JP2020041986A - Data processing device and buried material detection device - Google Patents

Abstract

To provide a data processing device that can remove a noise component even when there is a change in material around buried materials and can detect the buried materials in real time.SOLUTION: In a main control module 6, a peak detection unit 36 detects peaks of signal intensity in a depth direction of an object at respective timings. A grouping unit 51 takes, of depth positions at the peaks of signal intensity detected at the respective timings, depth positions at a plurality of peaks of signal intensity continuing within a predetermined interval in a movement direction A, as one group. A chattering removing unit 52 performs removal of noise from the group on the basis of a change in depth positions at the plurality of peaks in the group. A shape determination unit 53 and a signal intensity determination unit 54 perform detection of the presence or absence of buried materials on the basis of the group from which noise is removed.SELECTED DRAWING: Figure 5

Description

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

As a device for searching for a buried object in concrete, a wall scanner that detects a buried object from reflected waves of electromagnetic waves radiated toward the concrete while moving the surface of the concrete is used (for example, see Patent Document 1). .
In the conventional wall scanner, a noise component removal method using frequency analysis by Fourier transform or a filtering process of extracting a striped noise component in each axis direction and removing it from data is used.

Japanese Patent No. 2893010

However, in the filtering processing using the above-described frequency analysis, it becomes difficult to remove noise components due to a change in the material around the buried object (for example, a difference in the material of a concrete wall or the like), and the processing speed is increased, and the buried object is removed in real time. Could not be detected.
An object of the present invention is to provide a data processing device and a buried object detection device capable of removing a noise component even when there is a change in material around the buried object and capable of detecting the buried object in real time. That is.

  A data processing device according to a first invention is a data processing device for detecting a buried object in an object using data on a reflected wave of an electromagnetic wave radiated toward the object while moving on the surface of the object. There is provided a receiving unit, a signal strength peak detecting unit, a grouping unit, a noise removing unit, and an embedded object detecting unit. The receiving unit receives data on the reflected wave measured at each timing associated with the movement. The signal strength peak detector detects a peak of the signal strength in the depth direction of the object at each timing. The grouping unit sets the depth positions at a plurality of signal intensity peaks that are continuous within a predetermined interval in the moving direction among the depth positions at the signal intensity peaks detected at each timing as one group. . The noise removing unit removes noise from the group based on a change in the depth position of the plurality of peaks in the group. The buried object detection unit detects the presence or absence of a buried object based on the group from which noise has been removed.

As described above, since the noise is removed based on the change in the depth position of the peak without using the frequency conversion or the like, even if there is a change in the material around the embedded object, the processing speed is high and the embedded object is detected in real time. be able to.
In addition, by removing the noise, the presence or absence of the buried object can be more accurately detected.

The data processing device according to a second invention is the data processing device according to the first invention, wherein the grouping unit is configured to determine, in the moving direction, a timing of a peak depth position at a predetermined timing before the predetermined timing. It is determined whether the position change from the depth position of the peak in the direction is a position change in the depth direction or a position change in the surface direction. The noise removing unit removes noise based on a direction of a position change at a depth position of a predetermined number of adjacent peaks.
Thereby, for example, when noise that suddenly becomes shallow while the depth position is deepening occurs, the noise can be removed.

A data processing device according to a third invention is the data processing device according to the second invention, wherein the noise elimination unit includes a position at a depth position of a predetermined number of adjacent peaks including the depth position of the predetermined peak. If the directions of change coincide, the direction of the matched position change is adopted as the result of the direction of the position change after the noise removal processing at the predetermined depth position, and the position at the depth position of the predetermined number of adjacent peaks is used. If the directions of the change do not match, the result of the direction of the position change after the noise elimination processing at the depth position of the peak before the predetermined peak is expressed as the position change after the noise elimination processing at the predetermined peak depth position. Adopt as a result of the direction.
Thereby, for example, when noise that suddenly becomes shallow while the depth position is deepening occurs, the noise can be removed.

A data processing device according to a fourth invention is the data processing device according to the first invention, wherein the embedded object detection unit has a shape determination unit. The shape determining unit determines that an embedded object exists when the group has a predetermined shape on a plane in the moving direction and the depth direction, and determines that no embedded object exists when the group does not have the predetermined shape.
As described above, when the peak continues continuously in the moving direction and the shape is a predetermined shape, it can be determined that the buried object exists. The predetermined shape is, for example, a mountain shape.

The data processing device according to a fifth invention is the data processing device according to the fourth invention, wherein the predetermined shape is a mountain shape, and the shape determination unit determines a peak of the signal intensity along the moving direction. A first condition that the depth position is continuously shallower than a predetermined amount, a second condition that the depth position of the peak is continuously deeper than a predetermined amount along the moving direction, and a depth condition of the group. When all of the third conditions having a width equal to or larger than the predetermined amount are satisfied, it is determined that the group has a mountain-shaped waveform.
When the three conditions are satisfied in this way, it can be determined that the waveform is a mountain-shaped waveform, and the presence or absence of an embedded object can be determined.

A data processing device according to a sixth invention is the data processing device according to the fifth invention, wherein the embedded object detection unit further includes a signal strength determination unit. When the first condition and the second condition are satisfied but the third condition is not satisfied, the signal strength determination unit determines the presence / absence of a buried object based on the signal strength of each of all peaks in the group.
Depending on the shape of the buried object, the waveform may have a flat mountain shape (the first condition and the second condition are satisfied, but the third condition is not satisfied). Even in such a case, the signal intensity is high. The presence or absence of a buried object can be determined based on

A data processing device according to a seventh invention is the data processing device according to the fifth or sixth invention, wherein the shape determination unit detects a peak at a depth position of the group determined to have a mountain shape. .
Thus, by detecting the peak position of the mountain-shaped waveform, the position of the buried object can be detected.

  An embedded object detection device according to an eighth invention includes the data processing device according to the seventh invention, and a display unit. The display unit can display a mountain-shaped group. On the display unit, a display indicating the peak of the position detected together with the mountain-shaped group is performed.

  In this way, by displaying the detected peak position on the display unit, the user can easily recognize the position of the buried object.

  According to the present invention, it is possible to provide a data processing device and a buried object detection device that can remove a noise component even when there is a change in material around the buried object and can detect the buried object in real time. be able to.

FIG. 1 is a perspective view showing a configuration of an embedded object detection device according to an embodiment of the present invention. FIG. 2 is a block diagram illustrating a configuration of the embedded object detection device in FIG. 1. FIG. 3 is a block diagram showing a configuration of the pulse control module of FIG. 2. FIG. 4 is a view showing data of reflected waves acquired by the MPU in FIG. 3. FIG. 3 is a block diagram illustrating a configuration of a main control module in FIG. 2. 7A is a diagram illustrating image data before performing gain adjustment, and FIG. 7B is a diagram illustrating image data after gain adjustment processing. 5A is a diagram illustrating image data before performing a difference process, and FIG. 5B is a diagram illustrating image data after the difference process. FIG. 9A is a diagram illustrating image data after performing a moving average process, and FIG. 8B is a diagram illustrating a signal intensity of RF data of a line L1 in FIG. FIG. 9 is an enlarged view between P10 and P3 in FIG. The figure for demonstrating the process in the increase / decrease determination part 41. The figure which shows the image data after pre-processing. FIGS. 7A to 7D are views for explaining processing by a grouping unit; FIGS. The figure which shows the position of some grouped peak. No. shown in FIG. 1 to No. The figure which shows the change of the position of the adjacent peak up to 15. The figure which shows the conditions for determining with a mountain shape. The figure which shows the state which scans a plate-shaped wood over a gypsum board. FIG. 17 is a diagram illustrating image data detected by the scan in FIG. 16. FIG. 18 is a diagram schematically illustrating image data as illustrated in FIG. 17. FIG. 3 is a diagram showing image data displayed on a display unit in FIG. 2. FIG. 4 is a flowchart showing processing of the impulse control module. FIG. 4 is a flowchart showing processing of a main control module. FIG. 22 is a flowchart showing the preprocessing of FIG. 21. FIG. 23 is a flowchart showing the gain adjustment processing of FIG. 22. FIG. 23 is a flowchart showing the difference processing of FIG. 22. FIG. 23 is a flowchart showing first-order differentiation processing of the difference result in FIG. 22. FIG. 23 is a flowchart showing the chattering removal processing in FIG. 22. FIG. 23 is a flowchart showing the peak detection processing in FIG. 22. FIG. 22 is a flowchart showing the embedded object determination process of FIG. 21. FIG. 29 is a flowchart showing the grouping process in FIG. 28. FIG. 29 is a flowchart showing the chattering removal processing in FIG. 28. FIG. 29 is a flowchart showing the embedded object determination process of FIG. 28. FIG. 32 is a flowchart showing embedded object determination processing 2 in FIG. 31.

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

  The embedded object detection device 1 of the present embodiment emits 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 embed the object in the concrete 100. The positions of the objects 101a, 101b, 101c, and 101d are detected. The direction of movement is indicated by arrow A. In FIG. 1, the buried objects 101a, 101b, 101c, and 101d are reinforcing bars, and are buried in depth positions of 20 cm, 15 cm, 10 cm, and 5 cm in order from the surface 100a, for example. The depth direction is indicated by arrow B, and the surface direction is indicated by arrow C.

The embedded object detection device 1 includes a main body 2, a handle 3, wheels 4, an impulse control module 5, a main control module 6, an encoder 7, and a display unit 8.
A handle 3 is provided on the upper surface of the main body 2. Four wheels are rotatably attached to a lower portion of the main body 2. When detecting a buried object inside the concrete 100, the worker moves the buried object detection device 1 on the surface 100 a of the concrete 100 while holding the handle 3 and rotating the wheel 4.

The impulse control module 5 controls the timing of emitting an electromagnetic wave toward the concrete 100, the timing of receiving a reflected wave of the emitted electromagnetic wave, and the like.
The encoder 7 is provided on the wheel 4 and transmits a signal for controlling the reception timing of the reflected wave to the impulse control module 5 based on the rotation of the wheel 4.
The main control module 6 receives the data related to the reflected wave received by the impulse control module 5, and detects an embedded object.
The display unit 8 is provided on the upper surface of the main unit 2 and displays an image indicating the positions of the buried objects 101a, 101b, 101c, and 101d.

(1-2. Impulse control module 5)
FIG. 3 is a block diagram showing a configuration of the impulse control module 5.
The impulse control module 5 includes a control unit 10, a transmission antenna 11, a reception antenna 12, a pulse generation unit 13, a delay unit 14, and a gate unit 15.

  The control unit 10 is configured by an MPU (Micro Processing Unit) or the like, and instructs the pulse generation unit 13 to generate a pulse using an encoder input as a trigger. The pulse generator 13 generates a pulse based on a command from the MPU and sends the pulse to the transmitting antenna 11. The transmission antenna 11 radiates an electromagnetic wave at a constant cycle based on a pulse cycle. The timing of the input of the encoder 7 corresponds to an example of the timing.

The receiving antenna 12 receives a reflected wave of the emitted electromagnetic wave. When receiving the pulse from the delay unit 14, the gate unit 15 captures the reflected wave received by the receiving antenna 12 and transmits the reflected wave to the control unit 10. The delay unit 14 transmits a pulse to the gate unit 15 at a predetermined interval, and captures a reflected wave. This predetermined interval has a pitch of 2.5 msec.
Thereby, the impulse control module 5 outputs the electromagnetic wave from the transmitting antenna 11 a plurality of times, with the input from the encoder or 7 as a trigger. Then, the impulse control module 5 can acquire reception data for each distance from the reception antenna 12 by delaying the reception timing 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 gradations of −4096 to +4096 with the axis O as the center, and the direction of the arrow indicates the minus side. The horizontal axis indicates the distance from the receiving antenna 12, and the direction of the arrow (corresponding to the depth direction B) indicates that the distance from the receiving antenna 12 is long. A longer distance corresponds to a greater depth.

Although described in detail later, the waveform W1 shown in FIG. 4 includes a reflected wave reflected by the antenna without being irradiated into the concrete 100 (p1 or the like). The change in the data of the reflected wave from inside the concrete 100 is extracted.
The data shown in FIG. 4 is data from the time when the input of the encoder 7 is received to the time when the input of the encoder 7 is next. By gradually delaying the reception timing, a reflected wave from a position at a long distance from the reception antenna 12 is received. However, if there is an input from the encoder 7, the delay of the reception timing is restored, and the reception timing is reset again. Delay slowly. That is, the reflected wave in the depth direction B at the predetermined measurement position in the movement direction A (the position where the input from the encoder 7 is received) is received. The data of the reflected wave from the input of the encoder 7 shown in FIG. 4 until the input of the next encoder is referred to as data for one line. The control unit 10 transmits RF (Radio Frequency) data for one line to the main control module 6 every time data for one line is accumulated.
Since the embedded object detection device 1 is moved, the measurement position is not exactly the same position, and the depth direction B is not strictly perpendicular to the surface 100a of the concrete 100.

(1-3. Main control module 6)
FIG. 5 is a block diagram showing the configuration of the main control module 6.
The main control module 6 includes a reception unit 21, an RF data management unit 22, a preprocessing unit 23, an embedded object determination unit 24, a determination result registration unit 25, and a display control unit 26.

The receiving unit 21 receives the RF data for one line each time it is transmitted from the impulse control module 5.
The RF data management unit 22 stores the RF data for one line received by the reception unit 21.
The preprocessing unit 23 detects a signal intensity peak for each data of one line.
The buried object determination unit 24 determines the presence or absence of a buried object using the peak of the signal intensity for each line of RF data detected by the preprocessing unit 23. The buried object determining 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 22.
The display control unit 26 controls the display unit 8 to display an image in which signal intensity is gradation-processed by color on a plane in the movement direction A and the depth direction B, and the position of the embedded object 101.

(1-3-1. Preprocessing unit 23)
The pre-processing unit 23 includes a gain adjustment unit 31, a difference processing unit 32, a moving average processing unit 33, a primary differentiation processing unit 34, a chattering removal unit 35, and a peak detection unit 36.

(A. Gain adjustment unit)
The gain adjustment unit 31 performs gain adjustment on the RF data for each line. As the distance from the transmitting antenna 11 and the receiving antenna 12 increases (as the delay time increases), the receiving sensitivity decreases. Therefore, when displaying an image described later, the density of white and black decreases. Therefore, the gain adjusting unit 31 increases the gain value (× 1 to × 20) to be multiplied (amplified) by the signal intensity as the depth position is deeper.

  FIG. 6A is a diagram showing image data before gain adjustment is performed. In the detection image shown in FIG. 6A, the horizontal axis indicates the movement distance, and the arrow direction indicates the movement in the movement direction B. The vertical axis indicates the depth position, and the arrow direction indicates the deep side. FIG. 6A shows the detection in which the signal intensity of each line shown in FIG. 4 is shown in black and white tones in the vertical axis direction, and the data in black and white tones of all lines is shown in the horizontal axis direction. It is an image. In the present embodiment, for example, the gradation processing is performed such that the larger the intensity of the received signal is, the whiter the signal is, and the smaller the intensity of the received signal is, the blacker the image is.

  Therefore, the shading shown in FIG. 6A indicates the signal intensity. Further, the intensity signal of one line subjected to black-and-white gradation is shown surrounded by a dotted line. FIG. 6B is a diagram illustrating image data obtained by performing a gain adjustment process on the image data of FIG. 6A. As shown in FIG. 6B, the shading is increased by the gain adjustment. Further, since the gain value of the deeper part is higher, the value of the RF data is larger. As a result, the lower image data becomes whitish as a whole. The whitish portion is shown surrounded by a dotted line.

(B. Difference processing unit)
The difference processing unit 32 extracts the RF data at the changed location by calculating the difference from the reference point from the RF data subjected to the gain adjustment. FIG. 7A is a diagram illustrating image data before the difference processing is performed, and FIG. 7B is a diagram illustrating image data after the difference processing is performed. FIG. 7A shows the same image data as FIG. 6B.

  Here, the reference point is the average value of the data acquired so far. For example, in the RF data, when calculating the difference between the signal intensity of the m-th line and the reference point of the signal intensity of n (mm), the depth n (mm) of the 1st to m-1st lines is calculated. The average value of the signal strength is calculated, and the average value is subtracted from the signal strength at the depth n (mm) of the m-th line. By performing this calculation for all the depth positions of all the lines, the change in the RF data signal can be clarified as shown in FIG.

(C. Moving average processing unit)
The moving average processing unit 33 performs a moving average process for each line on the RF data on which the difference processing has been performed. In the present embodiment, for example, the moving average processing can be performed by averaging eight points.
FIG. 8A is a diagram illustrating image data on which the moving average process has been performed, and FIG. 8B is a diagram illustrating the signal strength of the RF data of the line L1 in FIG. 8A. The horizontal axis in FIG. 8B indicates the depth position, and the depth increases along the arrow direction. The vertical axis in FIG. 8B indicates the signal strength, and the signal strength increases along the arrow direction.

  In the present embodiment, the higher the signal intensity, the whiter the gradation, and the lower the signal intensity, the blacker the gradation. In this embodiment, black portions on L1 in FIG. 8A are indicated by P1 to P5 in order to detect a downward peak, that is, a position where black is darkest. These P1 to P5 are also shown in FIG. FIG. 8B shows an upward peak between P2 and P3 as P10.

(D. Primary differential processing unit 34)
The primary differentiation processing unit 34 performs a primary differentiation process on the data on which the difference process has been performed in order to detect a downward peak. The primary differentiation processing unit 34 calculates a difference from the signal intensity at the predetermined depth position to the signal intensity at the next depth position.
FIG. 9 is an enlarged view between P10 and P3 in FIG. FIG. 10 is a diagram showing a table 150 of the signal intensity and the result of the first-order differentiation processing of the graph of FIG. As will be described later, FIG. 10 also shows a result of the chattering process and a graph 151.

The sequence numbers are shown in the leftmost column of the table 150 shown in FIG. The position increases as the sequence number increases. The second column from the left shows the signal strength at each sequence number. The third column from the left shows the difference calculated by the primary differentiation processing unit 34.
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 having the seventh sequence number is a value (−15) obtained by subtracting the seventh signal strength (432) from the eighth signal strength (416).
As described above, the primary differentiation processing unit 34 performs the primary differentiation processing on all data of one line.

(E. Chattering removing unit 35)
The chattering removing unit 35 performs a chattering removing process on the result of the primary differentiation process.

  In the data shown in FIG. 9, in the region R1, the data D2 is larger than the immediately preceding (shallow) data D1 even though the signal intensity data is reduced as a whole, and chattering due to noise occurs. You can see that it is doing. Further, in the region R2, the data D4 and D5 are smaller than the data D3, which indicates that chattering due to noise has occurred. Such chattering occurs when the reflected wave changes depending on the material and grain size of the aggregate contained in the concrete. The chattering removing unit 35 removes such chattering.

The chattering removing unit 35 determines whether the difference between the sequence numbers is a positive value or a negative value. The fourth column from the left indicates whether the change is a positive change (increase) or a negative change (decrease). In the case of a positive (+) change, 1 is indicated, and the negative change is indicated. In the case of the change of (-), -1 is shown.
That is, the chattering removing unit 35 determines whether the change in the signal intensity from the predetermined depth position to the next depth position on the deeper side is an increase or a decrease.

  Here, FIG. 10 shows a graph 151 of a portion surrounded by hatching in Table 150. In the data of ◆ indicating the change (+/−), only the sequence number 11 shows a positive (+) change despite the surrounding negative (−) change, and chattering due to noise occurs in the sequence number 11 You can see that it is doing. The difference of the sequence number 11 and the value of the change (+/−) correspond to the data D1 to D2 in FIG.

  In addition, the sequence numbers 34 and 35 show a positive (+) change despite the negative (-) change in the surroundings, and it can be seen that chattering due to noise occurs in the sequence numbers 34 and 35. The difference between the sequence numbers 34 and the value of the change (+/−) correspond to the change between the data D3 and D4 in FIG. 9, and the difference and the value of the change (+/−) of the sequence number 35 are the same as those in FIG. Corresponding to the change between the data D4 and D5.

  The chattering removing unit 35 performs a chattering removing process on the value of the change (+/−). In the rightmost column of Table 1, values of change (+/-) after noise removal by the chattering removal processing are shown. The chattering removing unit 35 determines that the change is positive (+) when all three consecutive values are larger than 0, and determines that the change is negative (−) when all three consecutive values are smaller than 0. Otherwise, keep the previous value in all other cases.

  More specifically, the chattering removing unit 35 determines that the sequence number n-th change (+/-), n + 1-th change (+/-), and n + 2-th change (+/-) are all positive values (1). , The n-th change (+/−) is determined to be a positive value (1). In addition, the chattering removing unit 35 determines that the sequence number n-th change (+/−), the (n + 1) -th change (+/−), and the (n + 2) -th change (+/−) are all negative values (−1). , The n-th change (+/−) is determined to be a negative value (−1). The chattering removing unit 35 performs the (n−1) th change when the positive and negative of the sequence number nth change (+/−), the (n + 1) th change (+/−), and the (n + 2) th change (+/−) do not match. (+/-) is retained.

For example, the value of the sixth change (+/-) is -1, the value of the seventh change (+/-) is -1, and the value of the eighth change (+/-) is -1. It is. Therefore, the chattering removing unit 35 sets the value of the change (+/−) after the sixth chattering process to −1.
On the other hand, the value of the eleventh change (+/-) at which chattering occurs is 1, the value of the next twelfth change (+/-) is -1, and the value of the thirteenth change (+/-) is 1. ) Is -1. Therefore, the chattering removing unit 35 holds −1, which is the value of the change (+/−) after the tenth chattering process, as the value of the eleventh change (+/−).

Also, the value of the 34th change (+/−) in which chattering occurs is 1, the value of the 35th change (+/−) next to it is 1, and the 36th change (+/−) Is -1. Therefore, the chattering removing unit 35 holds −1, which is the value of the change (+/−) after the 33rd chattering process, as the value of the 34th change (+/−).
Further, the value of the 35th change (+/−) at which chattering occurs is 1, the value of the next 36th change (+/−) is −1, and the 37th change (+/−). ) Is 1. Therefore, the chattering removing unit 35 holds −1, which is the value of the change (+/−) after the 34th chattering process, as the value of the 35th change (+/−).

In the graph 151, in the data of ■ indicating the change (+/−) after the chattering process, the value of the change (+/−) of the sequence number 11 is changed to a negative (−) change, and the sequence numbers 34 and 35 are changed. It can be seen that the value of the change (+/−) has been changed to a positive (+) change, and that chattering has been removed.
The above-described chattering removal processing by the chattering removal unit 35 is performed for each line of RF data.

(F. Peak detector)
The peak detection unit 36 detects a peak of one line of the RF data after the chattering removal processing is performed. In the present embodiment, the downward peak (black peak) indicates the position of the buried object, so the downward peak is detected. Therefore, the peak detection unit 36 detects, as a peak, a point at which the change after the chattering removal processing changes from a negative change to a positive change. Specifically, as shown in Table T1 in FIG. 10, the change after the chattering removal processing in the sequence number 36 is a negative (-) change, and the change after the chattering removal processing in the sequence number 37 is positive ( +), The peak detection unit 36 detects that the signal intensity is a downward peak at the depth position of the sequence number 37.

(1-3-2. Buried object determination unit 24)
As shown in FIG. 5, the buried object determining unit 24 includes a grouping unit 51, a chattering removing unit 52, a shape determining unit 53, and a signal strength determining unit 54. The grouping unit 51 detects, as a group, peaks that are continuous with respect to the moving distance among the plurality of peaks detected by the peak detection unit 36. The chattering removing unit 52 removes chattering of the group. The shape determination unit 53 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, detects a peak at a depth position in the group, and Position. The signal strength determination unit 54 determines the presence or absence of the buried object based on the signal strength of the group when the shape is not determined to be the mountain shape.

(A. Grouping unit 51)
The grouping unit 51 groups the peak detection results obtained by the peak detection unit 36. The grouping unit 51 checks the presence or absence of a peak detection result in order from the past line. Using the result as a starting point, it is checked whether or not a continuous peak is detected in the traveling direction. FIG. 11 is a diagram illustrating image data after preprocessing by the preprocessing unit 23. FIG. 11 shows the line L2 acquired this time. FIGS. 12A to 12D are diagrams for explaining processing by the grouping unit 51. FIG.

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, with the position QS of the first peak found as the starting point (indicated by ● in FIG. 11). Confirm. The line where the peak position Q is found is defined as the current line.
FIG. 12A shows a state where the peak position QS has been found. FIG. 12B shows a case where the next peak position Q2 exists within 5 pixels in the moving direction B of the current line peak position QS and within the upper 5 pixels. In FIG. 12B, the peak position is rising (moving to a shallower side) in the moving direction. FIG. 12C shows a case where the peak position Q2 of the next line exists within 5 pixels and in the lower 5 pixels in the moving direction B of the current line peak position QS. In FIG. 12C, the position of the peak is moving down (moving deeper) in the moving direction.

Subsequently, it is determined whether or not the line on which the peak position Q2 exists is set as the current line, and whether or not the peak of the next line exists within 5 pixels in the movement direction B of the peak position Q2 and within 5 pixels above and below. Thus, every time the RF data of the line is received, the continuity of the peak is confirmed by shifting the current line in the moving direction.
Then, as shown in FIG. 12D, when the peak of the next line does not exist within 5 pixels in the moving direction B of the position Q3 of the peak of the current line and within 5 pixels above and below, the position of the peak Let Qe be the end point of the group (indicated by ■ in FIG. 11).
As described above, the grouping unit 51 performs grouping of peak positions. FIG. 11 shows a group (for example, group G1) in which a black circle and a black square are connected by a line.

(B. Chattering removal unit 52)
Next, the chattering removing unit 52 will be described. The shape of the group is determined by a shape determination unit 53 described later, and chattering is removed before that. FIG. 13 is a diagram illustrating positions of a plurality of peaks that are grouped. In FIG. 13, assuming that the position Qs of the peak, which is the starting point, is the first (No. 1) in the rearward position B, the position of the fifth (No. 5) peak despite the surroundings tending to rise. Q5 moves downward (in a deeper direction) than the fourth (No. 4) peak position Q4, and it can be seen that chattering occurs. Such chattering is removed by the chattering removing unit 52.

  FIG. 1 to No. It is a figure which shows the change of the position of the adjacent peak up to 15. FIG. 14 shows a change from the position of the n-th peak to the position of the (n + 1) -th peak. If the (n + 1) th position is above (shallower) than the nth position, the difference from the next point is defined as a positive (+) change (position change in the surface direction C). If the (n + 1) th position is below (deeper) than the nth position, the difference from the next point is defined as a negative (−) change (position change in the depth direction B).

For example, in the change from the position of the second peak to the position of the third peak, the position of the third peak is shallower than the position of the second peak as shown in FIG. The change from the third to the third is a positive (+) change.
As shown in Table 152 of FIG. 14, between the first and second, between the second and third, between the third and fourth, between the fifth and sixth, between the sixth and seventh, Despite the positive change between the seventh and eighth, there is a negative change between the fourth and fifth due to chattering.

  The chattering removing unit 52 sets the n-th to (n + 1) -th changes to positive (+) when the n-th to (n + 1) -th changes, the (n + 1) to n + 2-th changes, and the (n + 2) to (n + 3) -th changes are all positive (+) changes. Judge. Further, the chattering removing unit 52 sets the n-th to (n + 1) -th changes to negative (+) when the n-th to (n + 1) -th changes, the n + 1 to n + 2-th changes, and the n + 2 to n + 3-th changes are all negative (+) changes. +). If the signs of the n-th to n + 1-th changes, n + 1 to n + 2-th changes, and n + 2 to n + 3-th changes do not match, the chattering elimination unit 52 determines the changes after the (n-1) to n-th chattering elimination processing as n to n-th. It is retained as a change after the (n + 1) th chattering removal process.

For example, since the first to second changes, the second to third changes, and the third to fourth changes are all positive (+), the chattering removing unit 52 sets the first to second changes as shown in Table 153. The change is determined to be positive (+).
On the other hand, the chattering removing unit 52 determines that the second to third changes are positive (+), the third to fourth changes are positive (+), and the fourth to fifth changes are negative (−). , The second and third changes after the chattering removal processing retain the positive (+) of the first and second changes after the chattering removal processing.

Also, the chattering removing unit 52 determines that the fourth to fifth changes are negative (-), the fifth to sixth changes are positive (+), and the sixth to seventh changes are positive (+). The fourth to fifth changes hold positive (+), which is the change after the third to fourth chattering removal processing. Thus, the chattering that has occurred at the fifth time can be removed.
Note that the chattering removing unit 52 determines that the 11th to 12th changes are negative (-) since the 11th to 12th changes, the 12th to 13th changes, and the 13th to 14th changes are all positive (-). to decide.

(C. Shape determination unit 53)
The shape determination unit 53 determines whether the shape of the group after the chattering removal processing is a predetermined mountain shape. FIG. 15 is a diagram illustrating conditions for determining a mountain shape. The shape determining unit 53 determines that the group has a mountain shape when the first condition, the second condition, and the third condition are satisfied.

As shown in FIG. 15, the first condition is that the pixel continuously rises in the upward direction (shallow direction) by 5 pixels or more in the moving direction A, and the second condition is that 5 pixels continuously appear in the moving direction A. As described above, it is descending downward (in the deep direction), and the third condition is that the difference in the depth direction is 10 pixels or more.
When these three conditions are satisfied, the shape determining unit 53 determines that the shape of the group is a mountain shape, and determines that an embedded object exists.

On the other hand, when any one of the first to third conditions is not satisfied, the shape determining unit 53 does not determine that an embedded object exists.
Further, when performing the determination under the first to third conditions, the shape determination unit 53 also detects an upward peak of the position of the group.
The shape determining unit 53 sets the position of the shallowest as the vertex of the group, and stores the position.
The shape determination unit 53 sets the point at which the change in position changes from increasing to decreasing as the vertex of the group. For example, in FIG. 14, since the seventh to eighth changes are positive (+) and the eighth to ninth changes are negative (−), the eighth position has a peak as shown in FIG. Is determined. It is detected that a buried object exists at the position of this peak.

(D. Signal strength determination unit 54)
Since the shape of the ridge in the image data, especially the vicinity of the vertex may become flat due to the difference in the shape and material of the buried object, the conditions for determining the ridge shape (first condition, second condition, third condition) May not apply. For example, as shown in FIG. 16, when a plate-like wood 202 is scanned over a gypsum board 201, the vertices become flat as indicated by R3 of the image data in FIG. That is, as shown in the schematic diagram of the image data in FIG. 18, the first condition and the second condition are satisfied, but the third condition is not satisfied because the width in the vertical direction is 7 pixels.

Therefore, when the first condition and the second condition are satisfied but the third condition is not satisfied, the signal strength determination unit 54 determines the presence or absence of the buried object based on the signal strength.
The signal strength determination unit 54 checks the strengths (AD values) of all reception strengths in the group. In the present embodiment, the setting is such that the AD value becomes a small value (negative direction) when the black color appears dark.
Then, when all of the grouped AD values are smaller than a predetermined threshold, that is, when black is darker than the threshold, it is determined that an embedded object is present.

(1-3-3. Determination result registration unit 25)
The determination result registration unit 25 registers the result (group, peak position, and the like) determined by the buried object determination unit 24 in the RF data management unit 22.

(1-3-4. Display control unit 26)
The display control unit 26 causes the display unit 8 to display the data image indicating the group, the peak position, and the like. FIG. 19 is a diagram illustrating an image displayed on the display unit 8. In FIG. 19, the vertical axis indicates the depth direction, and the horizontal axis indicates the moving distance. Also, the group is shown as a line, the start point in the group is shown by a black triangle, and the end point is shown by a black square. In addition, the peaks detected by the shape determination unit 53 are indicated by crosses.

  The operator can check this image and recognize that the buried object is buried at the peak position. 19, the peak pk1 indicates the position of the buried object 101a, the peak pk2 indicates the position of the buried object 101b, the peak pk3 indicates the position of the buried object 101c, and the peak pk4 indicates the position of the buried object 101d. Indicates the position of.

<2. Operation>
Next, the operation of the embedded object detection device 1 according to the embodiment of the present invention will be described.
(2-1. Impulse control module processing)
FIG. 20 is a flowchart showing the processing of the impulse control module 5.
When the impulse control module process is started, in step S1, when input from the encoder 7, impulse output control is started in step S2. For example, a pulse of an electromagnetic wave 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 in units of 10 psec from 0 to 5120 psec.
Next, in step S4, the control unit 10 AD-converts the RF data received from the reception 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). If not, the control returns to the step S3. By repeating steps S3, S4, and S5, data for one line can be obtained.
Next, in step S6, the AD-converted RF data is transmitted to the main control module 6.

Then, in step S7, the impulse control is stopped.
Next, when the buried object detection device 1 is moved in the movement direction A by the operator, there is an input from the encoder 7, and the control of steps S2 to S7 is performed, and the data of the next one line is obtained, Sent to main control module 6.

(2-2. Main control module processing)
FIG. 21 is a flowchart showing the processing of the main control module 6.
First, in step S11, when the receiving unit 21 receives one line of RF data from the impulse control module 5, in step S12, the preprocessing unit 23 performs preprocessing before determining the buried object.
Next, in step S13, an embedded object determination process is performed by the embedded object determination unit 24.

Next, in step S14, the result determined by the buried object determination unit 24 is registered by the determination result registration unit 25.
Next, the processing in each step will be described in detail.

(2-2-1. Pre-processing)
FIG. 22 is a flowchart showing the preprocessing.
First, in step S21, the gain adjustment unit 31 performs gain adjustment on one line of RF data.
Next, in step S22, the difference processing unit 32 calculates a difference from the reference value, and extracts a change in the RF data.
Next, in step S23, the moving average processing unit 33 performs a moving average process on one line of the RF data subjected to the difference processing. For example, a moving average process can be performed using an 8-point average.

Next, in step S24, the primary differentiation processing unit 34 performs primary differentiation processing on the difference result subjected to the moving average processing, and the difference between adjacent data in the depth direction is positive (increase) or negative (decrease). Is determined.
Next, in step S25, the chattering removing unit 35 performs the chattering removing process on the data after the primary differentiation process.

  Finally, in step S26, the peak detection unit 36 detects the peak of the signal intensity using the determination result after the chattering removal processing has been performed.

(A. Gain adjustment processing)
Next, the gain adjustment processing in step S21 in FIG. 22 will be described. FIG. 23 is a flowchart showing the gain adjustment processing.
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 21.
Then, after the gain adjusting unit 31 performs the process of step S32 on the signal strength data of sequence number 1, the control proceeds to step S33.
In step S33, it is determined whether or not the sequence number is the maximum value. If the sequence number is not the maximum value, the control returns to step S31, the sequence number is incremented by one, and the reception data of the sequence number 2 is Selected. Then, the process of step S32 is performed on the data of sequence number 2.

In this manner, the process is repeated until the process of step S32 is performed on all the data of one line.
In step S32, the data of the signal strength of each sequence number is multiplied by a predetermined magnification.

For example, a sequence No. with the shortest delay time of one line of RF data When a predetermined magnification is applied to the data of the sequence No. 1 (the data at the shallowest position), the sequence No. The sequence No. 1 having a short delay time next to No. 1 The data of No. 2 is multiplied by a predetermined magnification, and the predetermined magnification is multiplied by the sequence number until the sequence number becomes maximum. Specifically, the magnification is increased in the depth direction, the magnification is set to 1 for data of 1 to 25 pixels from the shallow side, and the magnification is set to 2 for data of 26 to 50 pixels. For data of 51 to 75 pixels, the magnification can be set to 3 times, and the magnification can be sequentially increased, and for data of 500 to 511 pixels, the magnification can be set to 21 times.
By this gain adjustment processing, the contrast can be clarified as in the image data shown in FIG.

(B. Difference processing)
Next, the difference processing in step S22 in FIG. 22 will be described. FIG. 24 is a flowchart showing the difference processing.
When the difference processing is disclosed, in step S41, the difference processing unit 32 selects the reception data of the sequence number 1 from the gain-adjusted RF data.
Then, after the difference processing unit 32 performs the processing of steps S42 and S43 on the data of sequence number 1, the control proceeds to step S44.
In step S44, it is determined whether or not the sequence number is the maximum value. If the sequence number is not the maximum value, the control returns to step S41, the sequence number is incremented by one, and the reception data of sequence number 2 is Selected. Then, the processing of steps S42 and S43 is performed on the data of sequence number 2.

In this manner, the flow is repeated until the processing of steps S42 and S43 is performed on all the data of one line.
In step S42, the difference processing unit 32 calculates the average value of the past gain-adjusted reception data (all the reception 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. If the sequence number is not the maximum value, the control returns to step S41, and the number is incremented by one. Thus, the reception data of sequence number 2 is selected.
Steps S42 and S43 are repeated until the numbers are sequentially incremented and the difference processing is performed on all the reception data of one line.

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

(C. First differential processing of the difference result)
Next, the primary differentiation processing of the difference result in step S23 in FIG. 22 will be described. FIG. 25 is a flowchart showing the primary differentiation processing of the difference result.
When the primary differentiation processing of the difference result is started, in step S51, the primary differentiation processing unit 34 selects a difference result of sequence number 1 from the difference results.

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

In this way, the numbers are sequentially incremented and the step S52 is repeated until the primary differentiation 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 processing 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 fourth column from the left of the table 150 in FIG. 10 is calculated.

(D. Chattering removal processing)
Next, the chattering removal processing in step S24 in FIG. 22 will be described. FIG. 26 is a flowchart showing the chattering removal processing.
When the chattering elimination process is started, in step S61, the chattering elimination unit 35 selects the sequence number 1 on which the primary differentiation process has been performed.

Then, after the chattering removing unit 35 performs any of the controls of steps S62 to S66 on the data of sequence number 1, the control proceeds to step S67.
In step S67, it is determined whether or not the sequence number is the maximum value. If the sequence number is not the maximum value, the control returns to step S61, the number is incremented by one, and the reception data of sequence number 2 is selected. Is done.

As described above, the number is sequentially increased and the processing of any one of steps S62 to S66 is repeated until the processing by the chattering removing unit 35 is performed on all the data of one line.
Here, steps S62 to S66 will be described assuming that chattering removal processing is performed on the n-th data.

  In step S62, the chattering removing unit 35 determines whether or not all three successive primary differential results are greater than zero. Since the sequence number n is selected, if the first-order differential results of the sequence numbers n, n + 1, n + 2 are all 0 or more, the chattering removing unit 35 performs the first-order differentiation after the chattering removing process on the sequence number n in step S63. Store the result as positive (+).

  On the other hand, in step S62, if at least one of the primary differential results of the three consecutive sequence numbers is equal to or less than 0, the chattering removing unit 35 determines in step S64 that all three consecutive primary differential results are smaller than 0. It is determined whether or not. Since the sequence number n has been selected, if the first-order differential results of the sequence numbers n, n + 1, and n + 2 are all smaller than 0, the chattering removing unit 35 performs the primary operation after the chattering removing process on the sequence number n in step S65. The differential result is stored as negative (-).

In addition, in step S63, if at least one of the three consecutive primary differentiation results is larger than 0, the control proceeds to step S66.
Then, in step S66, the chattering removing unit 35 stores the state of the previous sequence number as the state of the current sequence number. Since the sequence number n is selected, the chattering removing unit 35 compares the positive (+) or negative (−) result after the chattering removal processing stored for the sequence number n−1 with the value after the chattering removal processing for the sequence number n. The result is stored.
Thereby, the change after the chattering process on the rightmost side of the table 150 in FIG. 10 can be obtained.

(E. Peak detection processing)
Next, the peak detection processing in step S25 in FIG. 22 will be described. FIG. 27 is a flowchart showing the peak detection processing.

When the peak detection processing is started, in step S71, the peak detection unit 36 selects the sequence number 1 on which the chattering removal processing has been performed.
Then, after performing the control of steps S72 and S73 for the data of sequence number 1, the peak detection unit 36 proceeds to step S74.
In step S74, it is determined whether or not the sequence number is the maximum value. If the sequence number is not the maximum value, the control returns to step S71, the sequence number is incremented by one, and the reception data of the sequence number 2 is Selected. Then, the processing of steps S72 and S73 is performed on the data of sequence number 2.

In this way, the numbers are sequentially incremented and the processing of steps S72 and S73 is repeated until the processing by the chattering removing unit 35 is performed on all of the data for one line.
Here, steps S72 to S73 will be described assuming that peak detection processing is performed on the n-th data.

In step S72, the peak detection unit 36 determines whether the previous state of the sequence number n-1 after the removal of chattering is negative (-) and the state of the current sequence number n is positive (+). .
If the state of the previous sequence number n-1 is negative (-) and the state of the current sequence number n is positive (+), the peak detecting unit 36 stores the n-th coordinate in step S73. I do. The coordinates can be represented by a moving distance (also referred to as a line number) and a depth position in units of pixels, for example.
Thereby, as described above, for example, the sequence number 37 in the table 150 of FIG. 10 can be detected as a peak.

(2-2-2. Buried object determination processing)
Next, the embedded object determination processing shown in step S13 of FIG. 21 will be described. FIG. 28 is a flowchart showing an embedded object determination process.
When the buried object determination process is started, first, in step S81, the grouping unit 51 performs a grouping process of the peak detection results performed in the preprocessing unit 23.

Next, in step S82, the chattering removing unit 52 performs a chattering removing process on the grouped groups.
Next, in step S83, the shape determination unit 53 or the signal strength determination unit 54 performs an embedded object determination process.
Next, in step S84, the display control unit 26 puts an x mark on the position of the peak detected by the shape determination unit 53 and causes the display unit 8 to display the mark.

(A. Grouping processing of peak detection results)
The grouping processing of the peak detection result in step S81 in FIG. 28 will be described. FIG. 29 is a flowchart showing a grouping process of peak detection results.

First, in step S91, the grouping unit 51 sets the detection state to an “undetected” state.
In step S92, the grouping unit 51 selects old data in the past as processing targets for all data acquired in the past. Then, in step S103, the grouping unit 51 determines whether or not the processing has been performed on all of the data acquired in the past up to the line acquired this time. If the processing has not been performed, the control returns to step S92, and the next The oldest data is processed. In this way, for example, the processing of steps S93 to S102 is performed sequentially from the sequence number 1 of the oldest line.

In step S93, the grouping unit 51 determines whether 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, the predetermined range may be set to one line, or may be set to the sequence number of one line.

As described above, in step S94, it is determined whether there is a position where a peak is detected in order from the oldest data. If there is a position where a peak is detected, in step S95, the grouping unit 51 The detection state is “detected”.
Next, in step S96, the grouping unit 51 stores the point at which the peak was detected. This point is a coordinate in units of pixels, and can be indicated by, for example, a moving distance (also referred to as a line number) and a depth position. Note that this point corresponds to the starting point (●) in FIGS. 11 and 19.

Next, after step 103 and step S92, the next data is processed.
Next, in step S93, since the detection state is "detecting", the control proceeds to step S97.
In step S97, the grouping unit 51 determines whether or not there is a position where a peak is detected within a predetermined range from the position stored in step S96. The predetermined range can be set, for example, within 5 pixels in the moving direction described with reference to FIGS. 12A to 12D and within 5 pixels up and down. If the position at which the peak is detected is within the predetermined range, in step S98, the grouping unit 51 determines 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, if the current depth position is shallower than the previous depth position, positive (+) is stored as the depth position is rising. If the current depth position is deeper than the previous depth position, a negative value (−) is stored as the depth position is lowered.

Next, after step S97 and step S92, the next data is processed.
Next, in step S93, since the detection state is "detecting", the control proceeds to step S97.
In this step S97, it is detected whether or not a point at which a peak is detected exists within a predetermined range from the point previously stored in step S98. If so, in step S99, the point is stored. . Then, in step S100, the previous point and the comparison result are stored. As a result, as shown in FIG. 14, continuous points are sequentially grouped, and whether the change to the next point is ascending or descending is stored.

If no peak is detected in the predetermined range in step S97, the control proceeds to step S101.
In step S101, the grouping unit 51 determines that there is no continuous point, and stores the detection results up to that point. The last detected point corresponds to the end point (点) in FIG. 11 and FIG.
Next, in step S102, the grouping unit 51 sets the detection state to an “undetected” state.
Then, in step S103, when it is determined that the processing has been performed on all the data of the previously acquired line, the processing ends.

(B. Chattering removal processing)
The chattering removal processing in step S82 of FIG. 28 will be described. FIG. 30 is a flowchart showing the chattering removal processing.

The chattering removal processing is performed on all data resulting from the grouping.
When the chattering removal processing is started, in step S111, the chattering removal unit 52 selects data in order from the start point side of the grouped data. For example, in step S111, the chattering removing unit 52 sets the data of the change from the first to the second shown in FIG. 14 as a processing target.

Next, in step S112, the chattering elimination unit 52 reads the comparison result of consecutive points. When the selected data is a change from the first to the second, the data of the change from the first to the second, the change from the second to the third, and the change from the third to the fourth are read.
Next, in step S113, the chattering removing unit 52 determines whether all three consecutive comparison results are greater than zero. In the data shown in Table 152 in FIG. 14, since the change from the first to the second, the change from the second to the third, and the change from the third to the fourth are all larger than 0, the chattering removing unit 52 Indicates that the state of change from the first to the second after the removal of chattering is positive (+) (it can be said to be rising in a shallow direction), as shown in Table 153 of FIG.

Next, in step S113, the chattering removing unit 52 determines whether or not the processing has been performed on all the data as a result of the grouping. If the processing has not been completed, the control returns to step S111. The data of the change from the third to the third is selected as a processing target.
In this way, processing is performed for all changes in the grouped data.

  In step S113, if any one of the three consecutive comparison results is equal to or smaller than 0, the control proceeds to step S115, and the chattering removing unit 52 determines whether all three consecutive comparison results are smaller than 0. Is determined. If the eleventh to twelfth are targets for processing, in the table 152 of FIG. 14, the change from the eleventh to the twelfth, the change from the twelfth to the thirteenth, and the change from the thirteenth to the fourteenth are all Since it is smaller than 0, the chattering removing unit 52 sets the state of change from the eleventh to the twelfth after the removal of chattering as negative (-) (falling in the deeper direction) as shown in Table 153 of FIG. It can be said).

On the other hand, in step S115, if any one of the three consecutive comparison results is 0 or more, the control proceeds to step S117.
In step S117, the chattering removing unit 52 sets the state after the chattering removal to the previous state. For example, when the fourth to fifth changes are to be processed, in FIG. 14, the fourth to fifth changes are negative (-), and the fifth to sixth changes are positive (+). And the change from the sixth to the seventh is positive (+). Therefore, as shown in Table 153 of FIG. 14, the state of the fourth to fifth changes is positive (+), which is the state after the previous third to fourth chattering processing.

  As described above, the chattering removing unit 52 performs the n-th to (n + 1) -th change when the n-th to (n + 1) -th change, the (n + 1) to (n + 2) -th change, and the (n + 2) to (n + 3) -th change are all positive (+) changes. Judge as positive (+). Further, the chattering removing unit 52 sets the n-th to (n + 1) -th changes to negative (+) when the n-th to (n + 1) -th changes, the n + 1 to n + 2-th changes, and the n + 2 to n + 3-th changes are all negative (+) changes. +). The chattering elimination unit 52 holds the (n-1) to (n) -th changes when the signs of the (n) to (n + 1) th changes, the (n + 1) to (n + 2) th changes, and the (n + 2) to (n + 3) th changes do not match.

Then, if it is determined in step S118 that the processing has been performed on all the grouped data, the processing ends. If the processing has not been performed for all data, the control returns to step S111, and the next data is selected.
With the above processing, a table 153 after chattering removal in FIG. 14 is obtained.

(C. Buried object determination processing)
The embedded object determination processing in step S83 in FIG. 28 will be described. FIG. 31 is a flowchart showing an embedded object determination process.
The buried object determination process is performed on all data resulting from the grouping.
When the embedded object determination process is started, in step S121, the shape determination unit 53 selects data in order from the start point side of the grouped data. For example, in step S121, the shape determination unit 53 sets the data after the chattering removal of the change from the first to the second shown in FIG. 14 as a processing target.

In step S122, the shape determination unit 53 reads the result after the chattering removal processing of the change from the first to the second.
In step S123, the shape determination unit 53 determines whether the result of the change after the chattering removal processing is positive (+). For example, since the result after the chattering removal processing of the change from the first to the second shown in FIG. 14 is positive (+), the control proceeds to step S124.

In step S124, the shape determination unit 53 sets the-(minus) count to 0.
Next, in step S125, the shape determining unit 53 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 53 stores the first Y coordinate (depth position) and sets a start point.

Next, in step S127, the shape determination unit 53 sets the + (plus) count to +1.
Next, in step S138, the shape determination unit 53 determines whether or not the processing has been completed for all the data resulting from the grouping. If not, control returns to step S121, and the next step is performed. The data (change from the second to the third) is selected as a processing target.

Then, in step S122, the shape determination unit 53 reads out the result after the chattering removal processing of the change from the second to the third.
Next, in step S123, the shape determination unit 53 determines whether or not the result of the change after the chattering removal processing is positive (+). For example, since the result after the chattering removal processing of the change from the second to the third shown in FIG. 14 is positive (+), the control proceeds to step S124.

Next, in step S125, the shape determining unit 53 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 53 adds +1 to the + (plus) count and sets it to +2.

Thus, steps S121 to S127 and step S138 are repeated. Then, in step S123, when the result of the change after the chattering removal processing becomes negative (-), the control proceeds to step S128.
In step S128, the shape determining unit 53 determines whether or not the + count is 5 or more. Here, when the count is 5 or more, it satisfies the condition 1 of continuously increasing in the Y-axis direction by 5 pixels or more.

In the data shown in FIGS. 13 and 14, for example, the result after the chattering removal processing of the change from the eighth to the ninth is negative (−), and up to that time, seven positive (+) exist. The + count is 7. Therefore, control proceeds to step S129.
In step S129, the shape determination unit 53 determines whether the-(minus) count is 0. Since the minus count is 0, the control proceeds to step S130.

In step S130, the shape determination unit 53 stores the previous depth position (also referred to as the Y coordinate). That is, the shape determination unit 534 stores the Y coordinate of the peak of the mountain (the point at which the slope changes from + to-). In the data of FIGS. 13 and 14, the eighth Y coordinate, which is the previous point in the change from the eighth to the ninth, is stored.
Next, in step S131, the shape determination unit 53 adds +1 to the-(minus) count.

  Next, in step S132, the shape determination unit 53 determines whether the-(minus) count is 5 or more. Here, when the count is 5 or more, it satisfies the condition 2 that the number of pixels continuously drops in the Y-axis direction by 5 pixels or more. In the case of the change from the eighth to the ninth, since the -count is +1, the control proceeds to step S138, and the result after the chattering process of the change from the ninth to the tenth is obtained through step S121. Selected as target.

As described above, the results are sequentially selected, and when the result after the chattering processing of the change from the twelfth to the thirteenth is selected as the processing target, the minus (−) count in step S132 becomes +5 or more. The control proceeds to step S133.
In step S133, the shape determining unit 53 calculates a difference between the Y coordinate of the starting point and the Y coordinate of the vertex. 13 and 14, the difference between the first Y coordinate and the eighth Y coordinate is calculated.

Next, in step S134, the shape determining unit 53 determines whether the calculated difference is 10 or more. Here, when it is 10 or more, it satisfies the condition 3 that the difference in the Y-axis direction is 10 pixels or more.
If the calculated difference is 10 or more, in step S135, the shape determining unit 53 determines that the group and the loop are mountain-shaped, and determines that there is an embedded object.

  On the other hand, when the calculated difference as shown in FIG. 18 is less than 10, the control proceeds to step S136, and the embedded object determination process 2 is executed. The embedded object determination process 2 is a process of determining an embedded object when the shape of the embedded object is not round but flat.

(D. Buried object determination processing 2)
Next, the embedded object determination process 2 in step S136 in FIG. 31 will be described. FIG. 32 is a flowchart showing the embedded object determination process 2.
The buried object determination process 2 is performed on all the data resulting from the grouping.
When the buried object determination processing 2 is started, in step S141, the signal strength determination unit 54 selects data in order from the start point side of the grouped data. For example, in step S141, the signal strength determination unit 54 processes the first data shown in FIG.
Next, in step S142, the signal strength determination unit 54 reads the value of the first received data (received strength / AD value).

Next, in step S143, the signal strength determination unit 54 determines whether the AD value of the first received data is smaller than a predetermined value. Here, when the black color is dark, the AD value is in the direction of a smaller value (minus), and when it is smaller than the predetermined value, it can be determined that the black color is darker than the predetermined darkness.
Next, in step S144, the signal strength determination unit 54 determines whether or not the processing has been completed for all the data as a result of the grouping. If the processing has not been completed, the control returns to step S141. Is selected as a processing target.

  Then, the processing of steps S142 and S143 is performed on the selected second data. As described above, the processing is performed on all the grouped data, and when the signal strengths of all the data are smaller than the predetermined value, the signal strength determination unit 54 determines in step S145 that an embedded object is present. On the other hand, if at least one of the grouped data is determined to be equal to or greater than the predetermined value in step S143, it is not determined that there is an embedded object, and the control ends.

In step S84 in FIG. 28, the display control unit 26 displays an image on the display unit 8 with an X mark at the position of the eighth data, which is the vertex, in the example shown in FIGS. See FIG. 19).
[Other embodiments]
As described above, one embodiment of the present invention has been described, but the present invention is not limited to the above embodiment, and various changes can be made without departing from the gist of the invention.

(A)
In the above embodiment, the control method of the buried object detection device 1 and the main control module 6 (an example of the data processing device) has been described by way of example in accordance with the flowcharts shown in FIGS. 20 to 32. It is not limited.
For example, the present invention may be realized as a program that causes a computer to execute a control method of the embedded object detection device 1 and the main control module 6 (an example of a data processing device) that is performed according to the flowcharts illustrated in FIGS. .

Further, one usage form of the program may be such that the program is recorded on a recording medium such as a ROM, which is readable by a computer, and operates in cooperation with the computer.
One usage form of the program may be a mode in which the program is transmitted through a transmission medium such as the Internet or a transmission medium such as light, radio waves, or sound waves, read by a computer, and operates in cooperation with the computer.
Further, the above-described computer 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 control method of the power consuming body may be realized by software or may be realized by hardware.

(B)
In the above-described embodiment, the rebar has been described as an example of the buried object.However, the rebar is not limited thereto, and may be a gas pipe, a water pipe, wood, or the like. The target object is not limited to concrete.

(C)
In the above-described embodiment, black is set to indicate an embedded object by gradation processing. However, the present invention is not limited to this, and white may be set to indicate an embedded object.

(D)
In the chattering removal processing (step S25) in the preprocessing of the above embodiment, three data are used as an example of the predetermined number, but the number is not limited to three. In the chattering removal process (step S82) in the embedded object determination process, three data are used as an example of the predetermined number, but the number is not limited to three.

(E)
In the present embodiment, the main control module 6 is provided in the embedded object detection device 1, but the main control module 6 may be provided separately from the embedded object detection device 1. In this case, for example, the embedded object detection device is provided with a main body 2, a handle 3, wheels 4, an impulse control module 5, an encoder 7, and the like. 8 may be provided. Communication between the buried object detection device and the tablet may be performed wirelessly or by wire.

  The data processing device and the buried object detection device of the present invention can remove a noise component even when there is a change in the material around the buried object, and have an effect that the buried object can be detected in real time. It is useful for detecting embedded objects in concrete.

1: buried object detection device 2: body part 3: handle 4: wheel 5: impulse control module 6: main control module (an example of a data processing device)
7: Encoder 8: Display unit 10: Control unit 11: Transmitting antenna 12: Receiving antenna 13: Pulse generating unit 14: Delay unit 15: Gate unit 21: Receiving unit (an example of a receiving unit)
22: RF data management unit 23: preprocessing unit 24: buried object determination unit (an example of a buried object determination 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 differentiation processing unit (an example of a difference calculation unit)
35: Chattering removing unit 36: Peak detecting unit (an example of a signal intensity peak detecting unit)
37: sequence number 41: increase / decrease determination unit 43: step 51: grouping unit (an example of a grouping unit)
52: Chattering removing unit (an example of a noise removing unit)
53: Shape determination unit (an example of a buried object detection unit, an example of a shape determination unit)
54: Signal strength determination unit (an example of a buried object detection unit, an example of a signal strength determination unit)
100: concrete 100a: surface 101: embedded object 101a: embedded object 101b: embedded object 101c: embedded object 101d: embedded object 151: graph 202: wood 534: shape determination unit

Claims (8)

A data processing device for detecting a buried object in the object using data on reflected waves of electromagnetic waves radiated toward the object while moving the surface of the object,
A receiving unit that receives data related to the reflected wave measured at each timing associated with the movement,
A signal strength peak detector that detects a peak of the signal strength in a depth direction of the object at each of the timings,
Of the depth positions at the signal strength peaks detected at the respective timings, the depth positions at a plurality of the signal strength peaks that are continuous within a predetermined interval in the moving direction are defined as one group. A grouping unit,
A noise removing unit that removes noise from the group based on a change in the depth position of the plurality of peaks in the group;
Based on the group from which the noise has been removed, comprising an embedded object detection unit that detects the presence or absence of the embedded object,
Data processing device. The grouping unit is configured such that, in the moving direction, a change in position of the depth position of the peak at the predetermined timing from the depth position of the peak at the timing before the predetermined timing is in the depth direction. Determine whether the position change in the direction of the position change in the direction of the position change or surface direction,
The noise removing unit removes noise based on a direction of the position change at the depth position of the predetermined number of adjacent peaks,
The data processing device according to claim 1. The noise removing unit includes:
When the direction of the position change at the depth position of the predetermined number of the adjacent peaks including the depth position of the predetermined peak coincides with each other, the direction of the coincident position change is changed to the predetermined depth position. Adopted as a result of the direction of the position change after the noise removal processing in
When the direction of the position change at the depth position of the predetermined number of adjacent peaks does not match, the direction of the position change after the noise removal processing at the depth position of the peak before the predetermined peak is The result is adopted as a result of the direction of the position change after the noise removal processing at the depth position of the predetermined peak,
The data processing device according to claim 2. The buried object detection unit,
In the plane in the moving direction and the depth direction, when the group has a predetermined shape, it is determined that the buried object is present, and when the group is not the predetermined shape, it is determined that the buried object is not present. Having a part,
The data processing device according to claim 1. The predetermined shape is a mountain shape,
The shape determination unit,
A first condition in which the depth position of the peak of the signal intensity is continuously reduced by a predetermined amount or more along the moving direction;
A second condition in which the depth position of the peak is continuously greater than or equal to a predetermined amount along the moving direction,
When the width of the depth position of the group satisfies all of the third conditions that are equal to or greater than a predetermined amount, it is determined that the group has a mountain-shaped waveform.
The data processing device according to claim 4. The buried object detection unit,
When the first condition and the second condition are satisfied but the third condition is not satisfied, a signal strength determination for determining the presence or absence of the buried object based on the signal strength of each of all the peaks in the group Further comprising a part,
The data processing device according to claim 5. The shape determination unit detects a peak at the depth position of the group determined to be a mountain shape,
The data processing device according to claim 5. A data processing device according to claim 7,
A display unit capable of displaying the mountain-shaped group,
In the previous period display unit, a display indicating the peak of the detected position is performed together with the mountain-shaped group,
Buried object detection device.

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