JP6984582B2 - Buried object detection device and buried object detection method - Google Patents

Description

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

As a device for searching for buried objects in concrete, a buried object detecting device for detecting buried objects from reflected waves of electromagnetic waves radiated toward concrete while moving the surface of concrete is used (for example, Patent Document 1). reference).
While scanning the buried object detection device, the presence or absence of the buried object is detected by repeatedly operating the device so as to reciprocate between two points on the same path. By scanning between one point and the other, distance information is acquired by the encoder installed in the buried object detection device, and the signal strength is displayed in color on a plane with two axes, the route direction and the depth direction. be able to. When the position of the buried object is detected each time the scanning between the two points is repeated, the certainty of the position of the buried object can be improved based on the position of the buried object detected a plurality of times.

Japanese Patent No. 5789088

However, in the case of the conventional buried object detection device, if the buried object is detected and then scanned further off the path, the buried object is detected at a position different from the position of the buried 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 a buried object detecting device and a buried object detecting method capable of improving the certainty of the position of a buried object.

The buried object detecting device according to the first invention is a buried object detecting device that detects buried objects in an object by using data on reflected waves of electromagnetic waves radiated toward the object while moving on the surface of the object. It is provided with a receiving unit, a buried object detection unit, and a scanning error determination unit. The receiving unit receives data related to the reflected wave at each timing associated with the movement. The buried object detection unit detects the buried object by using the data on the reflected wave when reciprocating on the same path on the surface of the object. The scanning error determination unit corresponds to the data regarding the reflected wave in the 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 related to the reflected wave in the second range is compared with the data, and it is determined whether or not the data is scanned so as to reciprocate on the same route.

In this way, since it can be determined that the route is off the same path, for example, by clearing the position of the buried object detected before the determination, the position of the buried object can be detected again from the beginning. Alternatively, by notifying the user that he / she has deviated from the same route, the position of the detected buried object can be erased by the user. Alternatively, only the position of the buried object detected when deviating from the same path can be erased.

As described above, it is possible to improve the certainty of the position of the buried object by detecting that it deviates from the same path.
Further, for example, if the difference between the data related to the reflected wave in the first range and the data related to the reflected wave in the second range is within a predetermined error range, it is assumed that the same data is received, and the data moves back and forth on the same route. It can be judged that it is doing. On the other hand, if the difference between the data related to the reflected wave in the first range and the data related to the reflected wave in the second range is larger than the predetermined error range, it is assumed that different data are received and the data moves back and forth on the same route. It can be judged that it is not.

The buried object detecting device according to the second invention is the buried object detecting device according to the first invention, and the scanning error determination unit has a buried object position erasing unit. When it is determined that the buried object position erasing unit does not reciprocate on the same route, the buried object position erasing unit erases the detected position of the buried object detected by the movement of the route before the movement of the route at the time of determination.
As a result, the position of the buried object can be detected again from the beginning, so that the certainty of the position of the buried object can be improved.

The buried object detection device according to the third invention is the buried object detection device according to the first invention, and 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 vehicle is not reciprocating on the same route.

The buried object detection device according to the fourth invention is the buried object detection device according to the first invention, and the first range is a range including a detection position where a buried object is detected or a range near the detection position. Is.
Since the data on the reflected wave changes greatly at the position of the buried object, by comparing the data on the reflected wave in the first range and the data on the reflected wave in the second range, it is possible to reciprocate on the same route. Can be detected more accurately.

The buried object detecting device according to the fifth invention is the buried object detecting device according to the first or fourth invention, and the first range and the second range are the same distance from the turning position in the reciprocating motion.
Here, the distance is obtained by converting from the timing accompanying the movement. Since data on similar reflected waves can be detected when following the same route within the same distance from the turning position, reciprocating on the same route by comparing the data on the reflected waves in the first range and the second range. It is possible to detect whether or not it is done.

The buried object detecting device according to the sixth invention is the buried object detecting device according to the fourth invention, and the first range includes the detection position and is the range before the detection position in the second movement.
This makes it possible to determine as quickly as possible that they are not following the same path.

The buried object detection device according to the seventh invention is the buried object detection device according to the first invention, and the buried object detecting unit includes a signal intensity peak detecting unit and a buried object position detecting unit. The signal strength peak detection unit detects the peak of the signal strength in the depth direction of the object at each timing. The buried object position detecting unit detects the position of the buried object based on the peak of the signal strength detected at each timing.
This makes it possible to detect the position of the buried object based on the signal strength.

The buried object detection device according to the eighth aspect of the invention is the buried object detection device according to the seventh invention, and the scanning error determination unit determines the signal strength at the depth position in the depth direction for each timing in the first range. , The signal strength at the depth position in the depth direction for each timing in the second range is compared, and it is determined whether or not the scanning is performed so as to reciprocate on the same route.
For example, if the difference between the signal strength at the depth position for each timing in the first range and the signal strength at the depth position for each timing in the second range is within a predetermined error range, the same data is received. If so, it can be determined that the vehicle is reciprocating on the same route. On the other hand, if the difference between the signal strength at the depth position for each timing in the first range and the signal strength at the depth position for each timing in the second range is larger than the predetermined error range, different data is received. If so, it can be determined that the vehicle is not reciprocating on the same route.

The buried object detecting device according to the ninth invention is the buried object detecting device according to the eighth invention, and the first range includes a plurality of first positions specified by timing and depth positions. The second range includes a plurality of second positions identified by timing and depth positions. The scanning error determination unit includes a difference calculation unit, a count unit, and a determination unit. The difference calculation unit 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 greater than the first threshold value. The determination unit determines whether or not the count number is equal to or greater than the second threshold value, and if the count number is equal to or greater than the second threshold value, determines that a scanning error occurs.
As a result, if the difference between the signal strength in the first range and the signal strength in the second range is within a predetermined error range, it is determined that the same data is being received and the vehicle is reciprocating on the same route. can do.

The buried object detecting device according to the tenth invention is the buried object detecting device according to the seventh invention, and the buried object detecting unit further includes a difference processing unit. The difference processing unit detects the difference in the change in the signal strength at a predetermined depth position from the signal strength at the previous depth position in the depth direction or the surface direction vice versa.
This makes it possible to extract changes in signal strength due to the influence of buried objects.

The buried object detecting device according to the eleventh invention is the buried object detecting device according to the tenth invention, and the signal intensity peak detecting unit has a depth position in which the difference changes from a decrease to an increase and a difference decreases from an increase. At least one of the depth positions changing to is detected as the peak of the signal strength.
In this way, the peak of the signal strength can be detected by using the data of the increase / decrease in the signal strength.

The buried object detecting device according to the twelfth invention is the buried object detecting device according to the eleventh invention, and the buried object detecting unit includes a grouping unit and a depth position peak detecting unit. The grouping unit groups the depth positions of a plurality of signal strength peaks that are continuous within a predetermined interval in the moving direction among the depth positions of the signal strength peaks detected at each timing. .. The depth position peak detection unit detects the peak at the depth position of the group in the plane in the moving direction and the depth direction.
In this way, continuous peaks are grouped into one group, and the position of the buried object can be detected by detecting the peak at the depth position in the group.

The buried object detecting device according to the thirteenth invention is the buried object detecting device according to the twelfth invention, and the buried object detecting unit further includes a buried object positioning unit. The buried object positioning unit sets the position of the buried object based on the peak of the detected depth position.
This makes it possible to determine the position of the buried object.

The buried object detecting device according to the fourteenth invention is the buried object detecting device according to the thirteenth invention, and the buried object positioning unit is a group of peaks of signal strength changing from a decrease to an increase within a predetermined range. One of the peak at the depth position and the peak at the depth position in the group of peaks of signal intensity changing from increase to decrease is detected, and the peak at the other depth position exists within a predetermined range from the peak. If not, the detected peak is not set as the location of the buried object.
This makes it possible to set the position of the buried object with one detected peak.

The buried object detecting device according to the fifteenth invention is the buried object detecting device according to the thirteenth invention, and the buried object positioning unit is a depth position in a group of peaks of signal strength changing from a decrease to an increase. If the peaks and the peaks at the depth position in the group of peaks of signal intensity changing from increase to decrease are adjacent to each other within a predetermined range, the position of the shallower peak is set at the position of the buried object.
As a result, the position of the shallower peak can be set as the position of the buried object.

The buried object detecting device according to the sixteenth invention is the buried object detecting device according to the thirteenth invention, and the buried object positioning unit is the depth position in the group of peaks of signal strength changing from decreasing to increasing. When three or more peaks at the depth position in the group of peaks of signal intensity changing from increase to decrease are alternately present next to each other within a predetermined range, the position of the shallowest peak is the buried object. Set to position.
This allows the position of the shallowest peak to be the position of the buried object.

The buried object detecting device according to the seventeenth invention is the buried object detecting device according to the thirteenth invention, and the buried object positioning unit has a large number of peaks at adjacent depth positions in reciprocating motion. Adopt the position of the buried object.
This makes it possible to improve the accuracy of the position of the buried object.

The buried object detection device according to the eighteenth invention is the buried object detection device according to the twelfth invention, and the depth position peak detection unit has a group having a predetermined shape in a plane in a moving direction and a depth direction. If so, it is determined that the buried object exists, and if it does not have a predetermined shape, it is determined that the buried object does not exist.
In this way, when the peaks continue 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.

The buried object detecting device according to the nineteenth invention is the buried object detecting device according to the first invention, and the buried object detecting unit further includes an averaging processing unit. During the reciprocating motion, the averaging processing unit averages the signal strength in the depth direction of the object at each timing with the signal strength in the depth direction of the object at each timing received before that. ..
This makes it possible to improve the certainty of the position of the buried object by scanning the same route a plurality of times.

The buried object detecting device according to the twentieth invention is the buried object detecting device according to the first invention, and further includes a display unit. In the reciprocating movement, the display unit displays the signal strength in the planes in the movement direction and the depth direction for each movement. When a buried object is detected, the display unit indicates the detection position of the buried object together with the display.
By displaying the detection position of the buried object in this way, the user can easily recognize the position of the buried object.

The buried object detection device according to the twenty-first invention is the buried object detection device according to the twentieth invention, and the display unit detects a buried object when it is determined that the display unit does not reciprocate on the same route. Erase.
By erasing the detection position of the buried object when a scanning error is detected, it is possible to prevent the buried object from being displayed at a position that does not exist in the movement when the scanning error is detected, and the user is not confused.

The buried object detection method according to the 22nd invention is a buried object detection method for detecting a buried object in an object by using data on reflected waves of electromagnetic waves radiated toward the object while moving on the surface of the object. It includes a reception step, a buried object detection step, and a scanning error determination step. The reception step receives data on the reflected wave at each timing associated with the movement. The buried object detection step corresponds to data on the 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 related to the reflected wave in the second range is compared with the data, and it is determined whether or not the data is scanned so as to reciprocate on the same route.

In this way, since it can be determined that the route is off the same path, for example, by clearing the position of the buried object detected before the determination, the position of the buried object can be detected again from the beginning. Alternatively, by notifying the user that he / she has deviated from the same route, the position of the detected buried object can be erased by the user. Alternatively, only the position of the buried object detected when deviating from the same path can be erased.

As described above, it is possible to improve the certainty of the position of the buried object by detecting that it deviates from the same path.
Further, for example, if the difference between the data related to the reflected wave in the first range and the data related to the reflected wave in the second range is within a predetermined error range, it is assumed that the same data is received, and the data moves back and forth on the same route. It can be judged that it is doing. On the other hand, if the difference between the data related to the reflected wave in the first range and the data related to the reflected wave in the second range is larger than the predetermined error range, it is assumed that different data are received and the data moves back and forth on the same route. It can be judged that it is not.

The buried object detecting method according to the 23rd invention is the buried object detecting method according to the 22nd invention, further comprising a buried object position erasing step. The buried object position erasing step erases the detected position of the buried object detected by the movement of the route before the movement of the route when it is determined that the reciprocating motion is not performed on the same route.
As a result, the position of the buried object can be detected again from the beginning, so that the certainty of the position of the buried object can be improved.

According to the present invention, it is possible to provide a buried object detecting device and a buried object detecting method capable of improving the certainty of the position of the buried object.

The perspective view which shows the structure of the buried object detection apparatus in embodiment which concerns on this invention. The block diagram which shows the structure of the buried 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 acquired by the MPU of FIG. The block diagram which shows the structure of the main control module of FIG. (A)-(c) The figure for demonstrating the processing by the averaging processing unit of FIG. The block diagram which shows the structure of the buried object detection part of FIG. (A) A diagram showing image data before gain adjustment, and (b) a diagram showing image data after gain adjustment processing. (A) A diagram showing image data before the difference processing, and (b) a diagram showing the image data after the difference processing. (A) A diagram showing image data after performing moving average processing, and (b) a diagram showing signal strength of RF data of line L1 in FIG. 10 (a). An enlarged view between P10 and P3 in FIG. 10 (b). The figure for demonstrating the processing by the first derivative processing part. The figure which shows the image data after preprocessing. (A)-(d) The figure for demonstrating the processing by a grouping part. The figure which shows the position of a plurality of grouped peaks. No. shown in FIG. 1-No. The figure which shows the change of the position of the adjacent peak up to 15. The figure which shows the pattern of the detected peak. (A) A diagram showing image data in which three adjacent peaks are detected, and (b) a diagram showing an example of the position of a determined buried object. (A) A diagram showing image data in which two adjacent peaks are detected, and (b) a diagram showing an example of the position of a determined buried object. (A) A diagram showing image data in which adjacent peaks are not detected and one peak is detected, and (b) a diagram showing a state in which the position of a buried object is not determined. The figure which shows the 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 which the buried object detection device does not reciprocate on the same path (the state which is misaligned). The block diagram which shows the structure of the scan error determination part of FIG. (A), (b) The figure for demonstrating the setting of the range by the range setting part of FIG. 24. (A), (b) The figure for demonstrating the setting of the range by the range setting part of FIG. 24. The flow chart which shows the processing of the buried object detection apparatus 1. The flow chart which shows the data acquisition process of FIG. 27. The flow chart which shows the waveform data averaging process of FIG. FIG. 2 is a flow chart showing a scanning error determination process of FIG. 27. FIG. 3 is a flow chart showing a misalignment amount acquisition process of FIG. 30. The flow chart which shows the misalignment processing of FIG. FIG. 2 is a flow chart showing a buried object detection process of FIG. 27. The flow chart which shows the preprocessing of FIG. 33. The flow diagram which shows the gain adjustment process of FIG. 33. The flow diagram which shows the difference processing of FIG. 33. FIG. 3 is a flow chart showing a first-order differential process of the difference result of FIG. 33. The flow chart which shows the peak detection processing of FIG. 33. FIG. 3 is a flow chart showing a buried object determination process of FIG. 33. The flow chart which shows the grouping process of FIG. 39. The flow chart which shows the vertex detection process of FIG. 39. FIG. 9 is a flow chart showing a 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.

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

The buried 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 the concrete 100, and receives and analyzes the reflected wave to bury the object in the concrete 100. The positions of objects 101a, 101b, 101c, and 101d are detected. The buried object detection device 1 reciprocates the same path (see arrows A1 and A2) to increase the certainty of the positions of the buried objects 101a, 101b, 101c, and 101d.

In FIG. 1, the buried objects 101a, 101b, 101c, and 101d are reinforcing bars, and are, for example, buried at depths of 20 cm, 15 cm, 10 cm, and 5 cm in order from the surface 100a. The depth direction is indicated by the arrow B, and the surface direction is indicated by the arrow C.
The buried object detection device 1 includes a main body portion 2, a handle 3, a wheel 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 lower part of the main body 2. When detecting the buried object inside the concrete 100, the operator moves the buried object detecting device 1 on the surface 100a of the concrete 100 while grasping the handle 3 and rotating the wheel 4.
The impulse control module 5 controls the timing of radiating an electromagnetic wave toward the concrete 100, the timing of receiving the reflected wave of the radiated 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 data on 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 buried 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 includes a control unit 10, a transmitting antenna 11, a receiving antenna 12, a pulse generating unit 13, a delay unit 14, and a gate unit 15.
The control unit 10 is composed of an MPU (Micro Processing Unit) or the like, and commands the pulse generation unit 13 to generate a pulse by using an encoder input as a trigger. The pulse generation unit 13 generates a pulse based on a command from the MPU and sends it to the transmission antenna 11. The transmitting antenna 11 radiates an electromagnetic wave at a fixed cycle based on the pulse cycle. The input timing of the encoder 7 corresponds to an example of 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 takes in the reflected wave received by the receiving antenna 12 and transmits it to the control unit 10. The delay unit 14 transmits a pulse to the gate unit 15 at predetermined intervals to capture the reflected wave. This predetermined interval is, for example, a 2.5 mm pitch.
As a result, the impulse control module 5 outputs electromagnetic waves from the transmitting antenna 11 a plurality of times, triggered by the input from the encoder or 7. Then, the impulse control module 5 can acquire the reception data for each distance from the reception antenna 12 by delaying the reception timing by using the delay IC by the delay unit 14.

FIG. 4 is a diagram showing data of reflected waves acquired by the MPU. The vertical axis indicates the intensity of the received signal in a gradation of −4096 to +4096 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 arrow direction (corresponding to the depth direction B) indicates that the distance from the receiving antenna 12 is long. Further, a long distance corresponds to a deep depth.

Although the details will be described later, since the waveform W1 shown in FIG. 4 includes the reflected wave reflected by the antenna without being irradiated in the concrete 100 (p1 etc.), the difference from the reference waveform is calculated. , Changes in reflected wave data from within the concrete 100 are extracted.
Further, the data shown in FIG. 4 is data from the time when the input of the encoder 7 is input to the time when the input of the encoder 7 is next. By gradually delaying the reception timing, the reflected wave is received from a position that is a long distance from the receiving antenna 12, but if there is an input from the encoder 7, the delay in the reception timing is restored and the reception timing is reset again. Gradually delay. That is, the reflected wave in the depth direction B at the predetermined measurement position in the moving direction A (the position where the input from the encoder 7 is received) is received. The reflected wave data from the input of the encoder 7 shown in FIG. 4 to the input of the next encoder is referred to as data for one line. Each time the data for one line is accumulated, the control unit 10 transmits the RF (Radio Frequency) data for one line to the main control module 6.

Since the buried object detection device 1 is moved, the measurement positions are not exactly the same, and the depth direction B is not exactly 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 receiving unit 61, an RF data management unit 62, an averaging processing unit 63, a buried object detection unit 64, a scanning error determination unit 65, and a display control unit 66.

The receiving unit 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 RF data for one line received by the reception unit 61.
The averaging processing unit 63 averages the one-line waveform data when it moves along the path two or more times. For example, if the route is moved toward the arrow A1 shown in FIG. 1 for the first time and then turned back and moved in the direction of the arrow A2 for the second time, the distance from the turning point is different in the first and second times. The average of the signal intensities at the same measurement position in the same depth direction is calculated.

The buried object detection unit 64 detects the peak of the signal intensity for each averaged line of data, determines the presence or absence of the buried object 101 using the signal intensity peak, and detects the position of the buried object 101. ..
The scanning error determination unit 65 determines whether or not the scanning is performed so as to reciprocate on the same route.

The display control unit 66 controls the display unit 8 to display an image in which the signal intensity is gradation-processed by color in the planes of the moving direction A and the depth direction B. Further, the display control unit 66 controls the display unit 8 to display the position of the buried object 101.
(Average processing unit 63)
The averaging processing unit 63 performs averaging processing of RF data. 6 (a) to 6 (c) are diagrams for explaining the averaging process.

The third figure from the right end of FIGS. 6A to 6C is a front view of a wall (an example of an object), and reinforcing bars as a buried object 101 are embedded along the vertical direction. ..
Here, it is assumed that the buried object detection device 1 is reciprocated between the points E and F so as to cross the buried object 101. As shown in FIG. 6A, when the buried object detection device 1 is moved from the point E to the point F for the first time, the receiving unit 61 of the encoder 7 from the point E to the point F along the moving direction A1. Each time there is an input, 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 figure of FIGS. 6A to 6C shows the intensity signal on the XY coordinate plane with the position in the scanning direction converted from the input of the encoder 7 as the X axis and the position in the depth direction as the Y axis. It is a figure which shows the strength of a black-and-white gradation.

Next, as shown in FIG. 6B, when the data is moved from the point F to the point E for the second time, the receiving unit 61 receives RF for a plurality of lines from the point F to the point E along the moving direction A2. The 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 strengths of the same XY coordinate values in the first and second times for all the XY coordinate values on the XY plane from the point E to the point F, and causes the RF data management unit 62 to calculate the average. It will be remembered.

Next, as shown in FIG. 6C, when the data is moved from the point E to the point F for the third time, the receiving unit 61 receives RF for a plurality of lines from the point E to the point F along the moving direction A1. The 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 route a plurality of times in this way, RF data can be averaged, noise can be reduced, and the position of a 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 buried object detection unit 64.
The buried object detection unit 64 includes a pretreatment unit 23, a buried object determination unit 24 (an example of a buried object position detection unit), and a determination result registration unit 25.

The preprocessing unit 23 detects the peak of the signal strength for each averaged line of data.
The buried object determination unit 24 determines the presence or absence of the buried object by using the peak of the signal strength for each RF data for one line detected by the pretreatment unit 23. Further, the buried object determination unit 24 detects the position of the buried 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.
(Pretreatment unit 23)
As shown in FIG. 7, the pre-processing unit 23 includes a gain adjusting unit 31, a difference processing unit 32, a moving average processing unit 33, a primary differential processing unit 34, and a peak detection unit 35 (signal intensity peak detection unit). An example) and.

(Gain adjusting unit 31)
The gain adjusting unit 31 adjusts the gain with respect to the RF data averaged for each line. Since the distance from the transmitting antenna 11 and the receiving antenna 12 becomes large (when the delay time becomes large), the receiving sensitivity becomes weak, so that the shades of white and black are reduced when displaying the image described later. Therefore, the gain adjusting unit 31 increases the gain value (× 1 × 20) multiplied (amplified) by the signal strength as the depth position becomes deeper.

FIG. 8A is a diagram showing image data before gain adjustment is performed. In the detection image shown in FIG. 8A, the horizontal axis (X-axis) indicates the movement distance, and the arrow direction indicates the movement in the movement direction A1. The vertical axis (Y-axis) indicates the depth position, and the arrow direction indicates the deep side. In the figure shown in FIG. 8A, the signal intensity for each line shown in FIG. 4 is shown in the vertical axis direction with black-and-white gradation, 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, gradation processing is performed so that the stronger the received signal is, the whiter it is, and the smaller the received signal is, the blacker it is.

Therefore, the shade shown in FIG. 8A indicates the signal strength. Further, one line of intensity signals with 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. 8 (b), the shade is increased by adjusting the gain. Further, since the gain value is higher in the deep part, the value of the RF data becomes larger. Therefore, the image data at the bottom becomes whitish as a whole. The whitish part is shown surrounded by a dotted line.

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

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 strength at the depth n (mm) (Y coordinate value Y _{n ) of the mth (X coordinate value X m) line, 1 to m.} -Calculate the average value of the signal strength of the line depth Y _n (mm) up to the 1st (X coordinate value X _{1 to X m-1} )), and use the average value as the m-th line depth n. Subtract from the signal strength of (mm). By performing this calculation for all depth positions of all lines, changes in the RF data signal can be clarified as shown in FIG. 9 (b).

(Moving average processing unit)
The moving average processing unit 33 performs a moving average process for each line of the RF data that has undergone the difference process. In the present embodiment, for example, the moving average processing can be performed with an 8-point average.
10 (a) is a diagram showing image data subjected to moving average processing, and FIG. 10 (b) is a diagram showing signal strength of RF data of line L1 of FIG. 10 (a). The horizontal axis of FIG. 10B indicates the depth position, and is deepened along the arrow direction. The vertical axis of FIG. 10B shows the signal strength, and the signal strength increases along the direction of the arrow.

In the present embodiment, the stronger the signal strength, the whiter the gradation, and the weaker the signal strength, the blacker the gradation. Further, in the present embodiment, a downward peak, that is, a position where the black color is the darkest, and an upward peak, that is, a position where the white color is the lightest are detected. For example, the position of the downward peak indicates the position of the reinforcing bar or the like in the concrete, and the position of the upward peak indicates the position of the cavity or the resin in the concrete.

Since the principle of detecting the downward peak and the upward peak is the same, the following description specifically describes the detection of the downward peak (the position where the black color is the darkest).
The black portion on L1 in FIG. 10A is shown by P1 to P5. These P1 to P5 are also shown in FIG. 10 (b). Also, in FIG. 10B, one of the upward peaks between P2 and P3 is shown as P10.

(First derivative processing unit 34)
The first derivative processing unit 34 performs the first derivative process on the data subjected to the difference process in order to detect the downward peak. The first derivative processing unit 34 calculates the difference from the signal strength at a predetermined depth position to the signal strength at the next depth position.
FIG. 11 is an enlarged view between P10 and P3 of FIG. 10 (b). FIG. 12 is a diagram showing Table 150 as a result of the signal strength and the first derivative processing of the graph of FIG.

The sequence number is shown in the leftmost column of 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. In the third column from the left, the difference calculated by the first derivative processing unit 34 is shown.
The difference of the sequence number n is a value obtained by subtracting the signal strength of the sequence number n from the signal strength of the sequence number n + 1. For example, the difference of 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 first derivative processing unit 34 performs the first derivative process on all the data in one line.
(Peak detection unit 35)
The peak detection unit 35 detects the peak of the RF data of one line after the first derivative processing is performed. For example, when detecting a downward peak (black peak), the peak detection unit 35 detects a point at which the change after the first derivative processing changes from a negative change to a positive change as a peak. Specifically, as shown in Table 150 of FIG. 12, the change in the sequence number 33 is a negative (−) change, and the change in the sequence number 34 is a positive (+) change. , The peak detection unit 35 detects that the signal strength is a downward peak at the depth position of the sequence number 34.

When detecting an upward peak (the position where the white color is the lightest), the peak detection unit 35 determines the point at which the change after the first derivative processing changes from a positive change to a negative change. Detect as a peak. For example, in Table 150 of FIG. 12, it is detected that the signal strength peaks upward at the depth position of sequence number 5.
(Buried 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. , Have. The grouping unit 51 detects as a group continuous peaks with respect to the moving distance (X-axis coordinates) among the plurality of peaks detected by the peak detecting unit 35. The shape determination unit 52 determines the presence or absence of a buried object based on whether or not the group has a mountain shape, and when it is determined that the buried object exists, the apex (an example of the peak at the depth position) in the group is determined. Detect and use as the position of the buried object.

(Grouping unit 51)
The grouping unit 51 groups the peak detection results of the peak detection unit 35. The grouping unit 51 confirms the presence / absence of a peak detection result in order from the past line. Using 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. 14 (a) to 14 (d) are diagrams for explaining the processing by the grouping unit 51.

The grouping unit 51 determines whether or not the peak of the next line exists within 5 pixels in the moving direction B and within 5 pixels above and below, starting from the position QS of the peak found first (indicated by ● in FIG. 13). Confirm. The line where the peak position Q is found is used as the current line.
FIG. 14A shows a state in which 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 moving direction A1 of the peak position QS of the current line and within the upper 5 pixels. In FIG. 14B, the position of the peak rises (moves to the shallow side) in the moving direction. FIG. 14 (c) shows a case where the peak position Q2 of the next line exists within 5 pxel of the moving direction A1 of the peak position QS of the current line and within 5 pixels of the lower side. In FIG. 14 (c), the position of the peak is descending (moving to the deeper side) in the moving direction.

Subsequently, with the line where the peak position Q2 exists as the current line, it is confirmed whether or not the peak of the next line exists within 5 pxel of the moving direction A1 of the peak position Q2 and within 5 pixels above and below. In this way, each time the RF data of the line is received, the current line is shifted in the moving direction and the continuity of the peak is confirmed.
Then, as shown in FIG. 14D, when the peak of the next line does not exist within 5pixel of the moving direction B of the peak position of the current line and within 5pixel of the upper and lower peaks, the peak position Qe Is the end point of the group (indicated by ■ in FIG. 13).

As described above, the grouping unit 51 groups the 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.
Similarly, grouping at the position of the upward peak (the position where the white color is the lightest) is also performed.
(Shape determination unit 52)
The shape determination unit 52 determines whether or not 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 the 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 movement direction A1 continuously rises by 5pixel or more and upward (shallow direction), and the second condition is that the movement direction A1 continuously rises 5pixel. As described above, it is descending in the downward direction (deep direction), and the third condition is that the difference in the depth direction is 10 pxel or more.
When these three conditions are satisfied, the shape determination unit 52 determines that the shape of the group is a mountain shape, and determines that a buried 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 buried object exists.
In addition, the shape determination unit 52 also detects an upward peak at the position of the group when determining 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 at which the change in position changes from an increase to a 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 (-), the 8th position is the apex as shown in FIG. Is determined to be.
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 position where the group is the shallowest as the position of the apex. do.

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

Specifically, the buried object positioning unit 53 determines whether or not the adjacent peaks are within ± 10 pixels on the X-axis and within ± 40 pixels on the Y-axis. The buried object positioning unit 53 determines whether or not there is another peak within ± 10 pixels on the X-axis and within ± 40 pixels on the Y-axis from the predetermined peak, and if another peak exists, the other peak is determined. It is determined whether or not another peak exists within ± 10 pixels on the X-axis and within ± 40 pixels on the Y-axis from the peak of, and the peaks in the entire range from which RF data has been acquired are determined.

As a result, as shown in Table 1 of FIG. 17, the buried object positioning unit 53 detects five patterns of peaks.
Pattern A1 consists of the vertices of the white (upward peak position) group, the black (downward peak position) group, and the white (upward peak position) adjacent to each other in order from the shallowest side. Shows the pattern in which the vertices of the group are detected.

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

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

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

Here, the difference between the X-axis values of the vertices P1 and P2 is within 10pixel, the difference between the X-axis values of the vertices p2 and P3 is within 10pixel, and further, the difference between the Y-axis values of the vertices P1 and the vertex P2 is within 10pixel. The difference is within 40pixel and the difference between the values on the Y-axis of the vertices P2 and P3 is within 40pixel.
In the case of the pattern A1, the buried object positioning unit 53 has three adjacent vertices P1 (black vertices), P2 (white vertices), and P3 (black vertices) as shown in FIG. 18 (b). The shallowest vertex P1 is determined as the position Pd of the buried object.

That is, the buried object position determination unit 53 determines whether the vertices P1, the apex P2, and the apex P3 are provided in the vicinity thereof, and if they are provided in the vicinity, the apex detected from one buried object. It is judged that the buried object is placed at the shallowest position.
Also in the case of the pattern A1, the buried object position determination unit 53 determines the shallowest apex as the buried object position Pd.

Further, the positions of the detected vertices P2 and P3 are only stored in the RF data management unit 62 and are not displayed, and only the vertices P1 determined to be the position Pd of the buried object are as shown in FIG. 18 (b). , Displayed on the display unit 8 by the display control unit 66.
FIG. 19 (a) is a diagram showing image data in which two adjacent vertices are detected, and FIG. 19 (b) is a diagram showing an example of the determined position of the buried object.

In FIG. 19A, images of white (upward peak position) group G2 and black (downward peak position) group G3 are shown in order from the shallowest side. The vertices P2 of the group G2 and the vertices P3 of the group G3 are detected and are indicated by x.
The difference between the X-axis values of the vertices P2 and P3 is within 10 pixels, and the difference between the Y-axis values of the vertices P2 and the vertex P3 is within 40 pixels.

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

Also in the case of the pattern B2, the buried object position determination unit 53 determines the position of the apex in the shallow direction as the position of the buried object.
Further, FIG. 20A is a diagram showing an example in which adjacent vertices are not detected and one vertex 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. 20 (a), the vertices P2 of the white (upward peak position) group G2 are detected in order from the shallowest one, and are indicated by x marks.

There are no other peaks within ± 10pixel on the X-axis and within ± 40pixel on the Y-axis from vertex P2. In the case of such a pattern C, the buried object position determining unit 53 does not determine the position of the buried object as shown in FIG. 20 (b).
(Buried object data integration unit 54)
As described with reference to FIGS. 6 (a) to 6 (c), the buried object data integrating unit 54 updates the position of the detected buried object when the same route is moved a plurality of times.

The buried object data integration unit 54 changes the buried object data based on the buried object data transition table shown in FIG. 22 (a) to 22 (c) are diagrams for explaining the transition of the buried object data.
FIG. 22A is a diagram showing a scanning direction, a vertex detection result, and a buried object position determination result when the buried object detecting device 1 is scanned for the first time from the point E to the point F. FIG. 22B is a diagram showing a scanning direction, a vertex detection result, and a buried object position determination result when the buried object detecting device 1 is scanned for the second time from the point E to the point F. FIG. 22 (c) is a diagram showing a scanning direction, a vertex detection result, and a buried object position determination result when the buried object detecting device 1 is scanned for the third time from the point E to the point F.

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

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

At this time, since the result of the second time (before change) is pattern B1 and the result of the second time (after change) is pattern A2 in the buried object data integration unit 54, A2 is adopted according to the transition table of FIG. Then, the position Pd of the buried object is determined to be the position of the apex P1.
(Judgment result registration unit 25)
The determination result registration unit 25 registers the result (group, peak position, determined position of the buried object, etc.) determined by the buried object determination unit 24 in the RF data management unit 62.

(Scanning error determination unit 65)
The scanning error determination unit 65 determines whether or not the scanning is performed so as to reciprocate on the same route.
Here, the problem that occurs when the vehicle is not reciprocating on the same route (also referred to as being misaligned) will be described in detail. FIG. 23 is a diagram for explaining a state in which the buried object detection device does not reciprocate on the same route.

For example, when the user moves the buried object detection device 1 from the position J to the folded-back origin O so as to cross the buried object 101 (for example, a reinforcing bar) and scans the buried object, the buried object 101 is buried at the position K. It can be detected that it is present. The image data at this time is shown in FIG. 23 (b). The position K is a position separated from the folding origin O by a distance L.
It is assumed that when the buried object detecting device 1 is moved to the folded-back origin O and then folded back at the folded-back origin O and the buried object detecting device 1 is moved toward the position J, the path deviates and heads toward the position R. In this case, the buried 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. 23 (c). FIG. 23 (c) shows the data at the time of the folded movement of the image data from the folded origin O to the position K, and the remaining data shows the data of FIG. 23 (b), and the previous position J is shown. The position P1 (Pd) of the buried object 101 when moving from the folded object to the origin O is shown.

In this way, when the buried object detection device deviates from the same path during scanning, the previous buried object detection position P1 may be displayed in a place where the buried object does not exist.
Therefore, the buried object detection device 1 of the present embodiment determines the scanning error, and when the scanning error is determined, the previously detected detection position P1 of the buried object is erased. This makes it possible to display the buried object at the position where it should be displayed on the deviated 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 a buried object position erasing unit 75.
The range setting unit 71 has a predetermined range S (an example of the first range) in the RF data when scanning along a predetermined path, and a range T (second range) in the RF data when the range is subsequently moved back and forth. Example) is set. The range T and the range S are the corresponding ranges.

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

The range T corresponding to the range S is set within the range of the distance L from the folding origin O to the position K, and the distance L1 from the position P moved toward the position R direction 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 at the position where L1 is moved from the coordinate value X1 toward the folded origin O is X2. As described above, the range T also indicates the range from the X coordinate values X1 to X2, and is the 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 where the change in signal strength is large, so that it becomes easy to determine whether or not the route is deviated. ..
As shown in FIGS. 25 (a) and 25 (b), the difference calculation unit 72 compares the signal strengths at the same distance from the folding origin O and at the same depth position. As shown in FIGS. 25 (a) and 25 (b), 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 the point nt at the depth position (an example of the second position). For example, the difference calculation unit 72 is the difference between the signal strength fs1 of the point s1 closest to the X coordinate value X1 and the shallowest point t1 in the range T and the signal strength ft1 of the point t1 closest to the X coordinate value X1 in the range T. Absolute value | 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 strength fsn at the point sn in the range S and the signal strength ftn at the point nt in the range T. , Calculate the absolute value of the difference between all the corresponding points.
The counting unit 73 counts the number m of points where 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 misalignment comparison number v, the determination unit 74 finds that the second route taken in FIG. 25 (b) is the first route taken in FIG. 25 (a). It is determined that a scanning error has occurred because the image is deviated from. On the other hand, when the counted number m is less than or equal to the position shift comparison number v, it is determined that no scanning error has occurred because the first and second paths are not deviated.

When the determination unit 74 determines that a scanning error has occurred, the buried object position erasing unit 75 determines the buried object position P1 (Pd) determined by the first scan from the RF data management unit 62. It is deleted, and 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 from the display unit 8, and the position Q detected by scanning from the folding origin O to the position R is deleted. (See FIG. 23A), the position P1'of the buried object is displayed.

Generally, when the buried object 101 is detected by using the buried object detecting device 1, the RF data is averaged by the averaging processing unit 63 by repeating the same route a plurality of times and reciprocating, and the buried object data is integrated. By updating the position of the buried object in the section 54, the certainty of the position of the buried object is improved. The buried object detection device 1 of the present embodiment deletes the position of the buried object acquired by the scanning so far when the path is deviated during this repetition. This prevents the buried object from appearing in its previous position if it goes off the road.

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

On the other hand, as shown in FIGS. 26A and 26B, for example, when determining the deviation of the route from the first movement in the arrow A1 direction, when determining the scanning error of the movement in the arrow A1 direction, It is set as a range for comparing the range S of the distance L1 from the position K where the buried object is detected to the side opposite to the folding origin O. Further, as shown in FIG. 26 (b), from the position P of the distance L (distance from the folding origin O to the position K) from the folding origin O at the time of movement for determining the scanning error to the side opposite to the folding origin O. The range R of the distance L1 is set as the range corresponding to the range S. In this way, it is set as the range S for comparing the range on the side opposite to the moving direction when determining the scanning error of the position of the buried object.

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 group and the peak position. For example, like the image data on the right side of FIG. 22 (c), the image data obtained by black-and-white gradation of the 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 buried object detection device 1 according to the embodiment of the present invention will be described.
FIG. 27 is a flow chart showing the processing of the buried object detection device 1.
(Overview of overall processing)
In step S11, the buried object detection device 1 is first initialized. In the initialization process, clearing of each data is executed.

Next, when the user moves the buried object detection device 1, RF data is acquired in step S12 using the input from the encoder 7 as a trigger.
Next, in step S13, the averaging process 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 scanning error determination processing. The scanning error determination process is not determined at the time of the first movement. Further, it can be determined that the encoder is continuously and repeatedly moving, for example, by inputting an encoder.

Next, in step S15, the buried object detection unit 64 performs the buried object detection process.
Next, steps S12 to S15 will be described in detail.
(Data acquisition process)
FIG. 28 is a flow chart showing the data acquisition process in step S12.

When the data acquisition process is started, when the data is input from the encoder 7 in step S1, the impulse output control is started in step S2, and a fixed period (for example, for example) from the transmitting antenna 11 based on the pulse from the pulse generating unit 13 is started. An electromagnetic pulse is output at 1 MHz).
Next, in step S3, the delay unit 14 sets the delay time in the delay IC. For example, the Delay time can be set from 0 to 5120 psec in units of 10 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 the maximum (for example, 5120 psec), and if it is not the maximum, 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 buried object detection device 1 is moved in the moving direction A by the operator, there is an input from the encoder 7, control of steps S2 to S7 is performed, and data for the next one line is acquired. It is transmitted to the main control module 6.

Next, in step S7, the receiving unit 61 waits until the impulse control module 5 receives the RF data for one line, 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 flow chart showing the waveform data averaging process.

When the waveform data averaging process is started, in step S171, the averaging process unit 63 detects whether or not one line RF data exists at the same X coordinate value of the scanning X axis.
Then, when the 1-line RF data acquired so far exists in the same X coordinate value, in step S172, the averaging processing unit 63 has 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, assuming that the depth direction is the Y axis and the depth position is the Y coordinate value, the averaging processing unit 63 has the 1-line RF data acquired this time and the 1-line RF data acquired so far. The data for one line is averaged by calculating the average of the signal strengths of the same XY coordinate values.

(Scanning error judgment processing)
Next, the scanning error determination process will be described. FIG. 30 is a flow chart showing a scanning error determination process.
When the scanning error determination process is started, first, in step S181, the range setting unit 71 determines whether or not there is reference data for comparison. Here, the comparison reference data is data acquired by scanning a predetermined path, and is data in which a buried object is detected. That is, it is detected whether or not the scan for acquiring the current RF data is a scan performed after the position of the buried object is detected at least once in order to improve the certainty of the position of the buried object. If the comparison reference data 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 in which the detection position of the buried object exists and the current X-axis coordinate value are within the comparison range. That is, to explain with the example of FIG. 23, in the range setting unit 71, the X coordinate value of the RF data of one line currently acquired in FIG. 23 (c) is in the range of the distance (L-L1) to L from the folding origin O. Determine if it is within.

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 immediately before the present, which is smaller than the X coordinate value of the detection position of the buried object. Judge whether or not.
If it is small, 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 equal to or greater than the X coordinate value of the detected value of the buried object. This indicates that the X coordinate value of the current 1-line RF data is equal to or higher than the detection position X1 of the buried object in the state of scanning in the direction of the arrow A1. That is, in scanning in the direction of arrow A1, it is detected whether or not the detection position X1 of the buried object has been reached.

On the other hand, if it is not small in step S183, in step S185, the range setting unit 71 determines whether or not the current X-axis coordinate value is equal to or less than the buried object X coordinate value. This detects whether or not the X coordinate value of the current 1-line RF data has reached the detection position x1 of the buried 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 or not the detection position x1 of the buried 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 detection position x1 of the buried object, the range setting unit 71 sets the position deviation 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). The range S and the range T can be appropriately changed within a range in which the positional deviation can be determined, and are not particularly limited.

Next, in step S187, the position shift amount acquisition process is performed by the difference calculation unit 72 and the count unit 73.
FIG. 31 is a flow chart showing a misalignment amount acquisition process.
When the misalignment amount acquisition process is started, in step S191, the counting unit 73 clears the comparative surreal number to zero.

Next, in step S192, the difference calculation unit 72 substitutes the position shift search start position into the position shift search counter. For example, the value of the X coordinate value X1 shown in FIGS. 25 (a) and 25 (b) is substituted into the position shift 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 has been 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 is acquired. The process is finished.

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 or not there is one line latest data of the position shift search counter position. The difference calculation unit 72 detects, for example, whether or not the latest 1-line RF data exists in the X coordinate value X1.
When the latest 1-line RF data exists, the difference calculation unit 72 sets the number of 1-line counters to zero in step S195.

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

Then, if the absolute value of the difference is not within the position shift comparison value, the count unit 73 increases the value of the comparison surreal number by +1 in step S199. This calculates the absolute value of the difference between the intensity signal at point s1 and the intensity signal at point t1 shown in FIGS. 25 (a) and 25 (b), and whether the absolute value of the difference is within the position shift comparison value. It is to judge whether or not.
Next, in step S200, the difference calculation unit 72 increases the 1-line counter value by +1. The control proceeds from step S200 to step S196, and when the number of 1-line counters is smaller than the 1-line size, in step S197, the difference calculation unit 72 uses the current 1-line RF data position shift 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 position shift search counter (X1) and the same 1-line counter (1) of the comparison reference data is calculated. Here, when the 1-line counter is 1, the signal strength at a point deeper than the previous time is compared. That is, the difference calculation unit 72 calculates the absolute value of the difference between the intensity signal at point s2 and the intensity signal at point t2 shown in FIGS. 25 (a) and 25 (b), and the absolute value of the difference is compared with the positional deviation. Determine if 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 is displaced. Increases the search count value by +1. As a result, the absolute value of the difference is calculated and the position shift comparison value (first threshold value) is compared with the data for one line in the X coordinate value next to the X coordinate value X1. As a result, the difference in signal strength at all points in the range S and the range T is calculated, and the comparison surreal number in which the absolute value of the difference exceeds the positional deviation comparison value is counted. In step S194, the control proceeds to step S98 even when the latest RF data of one line does not exist at the position of the position shift search counter.

Next, in step S188 of FIG. 30, the determination unit 74 determines whether or not the comparative surreal number is larger than the positional deviation comparison number (an example of the second threshold value), and if it is large, the positional deviation occurs. It is determined that there is.
If it is determined that the misalignment has occurred, the misalignment processing is performed in step S189.

FIG. 32 is a flow chart showing the processing at the time of misalignment.
When the misalignment processing is started, in step S110, the buried object position erasing unit 75 erases the positions of the buried objects detected so far.
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 flow chart showing a buried object detection process.
When the buried object detection process is lent, in step S201, the pre-process before determining the buried object is performed by the pre-processing unit 23.
Next, in step S202, the buried object determination process is performed by the buried object determination unit 24.

Next, in step S203, the result (position of the buried object) determined by the buried 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 flow chart showing the pretreatment.

First, in step S21, the gain adjusting unit 31 adjusts the gain of one line of RF data.
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 been differentially processed. For example, a moving average process can be performed using an 8-point average.

Next, in step S24, the first derivative processing unit 34 performs the first derivative process on the difference result processed by the moving average, and the difference between the adjacent data in the depth direction is positive (increase) or negative (decrease). Judgment is made.
Finally, in step S25, the peak detection unit 35 detects the peak of the signal strength using the result of the first derivative processing.

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

Then, after the gain adjusting unit 31 processes the signal strength data of sequence number 1 in step S32, the control proceeds to step S33.
In step S33, it is determined 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 S31, the sequence number is incremented by one, and the received data of the sequence number 2 is received. Be selected. Then, the process of step S32 is performed on the data of the sequence number 2.

In this way, it is repeated until the processing of step S32 is performed for all the data for one line.
In step S32, a predetermined magnification is applied to the signal strength data of each sequence number.
For example, the sequence No. with the shortest delay time of one line of RF data. When the data of 1 (which can be said to be the data at the shallowest position) is multiplied by a predetermined magnification, the sequence No. 1 is obtained. Next to No. 1, the sequence No. with the shortest delay time. A predetermined magnification is applied to the data of 2, and a predetermined magnification is applied in the order of sequence numbers until the sequence No. becomes maximum. Specifically, the magnification is increased in the depth direction, the magnification is set to 1 for the data of 1 to 25 pixel from the shallow side, and the magnification is set to 2 for the data of 26 to 50 pixel. The magnification can be set to 3 times for the data of 51 to 75pixel, the magnification can be increased in order, and the magnification can be set to 21 times for the data of 500 to 511pixel.

By this gain adjustment processing, light and dark can be clarified as shown in the image data shown in FIG. 8 (b).
(Difference processing)
Next, the difference processing in step S22 of FIG. 34 will be described. FIG. 36 is a flow chart showing the difference processing.

When the difference processing is disclosed, in step S41, the difference processing unit 32 selects the received data of the sequence number 1 from the gain-adjusted RF data.
Then, after the difference processing unit 32 processes the data of sequence number 1 in steps S42 and S43, the control proceeds to step S44.
In step S44, it is determined 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, the sequence number is incremented by one, and the received data of the sequence number 2 is received. Be selected. Then, the processes of steps S42 and S43 are performed on the data of the sequence number 2.

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

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

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

Next, in step S52, the first derivative processing unit 34 performs the first derivative process of the difference result. Here, the first-order 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, and 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 first derivative processing is performed on all the data for one line.
That is, when performing the first derivative processing of the sequence number n, the first derivative process is performed on the data of the sequence number n by subtracting the data of the difference result of the sequence number n from the data of the difference result of the sequence number n + 1. It can be carried out.

As a result, the difference in the third column from the left in Table 150 of FIG. 12 is calculated.
(Peak detection processing)
Next, the peak detection process in step S25 of FIG. 34 will be described. FIG. 38 is a flow chart showing a peak detection process.
When the peak detection process is started, in step S71, the peak detection unit 35 selects the sequence number 1 on which the first derivative processing has been performed.

Then, the peak detection unit 35 controls 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, and if the sequence number is not the maximum value, the control returns to step S71, the sequence number is incremented by one, and the received data of the sequence number 2 is received. Be selected. Then, the processes of steps S72 and S73 are performed on the data of the sequence number 2.

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

When the state of the previous sequence number n-1 is negative (−) and the state of the current sequence number n is positive (+), the peak detection unit 35 stores the nth coordinate in step S73. do. The coordinates can be indicated by, for example, a moving distance (which can be said to be a line number) and a depth position in pixels.
Thereby, as described above, for example, the sequence number 34 in Table 150 of FIG. 12 can be detected as a peak. This peak is a black (downward) peak.

On the other hand, when detecting a white (upward) peak, when the state after the previous first derivative is "+" and this time is "-", the white peak is stored by memorizing the coordinates of this time. Can be detected. As a result, the sequence number 5 in Table 150 of FIG. 12 can be detected as an upward peak.
(Buried object judgment process)
Next, the buried object determination process shown in step S122 of FIG. 33 will be described. FIG. 39 is a flow chart showing a buried object determination process.

When the buried object determination process is started, first, in step S81, the grouping unit 51 performs the grouping process of the peak detection result performed by the pretreatment unit 23.
Next, in step S82, the shape determination unit 52 performs vertex detection processing.
Next, in step S83, the buried object acquisition process is performed by the buried object position determining unit 53 or the buried object data integrating unit 54.

(Grouping process 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 flow chart 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 the data acquired in the past are targeted, and in step S92, the grouping unit 51 selects the old data in the past as the processing target. Then, in step S103, the grouping unit 51 determines whether all the data acquired in the past up to the line acquired this time has been processed, and if not, the control returns to step S92, and the next step is Old data is processed. In this way, for example, the processes of steps S93 to S102 are performed in order from the sequence number 1 of the oldest line.

In step S93, the grouping unit 51 determines whether or not the state has not been detected. Since the initial state is "not detected", the control proceeds to step S94.
In step S94, the grouping unit 51 determines whether or not there is a position where a peak is detected within a predetermined range. If no peak is detected in the predetermined range, the control proceeds to step S103. The predetermined range can be set as appropriate, for example, it may be set for one line, or it may be set for the sequence number of one line.

In this way, in step S94, it is determined whether or not there is a position where peaks are detected in order from the oldest data, and when there is a position where peaks are detected, in step S95, the grouping unit 51 determines. The detection status 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 in pixels, and can be indicated by, for example, a moving distance (which can be said to be a line number) and a depth position. This point corresponds to the starting point (●) in FIG.

Next, the next data is processed through steps S103 and S92.
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 position where a peak is detected within a predetermined range from the position stored in step S96. Within this predetermined range, for example, the movement direction described with reference to FIGS. 14 (a) to 14 (d) is within 5 pixels, and the range can be set within 5 pixels above and below. When the position where the peak is detected exists within a predetermined range, in step S98, the grouping unit 51 assumes that there is a continuous position and stores the position.

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, a positive (+) is stored as the depth position is rising. Further, 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, the next data is processed through steps S97 and S92.
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 point where a peak is detected within a predetermined range from the point stored in step S98 last time, and if so, 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, continuous points are sequentially grouped, and the change to the next point is also memorized as rising or falling.

Then, if the peak is not detected within the predetermined range in step S97, the control proceeds to step S101.
In step S101, the grouping unit 51 determines that there are no continuous points, and saves 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 lines acquired in the past, the processing ends.
(Vertex detection process)
The vertex detection process in step S83 of FIG. 39 will be described. FIG. 41 is a flow chart showing the vertex detection process.

The vertex detection process is performed for all the data as a result of grouping.
When the vertex detection process is started, in step S121, the shape determination unit 52 selects data in order from the start point side of the grouped data. For example, in step S121, the shape determination unit 52 processes the data of the change from the first to the second shown in FIGS. 15 and 16.

In step S122, the shape determination unit 52 reads out 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 the data as a result of grouping, and if not, the control returns to step S121, and the next step is The data (change from second to third) is selected for processing.

Then, in step S122, the shape determination unit 52 reads out 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 grouping post-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 steps 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 count is continuously increased 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 is 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 or not the − (minus) count is 5 or more. Here, when the count is 5 or more, it means that the condition 2 that the count is continuously descending in the Y-axis direction by 5 pixels or more is satisfied. In the case of the change from the 8th to the 9th, since the − count is +1 the control proceeds to step S138, and the change from the 9th to the 10th is selected as the processing target via step S121.

In this way, when the change is 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, so that 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 start point and the Y coordinate of the vertex. In the data of 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 10pixel or more is satisfied.
When the calculated difference is 10 or more, in step S135, the shape determination unit 52 determines that the loop and the loop have a mountain shape, and determines that a buried object exists.

On the other hand, if 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 flow chart showing a buried object acquisition process.
When the buried object acquisition process is started, in step S141, the buried object positioning unit 53 detects a pattern of a combination of vertices (see FIG. 17) detected by the above-mentioned vertex detection process.

Next, in step S142, the buried object position determining 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 buried object acquisition process is terminated without setting the position of the buried 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 performs 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 processing)
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 ● 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. 18 (b)).
In the case of the example shown in FIG. 15, the display control unit 26 marks the position of the eighth data, which is the apex, with a ● mark, and causes the display unit 8 to display the image.

[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, as a control method of the buried object detection device 1 and the main control module 6 (an example of a data processing device), an example of carrying out according to the flowcharts shown in FIGS. 27 to 42 has been described. Not limited.

For example, the present invention may be realized as a program for causing a computer to execute the buried object detecting device 1 and the buried object detecting method implemented according to the flowcharts shown in FIGS. 27 to 42.
Further, one usage mode of the program may be a mode in which the program is recorded on a recording medium such as a ROM that can be read by a computer and operates in cooperation with the computer.

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

(B)
In the above embodiment, the reinforcing bar has been described as an example of the buried object, but the reinforcing bar may not be 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 object is not limited to concrete.

(C)
In the above 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 embodiment, in step S88, it is determined whether or not the comparative surreal number is larger than the positional deviation comparison number as the lower limit value, but the upper limit value may also be set.

(E)
In the above embodiment, the buried object position erasing unit 75 erases the previously acquired buried object data (pattern and the determined position of the buried object), but instead of erasing or erasing, a scanning error due to misalignment occurs. You may notify that it has occurred. For example, as shown in FIG. 43, even if the scanning error determination unit 65'is further provided with a notification unit 76 and detects a scanning error, the user is notified of the occurrence of the scanning error by a warning sound or a display or the like. good.

(F)
In the above embodiment, the main control module 6 is provided in the main body 2 of the buried 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 a tablet or the like. Communication may be performed wirelessly or by wire between the main body 2 and the tablet.

(G)
In the above embodiment, the range S to be compared when determining the scanning error is set to include the detection position Pd of the buried 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 signal strength is large. ..

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

1: Buried object detection device 2: Main body part 3: Handle 4: Wheel 5: Impulse control module 6: Main control module 7: Encoder 8: Display unit 10: Control unit 11: Transmission antenna 12: Reception antenna 13: Pulse generation unit 14: Delay unit 15: Gate unit 23: Pretreatment unit 24: Buried object determination unit (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: Primary derivative processing unit 35: Peak detection unit (example of signal intensity peak detection unit)
51: Grouping unit 52: Shape determination unit (an example of depth position peak detection unit)
53: Buried object position determination unit 54: Buried object data integration unit 61: Reception unit 62: RF data management unit 63: Average processing unit 64: Buried object detection unit 65: Scanning error determination unit 65': Scanning error determination unit 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 Object 101c: Buried object 101d: Buried object

Claims (23)

It is a buried object detection device that detects buried objects in the object by using data on reflected waves of electromagnetic waves radiated toward the object while moving on the surface of the object.
A receiver that receives data related to reflected waves at each timing associated with movement,
A buried object detection unit that detects the buried object using data on the reflected wave when reciprocating on the same path on the surface of the object.
The data relating to the reflected wave in a predetermined first range in the first movement when the buried object is detected, and the second corresponding to the first range in the second movement after the first movement. The data relating to the reflected wave in the range is compared with the scanning error determination unit for determining whether or not the data is scanned so as to reciprocate on the same route.
Buried object detector. The scanning error determination unit is
When it is determined that the vehicle is not reciprocating on the same route, the buried object position erasing unit that erases the detection position of the buried object detected by the movement of the route before the movement of the route at the time of determination. The buried object detection device according to claim 1. The scanning error determination unit is
The buried object detection device according to claim 1, further comprising a notification unit for notifying the user that a scanning error has occurred when it is determined that the vehicle is not reciprocating on the same route. The first range is a range including the 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 buried object detection device according to claim 1 or 4, wherein the first range and the second range are the same distance from the turning position in the reciprocating motion. The first range includes the detection position and is a range in front of the detection position in the second movement.
The buried object detection device according to claim 4. The buried object detection unit is
A signal strength peak detection unit that detects the peak of the signal strength in the depth direction of the object at each of the timings,
It has a buried object position detecting unit that detects the position of the buried object based on the 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. And determine if it is being scanned to reciprocate the same path,
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 identified by the timing and the depth position.
The scanning error determination unit is
A difference calculation unit that calculates the difference between the signal strength of each of the first positions and the signal strength of the second position corresponding to each of the first positions.
A counting unit that counts the number of differences above the first threshold value,
A determination unit for determining whether or not the count number is equal to or greater than the second threshold value and determining a scanning error when the count number is equal to or greater than the second threshold value is provided.
The buried object detection device according to claim 8. The buried object detection unit is
Further provided with a difference processing unit for detecting the difference in the change in the signal strength at the predetermined depth position from the signal strength at the previous depth position in the depth direction or the surface direction vice versa.
The buried object detection device according to claim 7. The signal strength peak detection unit is
At least one of the depth position where the difference changes from decrease to increase and the depth position where the difference changes from increase to decrease is detected as the peak of the signal strength.
The buried object detection device according to claim 10. The buried object detection unit is
Of the depth positions at the signal strength peaks detected at each of the timings, the depth positions at a plurality of the signal strength peaks that are continuous within a predetermined interval in the moving direction are grouped together. Grouping part and
It has a depth position peak detection unit that detects a peak at the depth position of the group in a plane in the movement direction and the depth direction.
The buried object detection device according to claim 11. The buried object detection unit is
The buried object detection device according to claim 12, further comprising a buried object positioning unit for setting the position of the buried object based on the detected peak of the depth position. The buried object positioning unit is in the group of the peak of the depth position in the group of the peak of the signal intensity changing from decrease to increase and the peak of the signal intensity changing from increase to decrease in a predetermined range. If one of the peaks at the depth position is detected and there is no peak at the other 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-fixing unit
The peak of the signal strength that changes from decrease to increase at the depth position in the group and the peak of the signal intensity that changes from increase to decrease at the depth position in the group are within a predetermined range. If they are 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-fixing unit
The peak of the signal intensity changing from decrease to increase has three peaks at the depth position in the group, and the peak of the signal intensity changing from increase to decrease has three peaks at the depth position in the group alternately. When they are adjacent to each other within a predetermined range, the position of the shallowest peak is set at the position of the buried object.
The buried object detection device according to claim 13. The buried object position-fixing unit
In the reciprocating motion, the position of the buried object when the number of peaks at the adjacent depth positions is large is adopted.
The buried object detection device according to claim 13. The depth position peak detection unit is
If the group has a predetermined shape in a plane in the moving direction and the depth direction, it is determined that the buried object exists, and if it does not have 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 is
During the reciprocating motion, the average of the signal strength in the depth direction of the object at each said timing is averaged with the signal strength in the depth direction of the object at each of the previously received timings. It also has a chemical processing unit.
The buried object detection device according to claim 1. Wherein the reciprocating, each mobile further comprising a display unit that performs display plane smell in the depth direction of the object and the moving direction Te shows the signal strength,
When the buried object is detected, the display unit indicates the detection position of the buried object together with the display.
The buried object detection device according to claim 1. When it is determined that the display unit does not reciprocate on the same route, the display unit erases the detection position of the buried object.
The buried object detection device according to claim 20. It is a buried object detection method for detecting an embedded object in the object by using data on reflected waves of electromagnetic waves radiated toward the object while moving on the surface of the object.
A reception step that receives data related to reflected waves at each timing associated with movement,
A buried object detection step for detecting the buried object using data on the reflected wave when reciprocating on the same path on the surface of the object.
The data regarding the reflected wave in the predetermined first range in the first movement when the buried object is detected, and the second range corresponding to the first range in the second movement after the first movement. The data relating to the reflected wave in the range is compared with a scanning error determination step for determining whether or not the data is scanned so as to reciprocate on the same route.
Buried object detection method. When it is determined that the vehicle is not reciprocating on the same route, the buried object position erasing step for erasing the detection position of the buried object detected by the movement of the route prior to the movement of the route at the time of determination. The buried object detection method according to claim 22, further comprising.

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