchart showing the embedded object detection processing.
When the buried object detection process is lent, the pre-processing unit 23 performs a pre-process before determining the buried object in step S201.
Next, in step S202, the embedded object determination unit 24 performs an embedded object determination process.

Next, in step S<b>203, the result (position of the embedded object) determined by the embedded object determination unit 24 is registered by the determination result registration unit 25 and displayed on the display unit 8 by the display control unit 66.
Next, the processing in each step will be described in detail.

(Preprocessing)
FIG. 34 is a flowchart showing the preprocessing.
First, in step S21, the gain adjusting unit 31 adjusts the gain of the RF data for one line.
Next, in step S22, the difference processing unit 32 calculates the difference from the reference value, and the change in the RF data is extracted.
Next, in step S23, the moving average processing unit 33 performs moving average processing on the RF data for one line that has undergone the difference processing. For example, the moving average process can be performed using an 8-point average.

Next, in step S24, the primary differential processing unit 34 performs primary differential processing on the difference result that has been subjected to the moving average processing, and the difference between adjacent data in the depth direction is positive (increase) or negative (decrease). Whether or not it is determined.
Finally, in step S25, the peak detection unit 35 detects the peak of the signal intensity using the result of the first-order differentiation processing.

(Gain adjustment process)
Next, the gain adjustment process of step S21 of FIG. 34 will be described. FIG. 35 is a flowchart showing the gain adjustment processing.
When the gain adjustment process is started, the gain adjustment unit 31 selects the reception data of sequence number 1 from the RF data received by the reception unit 61 in step S31.

Then, after the gain adjusting unit 31 performs the process of step S32 on the signal intensity data of sequence number 1, the control proceeds to step S33.
In step S33, it is determined whether or not the sequence number is the maximum value. If the sequence number is not the maximum value, the control returns to step S31, the sequence number is incremented by 1, and the received data of the sequence number 2 is received. Selected. Then, the process of step S32 is performed on the data of sequence number 2.

In this manner, the process is repeated until the process of step S32 is performed on all the data for one line.
In step S32, the signal strength data of each sequence number is multiplied by a predetermined scale factor.
For example, the sequence No. having the shortest delay time of the RF data of one line. When the data of No. 1 (which can be said to be the data at the shallowest position) is multiplied by a predetermined magnification, the sequence No. 1 is followed by a sequence No. having a short delay time. The data of No. 2 is multiplied by a predetermined magnification, and the predetermined magnification is multiplied in the sequence number order until the sequence number becomes maximum. Specifically, the magnification is increased in the depth direction, and the magnification is set to 1 for the data of 1 to 25 pixels from the shallow side, and set to 2 for the data of 26 to 50 pixels. , The data of 51 to 75 pixels can be set to 3 times and the magnification can be increased in order, and the data of 500 to 511 pixels can be set to 21 times.
By this gain adjustment processing, it is possible to clarify the brightness and darkness as in the image data shown in FIG.

(Differential processing)
Next, the difference processing in step S22 of FIG. 34 will be described. FIG. 36 is a flowchart showing the difference processing.

When the difference processing is disclosed, in step S41, the difference processing unit 32 selects the reception data of sequence number 1 from the gain-adjusted RF data.
Then, after the difference processing unit 32 performs the processing of steps S42 and S43 on the data of sequence number 1, the control proceeds to step S44.
In step S44, it is determined whether or not the sequence number is the maximum value. If the sequence number is not the maximum value, the control returns to step S41, the sequence number is incremented by one, and the received data of the sequence number 2 is received. Selected. Then, the processes of steps S42 and S43 are performed on the data of sequence number 2.

In this way, the flow is repeated until the processes of steps S42 and S43 are performed on all the data for one line.
In step S42, the difference processing unit 32 calculates the average value of the past gain-adjusted reception data up to this line (all reception data received in the past).
Next, in step S43, the difference processing unit 32 sets the calculated average value as the value of the reference point, and calculates the difference between that value and the received data of the current line.

Next, in step S44, the difference processing unit 32 determines whether or not the sequence number is the maximum value, and if the sequence number is not the maximum value, the control returns to step S41 and the number is incremented by one. Thus, the received data of sequence number 2 is selected.
In this way, steps S42 and S43 are repeated until the numbers are sequentially incremented and the difference processing is performed on all the received data of one line.

When the difference processing of the data of the m-th line is performed, the average value of the signal intensities at the 1-m-1st predetermined depth positions is subtracted from the signal intensity at the predetermined depth position of the m-th line. .. Further, when the difference processing is performed on the next m+1-th line, the average value of the 1st to m-th signal intensities is calculated, and the value of the reference point is updated.
By this difference processing, a change in RF data can be extracted as in the image data shown in FIG. 9B.

(First order differential processing of the difference result)
Next, the primary differential processing of the difference result in step S23 of FIG. 34 will be described. FIG. 37 is a flowchart showing the first derivative processing of the difference result.
When the primary differential processing of the difference result is started, in step S51, the primary differential processing unit 34 selects the differential result of sequence number 1 from the differential results.

Next, in step S52, the primary differential processing unit 34 performs primary differential processing of the difference result. Here, the primary differential processing is to calculate the difference between the difference result data at a predetermined position and the difference result data at the next position in the depth direction. That is, the difference between the sequence number 1 and the next sequence number 2 is calculated.
Next, in step S53, it is determined whether or not the sequence number is the maximum value. If the sequence number is not the maximum value, the control returns to step S51, the number is incremented by one, and the sequence number 2 is received. The data is selected. Then, the difference between the sequence number 2 and the sequence number 3 is calculated.

In this way, the numbers are sequentially incremented and step S52 is repeated until the primary differential processing is performed on all the data for one line.
That is, when the primary differential processing of the sequence number n is performed, the primary differential processing is performed on the data of the sequence number n by subtracting the differential result data of the sequence number n from the differential result data of the sequence number n+1. It can be carried out.
As a result, the difference in the third column from the left in the table 150 in FIG. 12 is calculated.

(Peak detection process)
Next, the peak detection process of step S25 of FIG. 34 will be described. FIG. 38 is a flowchart showing the peak detection processing.
When the peak detection process is started, in step S71, the peak detection unit 35 selects the sequence number 1 for which the primary differentiation process has been performed.

Then, the peak detection unit 35 performs the control of steps S72 and S73 for the data of sequence number 1, and then the control proceeds to step S74.
In step S74, it is determined whether or not the sequence number is the maximum value. If the sequence number is not the maximum value, control returns to step S71, the sequence number is incremented by 1, and the received data of sequence number 2 is Selected. Then, the processes of steps S72 and S73 are performed on the data of sequence number 2.

In this way, the numbers are sequentially incremented and the processing of steps S72 and S73 is repeated until the processing is performed on all the data for one line.
Here, assuming that the peak detection processing is performed on the n-th data, steps S72 to S73 will be described.
In step S72, the peak detection unit 35 determines whether or not the state of the previous sequence number n-1 after the primary differentiation is negative (-) and the state of the current sequence number n is positive (+). ..

If the previous sequence number n-1 is negative (-) and the current sequence number n is positive (+), the peak detector 35 stores the nth coordinate in step S73. To do. The coordinates can be indicated by a moving distance (also referred to as a line number) and a depth position in units of pixels.
Thereby, as described above, for example, the sequence number 34 in the table 150 of FIG. 12 can be detected as a peak. This peak is a black (downward) peak.

On the other hand, when a white (upward) peak is detected, when the state after the previous first derivative is “+” and this time is “−”, the current peak is stored to store the white peak. Can be detected. Thereby, the sequence number 5 in the table 150 of FIG. 12 can be detected as an upward peak.

(Underground judgment process)
Next, the buried object determination process shown in step S122 of FIG. 33 will be described. FIG. 39 is a flowchart showing the embedded object determination processing.
When the buried object determination process is started, first, in step S81, the grouping unit 51 performs the peak detection result grouping process performed by the preprocessing unit 23.
Next, in step S82, the shape determination unit 52 performs vertex detection processing.
Next, in step S83, a buried object acquisition process is performed by the buried object position determining unit 53 or the buried object data integrating unit 54.

(Grouping processing of peak detection results)
The grouping process of the peak detection result in step S81 of FIG. 39 will be described. FIG. 40 is a flowchart showing a grouping process of peak detection results.
First, in step S91, the grouping unit 51 sets the detection state to the “undetected” state.

All target data acquired in the past are targeted, and in step S92, the grouping unit 51 selects old data in the past as a target for processing. Then, in step S103, the grouping unit 51 determines whether or not the processing has been performed on all the data acquired in the past up to the line acquired this time. If the processing has not been performed, the control returns to step S92, and Old data is subject to processing. In this way, for example, the processes of steps S93 to S102 are sequentially performed from the sequence number 1 of the oldest line.

In step S93, the grouping unit 51 determines whether the state is undetected. Since the initial state is "undetected", the control proceeds to step S94.
In step S94, the grouping unit 51 determines whether or not the position where the peak is detected is within the predetermined range. When the peak is not detected in the predetermined range, the control proceeds to step S103. The predetermined range can be set as appropriate, and for example, may be set for one line or may be set for the sequence number of one line.

As described above, in step S94, it is determined whether or not there is a position where the peak is detected in order from the old data, and when there is the position where the peak is detected, in step S95, the grouping unit 51 The detection state is set to “detecting”.
Next, in step S96, the grouping unit 51 stores the point where the peak is detected. This point is a coordinate with a pixel as a unit, and can be indicated by, for example, a moving distance (also called a line number) and a depth position. This point corresponds to the starting point (●) in FIG.

Next, through steps S103 and S92, the next data is processed.
Next, in step S93, since the detection state is "detecting", the control proceeds to step S97.
In step S97, the grouping unit 51 determines whether or not there is a peak detected position within a predetermined range from the position stored in step S96. This predetermined range can be set within, for example, 5 pixels within the moving direction described with reference to FIGS. 14A to 14D and within 5 pixels above and below. When the position where the peak is detected is within the predetermined range, the grouping unit 51 determines that there is a continuous position and stores the position in step S98.

Next, in step S99, the grouping unit 51 compares the previous Y coordinate (depth position) with the current Y coordinate (depth position) (see FIG. 14).
Next, in step S100, the grouping unit 51 stores the comparison result as positive (+) or negative (-). Here, when the depth position of this time is shallower than the depth position of the previous time, positive (+) is stored as the depth position is rising. When the depth position of this time is deeper than the depth position of the previous time, a negative (-) is stored as the depth position is descending.

Next, through steps S97 and S92, the next data is processed.
Next, in step S93, since the detection state is "detecting", the control proceeds to step S97.
In this step S97, it is detected whether or not there is a peak-detected point within a predetermined range from the point previously stored in step S98, and if there is, that point is stored in step S99. .. Then, in step S100, the previous point and the comparison result are stored. As a result, as shown in FIG. 13, consecutive points are sequentially grouped, and whether the change to the next point is rising or falling is also stored.

Then, in step S97, when the peak is not detected within the predetermined range, the control proceeds to step S101.
In step S101, the grouping unit 51 determines that there are no consecutive points, and stores the detection results up to that point. The last detected point corresponds to the end point (■) in FIG.

Next, in step S102, the grouping unit 51 sets the detection state to the "undetected" state.
Then, in step S103, when it is determined that the processing has been performed for all the data of the line acquired in the past, the processing ends.

(Vertex detection process)
The vertex detection processing in step S83 of FIG. 39 will be described. FIG. 41 is a flowchart showing the vertex detection processing.
The vertex detection processing is performed on all data as a result of grouping.
When the vertex detection process is started, in step S121, the shape determination unit 52 sequentially selects data from the start point side of the grouped data. For example, in step S121, the shape determination unit 52 sets the data of the change from the first to the second shown in FIGS. 15 and 16 as the processing target.

In step S122, the shape determination unit 52 reads the result of the change from the first to the second.
In step S123, the shape determination unit 52 determines whether or not the result of the change is positive (+). For example, since the change from the first to the second shown in FIGS. 15 and 16 is positive (+), the control proceeds to step S124.

In step S124, the shape determination unit 52 sets the −(minus) count to 0.
Next, in step S125, the shape determination unit 52 determines whether or not the + (plus) count is 0. Since the + (plus) count is 0, the control proceeds to step S126.
In step S126, the shape determination unit 52 stores the first Y coordinate (depth position) and sets the start point.

Next, in step S127, the shape determination unit 52 sets the + (plus) count to +1.
Next, in step S138, the shape determination unit 52 determines whether or not the processing has been completed for all data as a result of grouping, and if not completed, the control returns to step S121, and the next The data (change from second to third) is selected for processing.

Then, in step S122, the shape determination unit 52 reads the result of the change from the second to the third.
Next, in step S123, the shape determination unit 52 determines whether or not the result of the change after the grouping process is positive (+). For example, since the result after the post-grouping processing of the change from the second to the third shown in FIGS. 15 and 16 is positive (+), the control proceeds to step S124.

Next, in step S125, the shape determination unit 52 determines whether or not the + (plus) count is 0. Since the + (plus) count is +1, the control proceeds to step S127.
Then, in step S127, the shape determination unit 52 adds +1 to the + (plus) count and sets it to +2.

In this way, steps S121 to S127 and step S138 are repeated. Then, in step S123, when the result of the change becomes negative (-), the control proceeds to step S128.
In step S128, the shape determination unit 52 determines whether or not the + count is 5 or more. Here, when the count is 5 or more, it means that the condition 1 that the pixel number continuously rises by 5 pixels or more in the Y-axis direction is satisfied.

In the data shown in FIGS. 15 and 16, for example, the change from the 8th to the 9th is negative (−), and there are 7 positive (+) by that time, so the +count becomes 7. There is. Therefore, the control proceeds to step S129.
In step S129, the shape determination unit 52 determines whether or not the −(minus) count is 0. Since the-(minus) count is 0, the control proceeds to step S130.

In step S130, the shape determination unit 52 stores the previous depth position (also referred to as Y coordinate). That is, the shape determination unit 52 stores the Y coordinate of the apex of the mountain (the point where the inclination changes from + to −). In the data of FIGS. 15 and 16, the 8th Y coordinate which is the previous point in the change from the 8th to the 9th is stored.
Next, in step S131, the shape determination unit 52 adds +1 to the-(minus) count.

Next, in step S132, the shape determination unit 52 determines whether the-(minus) count is 5 or more. Here, when the count is 5 or more, it means that the condition 2 in which the count is continuously decreased by 5 pixels or more in the Y-axis direction is satisfied. In the case of the change from the 8th to the 9th, the −count is +1. Therefore, the control proceeds to step S138, and the change from the 9th to the 10th is selected as a processing target through step S121.

In this way, when the changes are sequentially selected and the change from the 12th to the 13th is selected as the processing target, the −(minus) count in step S132 becomes +5 or more, and thus the control proceeds to step S133. move on.
In step S133, the shape determination unit 52 calculates the difference between the Y coordinate of the starting point and the Y coordinate of the vertex. With the data in FIGS. 15 and 16, the difference between the first Y coordinate and the eighth Y coordinate is calculated.

Next, in step S134, the shape determination unit 52 determines whether or not the calculated difference is 10 or more. Here, when it is 10 or more, the condition 3 that the difference in the Y-axis direction is 10 pixels or more is satisfied.
When the calculated difference is 10 or more, in step S135, the shape determination unit 52 determines that the gusset and the loop have a mountain shape, and determines that an embedded object exists.
On the other hand, when the calculated difference is less than 10, the control proceeds to step S138.

(Buried object acquisition process)
Next, the buried object acquisition process in step S83 of FIG. 39 will be described. FIG. 42 is a flowchart showing the buried object acquisition processing.
When the buried object acquisition process is started, the buried object position determination unit 53 detects the pattern of the combination of vertices detected by the above-described vertex detection process (see FIG. 17) in step S141.

Next, in step S142, the embedded object position determination unit 53 determines whether or not the detected pattern is other than C (that is, any of the patterns A1, A2, B1, and B2 having two or more peaks). If the detected pattern is C, the embedded object acquisition process is terminated without setting the position of the embedded object.
On the other hand, when the detected pattern is other than C and the pattern is detected by the previous scan, the buried object position determination unit 53 follows the buried object data (pattern) according to the buried object data transition table shown in FIG. And the determined position of the buried object) is updated and stored in the RF data management unit 62.

(Judgment result display process)
In the determination result display process shown in step S203 of FIG. 33, the display control unit 26 controls the display unit 8 to display a ● in the image data in order to indicate the position of the buried object acquired by the buried object acquisition process. (See, for example, FIG. 18B).
In the case of the example shown in FIG. 15, the display control unit 26 causes the display unit 8 to display an image with a ● mark at the position of the eighth data, which is the apex.

[Other Embodiments]
Although one embodiment of the present invention has been described above, the present invention is not limited to the above embodiment, and various modifications can be made without departing from the gist of the invention.
(A)
In the above embodiment, the control method of the embedded object detection device 1 and the main control module 6 (an example of the data processing device) has been described by way of an example in which it is executed according to the flowcharts shown in FIGS. 27 to 42. It is not limited.

For example, the present invention may be implemented as a program that causes a computer to execute the embedded object detection device 1 and the embedded object detection method implemented according to the flowcharts shown in FIGS. 27 to 42.
Further, one usage form of the program may be a mode in which the program is recorded in a recording medium such as a ROM readable by a computer and operates in cooperation with the computer.

Further, one usage form of the program may be a mode in which the program is transmitted through a transmission medium such as the Internet or a transmission medium such as light, radio waves, sound waves, read by a computer, and operates in cooperation with the computer.
The computer described above is not limited to hardware such as a CPU (Central Processing Unit), but may include firmware, an OS, and peripheral devices.
As described above, the method of controlling the power consuming body may be realized by software or hardware.

(B)
In the above-described embodiment, the reinforcing bar is described as an example of the buried object, but it is not limited to the reinforcing bar, and may be a gas pipe, a water pipe, wood, or the like, and the buried object is provided. The target object is not limited to concrete.

(C)
In the above-described embodiment, black is set to indicate the reinforcing bar by gradation processing, but the present invention is not limited to this, and white may be set to indicate the reinforcing bar.
(D)
In the above-described embodiment, in step S88, it is determined whether or not the number of comparisons is larger than the number of positional deviation comparisons as the lower limit value, but the upper limit value may be set.

(E)
In the above embodiment, the embedded object position erasing unit 75 erases the previously acquired embedded object data (the pattern and the determined position of the embedded object). You may notify that it occurred. For example, as shown in FIG. 43, the scanning error determination unit 65′ further includes a notification unit 76, and when a scanning error is detected, the user may be notified of the scanning error by a warning sound or a display. good.

(F)
In the above embodiment, the main control module 6 is provided in the main body 2 of the embedded object detection device 1, but the main control module 6 may be provided separately from the main body 2. In this case, the main control module 6 and the display unit 8 may be provided on the tablet or the like. Communication between the main body 2 and the tablet may be performed wirelessly or by wire.

(G)
In the above-described embodiment, the range S to be compared when determining a scanning error is set to include the detection position Pd of the embedded object, but the range S is not limited to this. The range S does not have to include the detection position of the buried object, but it is preferable to set the range S near the detection position Pd of the buried object because it is easier to determine the scanning error when the change in the signal intensity is large. ..

The buried object detecting apparatus and the buried object detecting method of the present invention have the effect of improving the accuracy of the position of the buried object, and are useful for detecting the buried object in concrete.

1 :Buried object detection device 2 :Main body 3 :Grip 4 :Wheel 5 :Impulse control module 6 :Main control module 7 :Encoder 8 :Display section 10 :Control section 11 :Transmission antenna 12 :Reception antenna 13 :Pulse generation section 14: delay unit 15: gate unit 23: preprocessing unit 24: buried object determination unit (an example of buried object position detection unit)
25: Judgment result registration unit 26: Display control unit 31: Gain adjustment unit 32: Difference processing unit 33: Moving average processing unit 34: First derivative processing unit 35: Peak detection unit (an example of signal intensity peak detection unit)
51: Grouping unit 52: Shape determination unit (an example of a depth position peak detection unit)
53: buried object position determining section 54: buried object data integrating section 61: receiving section 62: RF data managing section 63: averaging processing section 64: buried object detecting section 65: scanning error judging section 65': scanning error judging section 66 : Display control unit 71: Range setting unit 72: Difference calculation unit 73: Count unit 74: Judgment unit 75: Buried object position erasing unit 76: Notification unit 100: Concrete 100a: Surface 101: Buried object 101a: Buried object 101b: Buried Object 101c: buried object 101d: buried object

Claims

An embedded object detection device for detecting an embedded object in the object by using data relating to a reflected wave of an electromagnetic wave emitted toward the object while moving on the surface of the object,
A receiving unit that receives data regarding the reflected wave for each timing accompanying movement,
An embedded object detection unit that detects the embedded object using data regarding the reflected wave when reciprocating along the same path on the surface of the object,
Data relating to the reflected wave in a predetermined first range in the first movement when the buried object is detected, and second data corresponding to the first range in the second movement after the first movement. Comparing with the data on the reflected wave of the range, a scanning error determination unit for determining whether or not to be scanned so as to reciprocate the same path, and,
Buried object detection device.
The scanning error determination unit,
When it is determined that the same route is not reciprocatingly moved, the embedded object position erasing unit that erases the detected position of the embedded object detected by the movement of the route before the movement of the route when it is determined. The embedded object detection device according to claim 1, further comprising:
The scanning error determination unit,
The buried object detection device according to claim 1, further comprising a notification unit that notifies a user that a scanning error has occurred when it is determined that the user does not reciprocate along the same route.
The first range is a range including a detection position where the buried object is detected, or a range in the vicinity of the detection position,
The buried object detection device according to claim 1.
The embedded object detection device according to claim 1 or 4, wherein the first range and the second range are the same distance from a turnaround position in the reciprocating movement.
The first range includes the detection position, and is a range before the detection position in the second movement,
The buried object detection device according to claim 4.
The buried object detection unit,
A signal intensity peak detection unit that detects a peak of the signal intensity in the depth direction of the object at each of the timings,
An embedded object position detection unit that detects a position of the embedded object based on a peak of the signal intensity detected at each of the timings,
The buried object detection device according to claim 1.
The scanning error determination unit compares the signal strength at the depth position in the depth direction for each timing in the first range with the signal strength at the depth position in the depth direction for each timing in the second range. Then, it is determined whether or not scanning is performed so as to reciprocate along the same route.
The buried object detection device according to claim 7.
The first range includes a plurality of first positions specified by the timing and the depth position,
The second range includes a plurality of second positions specified by the timing and the depth position,
The scanning error determination unit,
A difference calculator that calculates a difference between the signal strength at each of the first positions and the signal strength at the second position corresponding to each of the first positions;
A counting unit that counts the number of the differences equal to or greater than a first threshold;
A determination unit that determines whether or not the count number is equal to or greater than a second threshold value, and that determines a scanning error when the count number is equal to or greater than the second threshold value,
The buried object detection device according to claim 8.
The buried object detection unit,
In the depth direction or the surface direction opposite thereto, further comprising a difference processing unit that detects a difference in change in signal intensity at a predetermined depth position from the signal intensity at the preceding depth position.
The buried object detection device according to claim 7.
The signal strength peak detection unit,
At least one of a depth position at which the difference changes from decrease to increase and a depth position at which the difference changes from increase to decrease is detected as a peak of the signal strength,
The buried object detection device according to claim 10.
The buried object detection unit,
Of the depth positions at the peak of the signal intensity detected at each of the timings, the depth positions at a plurality of the peaks of the signal intensity that are consecutive within a predetermined interval in the moving direction are set as one group. Grouping part,
In a plane in the moving direction and the depth direction, a depth position peak detection unit that detects a peak of the depth position of the group, and
The buried object detection device according to claim 11.
The buried object detection unit,
The embedded object detection device according to claim 12, further comprising an embedded object position determination unit that sets the position of the embedded object based on the detected peak of the depth position.
In the predetermined range, the buried object position determination unit has the peak of the depth position in the group of the peaks of the signal strength changing from decrease to increase and the peak of the peak of the signal strength changing from increase to decrease in the group. Either one of the peaks at the depth position is detected, and if there is no peak at another depth position within a predetermined range from the peak, the detected peak is not set as the position of the buried object,
The buried object detection device according to claim 13.
The buried object position determination unit,
The peak of the depth position in the group of the peak of the signal strength changing from decrease to increase, and the peak of the depth position in the group of the peak of the signal strength changing from increase to decrease within a predetermined range. When adjacent to each other, the position of the shallower peak is set to the position of the buried object,
The buried object detection device according to claim 13.
The buried object position determination unit,
Three peaks at the depth position in the group of the peaks of the signal strength changing from decrease to increase and three peaks at the depth position in the group of the peaks of the signal strength changing from increase to decrease are alternated. When existing adjacent to each other within the above predetermined range, the position of the shallowest peak is set to the position of the buried object,
The buried object detection device according to claim 13.
The buried object position determination unit,
In the reciprocating movement, the position of the buried object is adopted when the number of peaks at the adjacent depth positions is large.
The buried object detection device according to claim 13.
The depth position peak detection unit,
In the plane in the moving direction and the depth direction, if the group has a predetermined shape, it is determined that the buried object exists, if not the predetermined shape, it is determined that the buried object does not exist,
The buried object detection device according to claim 12.
The buried object detection unit,
An average that averages the signal strength in the depth direction of the object at each of the timings with the signal strength in the depth direction of the object at each of the timings received earlier during the reciprocating movement. Further having a chemical processing unit,
The buried object detection device according to claim 1.
In the reciprocating movement, further comprising a display unit for displaying a signal intensity on a plane in the movement direction and the depth direction for each movement,
The display section, when the buried object is detected, shows the detected position of the buried object together with the display,
The buried object detection device according to claim 1.
The display unit erases the detected position of the embedded object when it is determined that the embedded unit is not reciprocating along the same path.
The buried object detection device according to claim 20.
A buried object detection method for detecting a buried object in the object using data regarding a reflected wave of an electromagnetic wave radiated toward the object while moving on the surface of the object,
A receiving step of receiving data regarding the reflected wave for each timing accompanying movement,
An embedded object detecting step of detecting the embedded object using data regarding the reflected wave when reciprocating along the same path on the surface of the object;
Data relating to the reflected wave in a predetermined first range in the first movement when the buried object is detected, and second data corresponding to the first range in the second movement after the first movement. Comparing with the data on the reflected wave of the range, the scanning error determination step of determining whether or not to be scanned so as to reciprocate the same path, comprising:
Buried object detection method.
When it is determined that the same route is not reciprocating, the embedded object position erasing step of erasing the detected position of the embedded object detected by the movement of the route before the movement of the route when it is determined. 23. The embedded object detection method according to claim 22, further comprising: