JP7378203B2 - Data processing equipment and buried object detection equipment - Google Patents

Description

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

As a device for searching for buried objects in concrete, a wall scanner is used that detects buried objects from reflected waves of electromagnetic waves emitted toward concrete while moving on the concrete surface (for example, see Patent Document 1). .
Conventional wall scanners use a noise component removal method using frequency analysis using Fourier transform, and a filtering process that extracts striped noise components in each axis direction and removes them from data.

Patent No. 2893010

However, in the filtering process using the frequency analysis described above, it becomes difficult to remove noise components due to changes in the material surrounding the buried object (for example, differences in the material of concrete walls, etc.), and the processing speed increases, so that Could not be detected.
An object of the present invention is to provide a data processing device and a buried object detection device that can remove noise components even when there is a material change around the buried object and can detect the buried object in real time. That's true.

A data processing device according to a first invention is a data processing device for detecting a buried object within an object using data regarding reflected waves of electromagnetic waves emitted toward the object while moving on the surface of the object. It includes a receiving section, a signal strength peak detecting section, a grouping section, a noise removing section, and a buried object detecting section. The receiving unit receives data related to reflected waves measured at each timing associated with movement. The signal strength peak detection unit detects the peak of signal strength in the depth direction of the object at each timing. The grouping unit groups the depth positions of a plurality of consecutive signal strength peaks within a predetermined interval in the movement direction from among the depth positions of the signal strength peaks detected at each timing. . The noise removal unit removes noise from the group based on changes in the depth positions 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.

In this way, noise is removed based on changes in the depth position of the peak without using frequency conversion, etc., so even if there are changes in the material around the buried object, the processing speed is fast and the buried object can be detected in real time. be able to.
Furthermore, by removing noise, the presence or absence of a buried object can be detected more accurately.

A data processing device according to a second invention is the data processing device according to the first invention, in which the grouping unit is configured to detect a depth position of the peak at a predetermined timing at a timing before the predetermined timing in the moving direction. It is determined whether the positional change from the depth position of the peak in is a positional change in the depth direction or a positional change in the surface direction. The noise removal unit removes noise based on the direction of position change in depth positions of a predetermined number of adjacent peaks.
With this, for example, if noise occurs such that the depth position suddenly becomes shallower while it is becoming deeper, that noise can be removed.

A data processing device according to a third invention is the data processing device according to the second invention, in which the noise removing unit is configured to remove noise from a predetermined number of adjacent peak depth positions including a predetermined peak depth position. If the directions of change match, the matched direction of position change is adopted as the result of the direction of position change after noise removal processing at a predetermined depth position, and the positions of a predetermined number of adjacent peaks at the depth position are If the directions of change do not match, the result of the direction of position change after noise removal processing at the depth position of the peak before the predetermined peak is calculated as the position change after noise removal processing at the depth position of the predetermined peak. Adopt as a result of direction.
With this, for example, if noise occurs such that the depth position suddenly becomes shallower while it is becoming deeper, that noise can be removed.

A data processing device according to a fourth invention is the data processing device according to the first invention, in which the buried object detection section includes a shape determination section. The shape determination unit determines that a buried object exists when the group has a predetermined shape in a plane in the movement direction and the depth direction, and determines that a buried object does not exist when the group does not have a predetermined shape.
In this way, when the peaks continue in the moving direction and the shape is a predetermined shape, it can be determined that a buried object exists. Note that the predetermined shape may be, for example, a mountain shape.

A data processing device according to a fifth invention is the data processing device according to the fourth invention, in which the predetermined shape is a mountain shape, and the shape determination section is configured to determine the peak of the signal intensity along the moving direction. A first condition in which the depth position is continuously shallower by a predetermined amount or more, a second condition in which the peak depth position is continuously deeper by a predetermined amount or more along the movement direction, and a group depth position. When all of the third conditions, in which the width is equal to or greater than a predetermined amount, are satisfied, it is determined that the group has a mountain-shaped waveform.
When these three conditions are satisfied, it can be determined that the waveform is a mountain-shaped waveform, and the presence or absence of a buried object can be determined.

A data processing device according to a sixth invention is the data processing device according to the fifth invention, in which the buried object detection section further includes a signal strength determination section. The signal strength determination unit satisfies the first condition and the second condition, but when the third condition is not satisfied, the signal strength determination unit determines the presence or absence of a buried object based on the signal strength of each of all the peaks in the group.
Depending on the shape of the buried object, the waveform may become a flat mountain shape (the first and second conditions are satisfied, but the third condition is not satisfied), but even in such cases, the signal strength Based on this, it is possible to determine whether there is a buried object.

A data processing device according to a seventh invention is the data processing device according to the fifth or sixth invention, wherein the shape determining section detects a peak at a depth position of a group determined to be mountain-shaped. .
By detecting the peak position of the mountain-shaped waveform in this manner, the position of the buried object can be detected.

A buried object detection device according to an eighth invention includes the data processing device according to the seventh invention and a display section. The display unit can display a mountain-shaped group. The display section displays a mountain-shaped group and a peak at the detected position.

By displaying the detected peak position on the display unit in this manner, the user can easily recognize the position of the buried object.

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

FIG. 1 is a perspective view showing the configuration of a buried object detection device according to an embodiment of the present invention. FIG. 2 is a block diagram showing the configuration of the buried object detection device shown in FIG. 1. FIG. 3 is a block diagram showing the configuration of the pulse control module of FIG. 2. FIG. 4 is a diagram showing reflected wave data acquired by the MPU in FIG. 3. FIG. FIG. 3 is a block diagram showing the configuration of the main control module in FIG. 2; (a) A diagram showing image data before performing gain adjustment; (b) A diagram showing image data after gain adjustment processing. (a) A diagram showing image data before performing differential processing; (b) A diagram showing image data after differential processing. (a) A diagram showing image data after performing moving average processing, (b) A diagram showing the signal strength of RF data of line L1 in FIG. 8(a). An enlarged view between P10 and P3 in FIG. 8(b). FIG. 4 is a diagram for explaining processing in an increase/decrease determination unit 41. FIG. A diagram showing image data after preprocessing. (a) to (d) Diagrams for explaining processing by a grouping unit. FIG. 3 is a diagram showing the positions of a plurality of grouped peaks. No. shown in FIG. 1~No. FIG. 2 is a diagram showing changes in the positions of up to 15 adjacent peaks. The figure which shows the conditions for determining that it is a mountain shape. A diagram showing a state in which a plate-shaped piece of wood is scanned through a plasterboard. FIG. 17 is a diagram showing image data detected by the scan of FIG. 16; FIG. 18 is a diagram schematically shown to explain image data such as that shown in FIG. 17; 3 is a diagram showing image data displayed on the display section of FIG. 2. FIG. FIG. 3 is a flow diagram showing processing of the impulse control module. FIG. 3 is a flow diagram showing processing of the main control module. FIG. 22 is a flow diagram showing the preprocessing of FIG. 21; 23 is a flow diagram showing the gain adjustment process of FIG. 22. FIG. 23 is a flow diagram showing the difference processing in FIG. 22. FIG. FIG. 23 is a flowchart showing the first-order differential processing of the difference results in FIG. 22; 23 is a flow diagram showing the chattering removal process of FIG. 22. FIG. 23 is a flow diagram showing the peak detection process of FIG. 22. FIG. FIG. 22 is a flow diagram showing the buried object determination process of FIG. 21; FIG. 29 is a flow diagram showing the grouping process of FIG. 28; FIG. 29 is a flow diagram showing the chattering removal process of FIG. 28; FIG. 29 is a flow diagram showing the buried object determination process in FIG. 28; 32 is a flow diagram showing buried object determination processing 2 in FIG. 31. FIG.

EMBODIMENT OF THE INVENTION Below, the buried object detection apparatus based on embodiment of this invention is demonstrated based on drawing.
<1. Configuration>
(1-1. Overview of buried object detection device 1)
FIG. 1 is a perspective view showing a state in which a buried object detection device 1 according to an embodiment of the present invention is placed on concrete 100. FIG. 2 is a block diagram showing a schematic configuration of the buried object detection device 1 in this embodiment.

The buried object detection device 1 of this embodiment radiates electromagnetic waves to the concrete 100 while moving on the surface 100a of an object such as concrete 100, and receives and analyzes the reflected waves. The positions of 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, for example, at depths of 20 cm, 15 cm, 10 cm, and 5 cm in order from the surface 100a. The depth direction is indicated by arrow B, and the surface direction is indicated by arrow C.

The buried 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 section 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 part 2. When detecting a buried object inside the concrete 100, the operator moves the buried object detection device 1 on the surface 100a of the concrete 100 while holding the handle 3 and rotating the wheels 4.

The impulse control module 5 controls the timing of emitting electromagnetic waves toward the concrete 100 and the timing of receiving reflected waves of the emitted electromagnetic waves.
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 regarding the reflected waves received by the impulse control module 5 and performs buried object detection.
The display section 8 is provided on the upper surface of the main body section 2, and displays images showing the positions of the buried objects 101a, 101b, 101c, and 101d.

(1-2. Impulse control module 5)
FIG. 3 is a block diagram showing the configuration of the impulse control module 5. As shown in FIG.
The impulse control module 5 includes a control section 10 , a transmitting antenna 11 , a receiving antenna 12 , a pulse generating section 13 , a delay section 14 , and a gate section 15 .

The control section 10 is composed of an MPU (Micro Processing Unit) and the like, and uses an encoder input as a trigger to instruct the pulse generation section 13 to generate pulses. The pulse generator 13 generates pulses based on commands from the MPU and sends them to the transmitting antenna 11. The transmitting antenna 11 radiates electromagnetic waves at a constant cycle based on the pulse cycle. The timing of input to the encoder 7 corresponds to an example of timing.

The receiving antenna 12 receives reflected waves of the radiated electromagnetic waves. When the gate section 15 receives the pulse from the delay section 14 , it takes in the reflected wave received by the receiving antenna 12 and transmits it to the control section 10 . The delay unit 14 transmits pulses to the gate unit 15 at predetermined intervals to capture reflected waves. This predetermined interval has a pitch of 2.5 msec.
Thereby, the impulse control module 5 outputs electromagnetic waves from the transmitting antenna 11 multiple times using the input from the encoder 7 as a trigger. The impulse control module 5 can acquire received data for each distance from the receiving antenna 12 by delaying the reception timing using a delay IC provided by the delay section 14.

FIG. 4 is a diagram showing reflected wave data acquired by the MPU. The vertical axis indicates the strength of the received signal in -4096 to +4096 gradations centered on the axis O, and the direction of the arrow indicates the negative side. The horizontal axis indicates the distance to 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. Moreover, a long distance corresponds to a deep depth.

Although the details will be described later, since the waveform W1 shown in FIG. 4 includes reflected waves reflected by the antenna without being irradiated into the concrete 100 (p1, etc.), by calculating the difference from the reference waveform, , changes in data of reflected waves from within the concrete 100 are extracted.
Further, the data shown in FIG. 4 is data from when the encoder 7 is input to when the encoder 7 is input next. By gradually delaying the reception timing, reflected waves from a position with a long distance from the receiving antenna 12 are received. However, when there is an input from the encoder 7, the delay in the reception timing is returned to the original value, and the reception timing is changed again. Gradually delay. That is, the reflected wave in the depth direction B at a predetermined measurement position in the movement direction A (the position where the input from the encoder 7 is received) is received. The reflected wave data from the time when the encoder 7 is input as shown in FIG. 4 to the time when the next encoder is input is referred to as data for one line. The control unit 10 transmits one line of RF (Radio Frequency) data to the main control module 6 every time one line of data is accumulated.
Note that since the buried object detection device 1 is being moved, the measurement positions are 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. As shown in FIG.
The main control module 6 includes a reception section 21 , an RF data management section 22 , a preprocessing section 23 , a buried object determination section 24 , a determination result registration section 25 , and a display control section 26 .

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

(1-3-1. Preprocessing section 23)
The preprocessing section 23 includes a gain adjustment section 31 , a difference processing section 32 , a moving average processing section 33 , a first-order differential processing section 34 , a chattering removal section 35 , and a peak detection section 36 .

(a. Gain adjustment section)
The gain adjustment section 31 performs gain adjustment on the RF data line by line. As the distance from the transmitting antenna 11 and the receiving antenna 12 increases (as the delay time increases), the reception sensitivity decreases, so that the shading of white and black decreases when displaying an image to be described later. Therefore, the gain adjustment unit 31 increases the gain value (×1 to ×20) by which the signal strength is multiplied (amplified) as the depth position becomes deeper.

FIG. 6(a) is a diagram showing image data before gain adjustment. In the detection image shown in FIG. 6(a), the horizontal axis indicates the moving distance, and the direction of the arrow indicates the movement in the moving direction B. The vertical axis indicates the depth position, and the direction of the arrow indicates the deeper side. The diagram shown in FIG. 6(a) shows the signal intensity of each line shown in FIG. 4 in black and white gradation along the vertical axis, and the detection data on all the lines in black and white gradation along the horizontal axis. It is an image. Note that, in this embodiment, gradation processing is performed so that, for example, the intensity of the received signal is higher, the color becomes white, and the intensity of the received signal is smaller, the color becomes black.

Therefore, the shading shown in FIG. 6(a) indicates the signal strength. Further, one line of intensity signal with black and white gradation is shown surrounded by a dotted line. FIG. 6(b) is a diagram showing image data obtained by performing gain adjustment processing on the image data of FIG. 6(a). As shown in FIG. 6(b), the shading becomes stronger by adjusting the gain. Furthermore, since the gain value is higher at a deeper location, the value of the RF data becomes larger. Therefore, the image data at the bottom becomes whitish overall. The whitish area is shown surrounded by a dotted line.

(b. Difference processing section)
The difference processing unit 32 extracts RF data at a changed location from the gain-adjusted RF data by calculating the difference between the gain-adjusted RF data and the reference point. FIG. 7(a) is a diagram showing image data before performing differential processing, and FIG. 7(b) is a diagram showing image data after performing differential processing. FIG. 7(a) shows the same image data as FIG. 6(b).

Here, the reference point is the average value of the data acquired so far. For example, in RF data, when calculating the difference between the signal strength of the mth line at depth n (mm) and the reference point, An average value of the signal intensity is calculated, and the average value is subtracted from the signal intensity of the m-th line at a depth n (mm). By performing this calculation for all depth positions of all lines, changes in the RF data signal can be made clear as shown in FIG. 7(b).

(c. Moving average processing unit)
The moving average processing unit 33 performs moving average processing on each line of the RF data that has been subjected to the difference processing. In this embodiment, moving average processing can be performed using an 8-point average, for example.
FIG. 8(a) is a diagram showing image data subjected to moving average processing, and FIG. 8(b) is a diagram showing the signal strength of the RF data of line L1 in FIG. 8(a). The horizontal axis in FIG. 8(b) indicates the depth position, which becomes deeper in the direction of the arrow. The vertical axis in FIG. 8(b) indicates the signal strength, and the signal strength increases in the direction of the arrow.

Note that in this embodiment, the stronger the signal strength, the darker the gray level, and the weaker the signal strength, the darker the gray scale becomes. Furthermore, in this embodiment, in order to detect a downward peak, that is, a position where black is the darkest, the black portion on L1 in FIG. 8(a) is indicated by P1 to P5. These P1 to P5 are also shown in FIG. 8(b). Further, in FIG. 8(b), an upward peak between P2 and P3 is shown as P10.

(d. First-order differential processing unit 34)
The first-order differential processing unit 34 performs first-order differential processing on the data that has been subjected to the difference processing in order to detect a downward peak. The first-order differential processing unit 34 calculates the difference between the signal strength at a predetermined depth position and the signal strength at the next depth position.
FIG. 9 is an enlarged view of the area between P10 and P3 in FIG. 8(b). FIG. 10 is a diagram showing a table 150 of the signal strength of the graph of FIG. 9 and the results of first-order differential processing. As will be described later, FIG. 10 also shows the results of the chattering process and a graph 151.

The leftmost column of table 150 shown in FIG. 10 shows sequence numbers. As the sequence number increases, the position becomes deeper. 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 first-order differential processing unit 34.
The difference in sequence number n is the value obtained by subtracting the signal strength of sequence number n from the signal strength of sequence number n+1. For example, the difference for sequence number 7 is the value (-15) obtained by subtracting the seventh signal strength (432) from the eighth signal strength (416).
In this way, the first-order differential processing section 34 performs first-order differential processing on all data of one line.

(e. Chattering removal section 35)
The chattering removal unit 35 performs chattering removal processing on the result of the first-order differential processing.

In the data shown in FIG. 9, although the signal strength data decreases as a whole in region R1, data D2 is larger than the previous (shallow) data D1, and chattering due to noise occurs. I know what you're doing. Furthermore, in region R2, data D4 and D5 are smaller than data D3, indicating that chattering due to noise has occurred. Such chattering occurs because reflected waves change depending on the material and particle size of aggregate contained in concrete. The chattering removal unit 35 removes such chattering.

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

Here, FIG. 10 shows a graph 151 of the hatched portion of the table 150. In the data indicated by ◆, which indicates a change (+/-), only sequence number 11 shows a positive (+) change despite the surrounding negative (-) changes, and chattering due to noise occurs in sequence number 11. I know what you're doing. The difference and change (+/-) values of this sequence number 11 correspond to data between D1 and D2 in FIG.

Further, sequence numbers 34 and 35 show positive (+) changes despite negative (-) changes in the surroundings, and it can be seen that chattering due to noise occurs in sequence numbers 34 and 35. The difference and change (+/-) values of this sequence number 34 correspond to the changes between data D3 and D4 in FIG. This corresponds to a change between data D4 and D5.

The chattering removal unit 35 performs chattering removal processing on the above change (+/-) value. The rightmost column of Table 1 shows the change (+/-) value after noise removal by chattering removal processing. The chattering removal unit 35 determines a positive (+) change when all three consecutive values are greater than 0, and determines a negative (-) change when all three consecutive values are less than 0. However, all other values retain their previous values.

To explain in detail, the chattering removal unit 35 detects when the nth change (+/-), the n+1st change (+/-), and the n+2nd change (+/-) of the sequence number are all positive values (1). In this case, the nth change (+/-) is determined to be a positive value (1). In addition, the chattering removal unit 35 detects the case where the nth change (+/-), the n+1st change (+/-), and the n+2nd change (+/-) of the sequence number are all negative values (-1). In this case, the nth change (+/-) is determined to be a negative value (-1). If the sign of the nth change (+/-), the n+1st change (+/-), and the n+2nd change (+/-) of the sequence numbers do not match, the chattering removal unit 35 removes the n-1st change. Hold (+/-).

For example, the value of the 6th change (+/-) is -1, the value of the 7th change (+/-) is -1, and the value of the 8th change (+/-) is -1. It is. Therefore, the chattering removal unit 35 sets the value of the change (+/-) after the sixth chattering process to -1.
On the other hand, the value of the 11th change (+/-) where chattering occurred is 1, the value of the 12th change (+/-) that follows it is -1, and the value of the 13th change (+/-) is -1. ) is -1. Therefore, the chattering removal unit 35 holds -1, which is the value of the change (+/-) after the 10th chattering process, as the value of the 11th change (+/-).

Also, the value of the 34th change (+/-) where chattering occurred is 1, the value of the next 35th change (+/-) is 1, and the value of the 36th change (+/-) is 1. The value of is -1. Therefore, the chattering removal unit 35 holds -1, which is the value of the 33rd change (+/-) after the chattering process, as the value of the 34th change (+/-).
Also, the value of the 35th change (+/-) where chattering occurred is 1, the value of the 36th change (+/-) after that is -1, and the value of the 37th change (+/-) is 1. ) has a value of 1. Therefore, the chattering removal unit 35 holds -1, which is the value of the 34th change (+/-) after the chattering process, as the value of the 35th change (+/-).

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

(f. Peak detection section)
The peak detection unit 36 detects the peak of one line of RF data after performing chattering removal processing. In this 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 the point at which the change after the chattering removal process changes from a negative change to a positive change as a peak. Specifically, as shown in Table T1 in FIG. 10, the change in sequence number 36 after chattering removal processing is a negative (-) change, and the change in sequence number 37 after chattering removal processing is positive ( +), the peak detection unit 36 detects that the signal intensity has 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 determination section 24 includes a grouping section 51, a chattering removal section 52, a shape determination section 53, and a signal strength determination section 54. The grouping unit 51 detects, as a group, peaks that are continuous with respect to the moving distance from among the plurality of peaks detected by the peak detection unit 36. The chattering removal unit 52 removes group chattering. The shape determining unit 53 determines the presence or absence of a buried object based on whether the group has a mountain shape, and when it is determined that a buried object exists, detects the peak of the depth position in the group, and determines whether the buried object is present or not. position. When the shape of a mountain is not determined, the signal strength determining unit 54 determines whether there is a buried object based on the signal strength of the group.

(a. Grouping section 51)
The grouping section 51 groups the peak detection results by the peak detection section 36. The grouping unit 51 sequentially checks whether there is a peak detection result starting 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. 11 is a diagram showing image data after preprocessing by the preprocessing section 23. As shown in FIG. In FIG. 11, the line L2 acquired this time is shown. FIGS. 12(a) to 12(d) are diagrams for explaining the processing by the grouping unit 51.

The grouping unit 51 determines whether or not there is a peak of the next line within 5 pixels in the moving direction B and within 5 pixels above and below, starting from the position QS of the first peak found (indicated by ● in FIG. 11). confirm. Note that the line where the peak position Q is found is defined as the current line.
FIG. 12(a) shows a state in which the peak position QS has been found. FIG. 12B shows a case where the next peak position Q2 is within 5 pixels in the movement direction B and within 5 pixels above the peak position QS of the current line. In FIG. 12(b), the peak position is rising (moving to the shallow side) in the movement direction. FIG. 12C shows a case where the peak position Q2 of the next line is within 5 pixels in the moving direction B and within 5 pixels below the peak position QS of the current line. In FIG. 12(c), the peak position is descending (moving toward the deeper side) in the movement direction.

Next, with the line where the peak position Q2 exists as the current line, it is checked whether a peak of the next line exists within 5 pixels in the movement direction B and within 5 pixels above and below the peak position Q2. In this way, each time line RF data is received, the current line is shifted in the moving direction to check the continuity of the peak.
As shown in FIG. 12(d), if the peak of the next line does not exist within 5 pixels in the moving direction B and within 5 pixels above and below the position Q3 of the peak of the current line, the peak position 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. In FIG. 11, a group (for example, group G1) is shown in which a black circle and a black square are connected by a line.

(b. Chattering removal section 52)
Next, the chattering removal section 52 will be explained. The shape of the group is determined by the shape determining section 53, which will be described later, but before that, chattering is removed. FIG. 13 is a diagram showing the positions of a plurality of grouped peaks. In FIG. 13, if the peak position Qs, which is the starting point, is the first (No. 1) in the moving rear B, the fifth (No. 5) peak position is It can be seen that Q5 has moved downward (in a deeper direction) than the fourth (No. 4) peak position Q4, indicating chattering. Such chattering is removed by the chattering removal section 52.

FIG. 14 shows No. 1 shown in FIG. 1~No. FIG. 3 is a diagram showing changes in the positions of up to 15 adjacent peaks. FIG. 14 shows a change from the position of the nth peak to the position of the (n+1)th peak. When the (n+1)th position is located above (shallower side) than the nth position, the difference from the next position is defined as a positive (+) change (positional change in the surface direction C). Furthermore, if the n+1-th position is located below (deeper side) than the n-th position, the difference from the next point is taken as a negative (-) change (positional 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, as shown in FIG. 13, the position of the third peak is shallower than the position of the second peak. The change from the 3rd to the 3rd 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 7th and 8th positions, the change between the 4th and 5th positions is negative due to chattering.

If the n~n+1st changes, the n+1~n+2nd changes, and the n+2~n+3rd changes are all positive (+) changes, the chattering removal unit 52 converts the n~n+1st changes into positive (+) changes. I judge that. Furthermore, when the n to n+1st changes, the n+1 to n+2nd changes, and the n+2 to n+3rd changes are all negative (+) changes, the chattering removal unit 52 converts the n to n+1th changes into negative (+) changes. +). If the n-th to n+1-th changes, the n+1-n+2-th changes, and the n+2-n+3-th changes do not match in sign, the chattering removal unit 52 converts the n-1 to n-th changes after the chattering removal process into the n-th changes. This is retained as the change after the n+1st 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 removal unit 52 removes the first to second changes as shown in Table 153. Judge the change as positive (+).
On the other hand, in the chattering removal unit 52, the second to third changes are positive (+), the third to fourth changes are positive (+), and the fourth to fifth changes are negative (-). , the positive (+) values of the first and second changes after the chattering removal process are maintained for the second and third changes after the chattering removal process.

In addition, the chattering removal unit 52 detects that the 4th to 5th changes are negative (-), the 5th to 6th changes are positive (+), and the 6th to 7th changes are positive (+). , the fourth to fifth changes are kept positive (+), which are the changes after the third to fourth chattering removal processing. In this way, the chattering that occurred at the fifth point can be removed.
In addition, since the 11th to 12th changes, the 12th to 13th changes, and the 13th to 14th changes are all positive (-), the chattering removal unit 52 treats the 11th to 12th changes as negative (-). to decide.

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

As shown in FIG. 15, the first condition is that the movement is upward (shallow) by 5 pixels or more in the moving direction A, and the second condition is that the movement is upward (shallow) by 5 pixels or more in the moving direction A. As mentioned above, it is descending in the downward direction (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 determination unit 53 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 determining unit 53 does not determine that a buried object exists.
Further, the shape determining unit 53 also detects an upward peak in the position of the group when determining the first to third conditions.
The shape determining unit 53 determines the shallowest position as the apex of the group and stores the position.
The shape determination unit 53 determines the point where the change in position changes from increase to decrease as the apex of the group. For example, in Figure 14, the change from the 7th to the 8th is positive (+), and the change from the 8th to the 9th is negative (-), so as shown in Figure 13, the 8th position is the peak. It is determined that It is detected that a buried object exists at the position of this peak.

(d. Signal strength determination unit 54)
Due to differences in the shape and material of the buried object, the shape of the mountain in the image data, especially near the apex, may become flat, so the conditions for determining it as a mountain shape (first condition, second condition, third condition) may not apply. For example, as shown in FIG. 16, when a plate-shaped wood 202 is scanned through a gypsum board 201, the vertices become flat as shown in R3 of the image data in FIG. 17. That is, as shown in the schematic diagram of image data in FIG. 18, the first condition and the second condition are satisfied, but the third condition is not satisfied because the vertical width is 7 pixels.

Therefore, if 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 a buried object based on the signal strength.
The signal strength determination unit 54 checks the strength (AD value) of all reception strengths in the group. Note that in this embodiment, when black appears deep, the AD value is set to a small value (in the negative direction).
Then, when all the grouped AD values are smaller than a predetermined threshold value, that is, when the black color appears darker than the threshold value, it is determined that a buried object exists.

(1-3-3. Judgment result registration unit 25)
The determination result registration unit 25 registers the results (group, peak position, etc.) 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 indicates groups, peak positions, etc. on the data image and causes the display unit 8 to display the data image. FIG. 19 is a diagram showing an image displayed on the display section 8. As shown in FIG. In FIG. 19, the vertical axis indicates the depth direction, and the horizontal axis indicates the moving distance. Also, groups are shown as lines, the starting point of the group is shown as a black triangle, and the ending point is shown as a black square. Furthermore, the peaks detected by the shape determining section 53 are indicated by x marks.

The operator can check this image and recognize that the buried object is buried at the peak position. Note that peak pk1 shown in FIG. 19 indicates the position of buried object 101a shown in FIG. 1, peak pk2 indicates the position of buried object 101b, peak pk3 indicates the position of buried object 101c, and peak pk4 indicates the position of buried object 101d. Indicates the location of

<2. Operation>
Next, the operation of the buried object detection device 1 according to the embodiment of the present invention will be explained.
(2-1. Impulse control module processing)
FIG. 20 is a flow diagram showing the processing of the impulse control module 5.
When impulse control module processing is started, an input is received from the encoder 7 in step S1, and impulse output control is started in step S2. For example, pulses of electromagnetic waves are output at a frequency of 1 MHz).

Next, in step S3, the delay section 14 sets a delay time in DelayIC. For example, the delay time can be set in 10 psec units from 0 to 5120 psec.
Next, in step S4, the control unit 10 performs AD conversion on the RF data received from the receiving antenna 12 via the gate unit 15.

Next, in step S5, it is determined whether 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.

Then, in step S7, 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 data for the next line is acquired. It is sent to the main control module 6.

(2-2. Main control module processing)
FIG. 21 is a flow diagram 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, the preprocessing unit 23 performs preprocessing before determining a buried object in step S12.
Next, in step S13, buried object determination processing is performed by the buried object determination section 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 explained in detail.

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

Next, in step S24, the first-order differentiation processing unit 34 performs first-order differentiation processing on the difference result subjected to the moving average processing, and determines whether the difference between adjacent data in the depth direction is positive (increase) or negative (decrease). Make a judgment.
Next, in step S25, the chattering removal unit 35 performs chattering removal processing on the data after the first-order differential processing.

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

(a. Gain adjustment processing)
Next, the gain adjustment process in step S21 in FIG. 22 will be explained. FIG. 23 is a flow diagram showing gain adjustment processing.
When the gain adjustment process is started, in step S31, the gain adjustment section 31 selects the received data with sequence number 1 from among the RF data received by the reception section 21.
After the gain adjustment 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 the sequence number is the maximum value. If the sequence number is not the maximum value, control returns to step S31, the sequence number is incremented by one, and the received data with sequence number 2 is selected. Then, the process of step S32 is performed on the data with sequence number 2.

In this way, the process of step S32 is repeated until all data for one line is processed.
In step S32, the signal strength data of each sequence number is multiplied by a predetermined multiplier.

For example, the sequence No. with the shortest delay time for one line of RF data. 1 (which can also be said to be the data at the shallowest position) is multiplied by a predetermined magnification to obtain sequence No. Sequence No. 1 has the next shortest delay time. 2 is multiplied by a predetermined multiplier, and the predetermined multiplier is multiplied in order of sequence number until the sequence number reaches the maximum. Specifically, the magnification is increased in the depth direction, with the magnification being 1x for data from 1 to 25 pixels from the shallow side, and 2x for data from 26 to 50 pixels from the shallow side. , for data of 51 to 75 pixels, the magnification can be set to 3 times, and the magnification can be increased in order, and for data of 500 to 511 pixels, the magnification can be set to 21 times.
By this gain adjustment processing, brightness and darkness can be made clear as in the image data shown in FIG. 6(b).

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

In this way, the flow is repeated until the processes of steps S42 and S43 are performed on all 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 a reference point value, and calculates the difference between that value and the received data of the current line.

Next, in step S44, the difference processing unit 32 determines whether 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. Then, the received data with sequence number 2 is selected.
In this way, the numbers are sequentially incremented and steps S42 and S43 are repeated until the difference processing is performed on all the received data of one line.

Note that when performing differential processing on the data of the m-th line, the average value of the signal intensities at the 1st to m-1th predetermined depth positions is subtracted from the signal strength at the predetermined depth positions of the m-th line. . Furthermore, when performing differential processing on the next (m+1)th line, the average value of the 1st to mth signal intensities is calculated, and the value of the reference point is updated.
Through this difference processing, changes in the RF data can be extracted as in the image data shown in FIG. 7(b).

(c. First-order differential processing of difference results)
Next, the first-order differential processing of the difference result in step S23 of FIG. 22 will be explained. FIG. 25 is a flow diagram showing the first-order differential processing of the difference result.
When the first-order differential processing of the difference results is started, in step S51, the first-order differential processing unit 34 selects the difference result with sequence number 1 from among the difference results.

Next, in step S52, the first-order differential processing section 34 performs first-order differential processing on 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 sequence number 1 and the next sequence number 2 is calculated.
Next, in step S53, it is determined whether the sequence number is the maximum value, and if the sequence number is not the maximum value, control returns to step S51, the number is incremented by one, and sequence number 2 is received. 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 step S52 is repeated until the first-order differential processing is performed on all data for one line.
In other words, when performing first-order differential processing on sequence number n, the first-order differential processing is performed on the data of sequence number n by subtracting the data of the difference result of sequence number n from the data of the difference result of sequence number n+1. It can be carried out.
As a result, the difference in the fourth column from the left of table 150 in FIG. 10 is calculated.

(d. Chattering removal processing)
Next, the chattering removal process in step S24 of FIG. 22 will be explained. FIG. 26 is a flow diagram showing chattering removal processing.
When the chattering removal process is started, in step S61, the chattering removal unit 35 selects sequence number 1 on which the first-order differential process has been performed.

Then, after the chattering removal unit 35 performs any of the controls in steps S62 to S66 for the data of sequence number 1, the control proceeds to step S67.
In step S67, it is determined whether the sequence number is the maximum value, and if the sequence number is not the maximum value, control returns to step S61, the number is incremented by one, and the received data with sequence number 2 is selected. be done.

In this way, the numbers are incremented one after another and one of steps S62 to S66 is repeated until the chattering removal unit 35 processes all of the data for 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 removal unit 35 determines whether all three consecutive first-order differential results are greater than zero. Since sequence number n has been selected, if the first-order differential results of sequence numbers n, n+1, and n+2 are all 0 or more, in step S63, the chattering removal unit 35 calculates the first-order differential after chattering removal processing for sequence number n. Store the result as positive (+).

On the other hand, in step S62, if even one of the first-order differential results of three consecutive sequence numbers is less than or equal to 0, in step S64, the chattering removal unit 35 determines that all three consecutive first-order differential results are smaller than 0. Determine whether or not. Since sequence number n has been selected, if the first-order differential results of sequence numbers n, n+1, and n+2 are all smaller than 0, in step S65, the chattering removal unit 35 performs the first-order differentiation after chattering removal processing for sequence number n. Store the differential result as negative (-).

Further, in step S63, if any one of the three consecutive first-order differential results is greater than 0, the chattering removal unit 35 advances the control to step S66.
Then, in step S66, the chattering removal unit 35 stores the previous sequence number state as the current sequence number state. Since sequence number n has been selected, the chattering removal unit 35 uses the positive (+) or negative (-) result after chattering removal processing stored for sequence number n-1 as the result after chattering removal processing for sequence number n. memorize it as a result.
This makes it possible to obtain the change after the chattering process on the rightmost side of the table 150 in FIG.

(e. Peak detection processing)
Next, the peak detection process in step S25 in FIG. 22 will be explained. FIG. 27 is a flow diagram showing the peak detection process.

When the peak detection process is started, in step S71, the peak detection unit 36 selects sequence number 1 on which the chattering removal process has been performed.
Then, the peak detection unit 36 performs control in 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 the sequence number is the maximum value. If the sequence number is not the maximum value, control returns to step S71, the sequence number is incremented by one, and the received data with 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 processes of steps S72 and S73 are repeated until the chattering removal unit 35 processes all of the data for one line.
Here, steps S72 to S73 will be explained assuming that the peak detection process is performed on the n-th data.

In step S72, the peak detection unit 36 determines whether the previous sequence number n-1 after chattering removal is negative (-) and the current sequence number n is positive (+). .
Then, 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 detection unit 36 stores the n-th coordinate in step S73. do. The coordinates can be expressed, for example, in units of pixels and in terms of moving distance (which can also be called a line number) and depth position.
As a result, as described above, for example, sequence number 37 in table 150 of FIG. 10 can be detected as a peak.

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

Next, in step S82, the chattering removal unit 52 performs chattering removal processing on the grouped groups.
Next, in step S83, the shape determining section 53 or the signal strength determining section 54 performs buried object determination processing.
Next, in step S84, the display control unit 26 marks the position of the peak detected by the shape determining unit 53 with an x mark and causes the display unit 8 to display the mark.

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

First, in step S91, the grouping unit 51 sets the detection state to "undetected".
Targeting all data acquired in the past, in step S92, the grouping unit 51 selects old data in the past as a target for processing. Then, in step S103, the grouping unit 51 determines whether all of the data acquired in the past up to the currently acquired line has been processed, and if the process has not been performed, control returns to step S92 and the next Old data is subject to processing. In this way, for example, the processes from step S93 to step S102 are performed in order from sequence number 1 of the oldest line.

In step S93, the grouping unit 51 determines whether the state is undetected. Since the initial state is "undetected", control proceeds to step S94.
In step S94, the grouping unit 51 determines whether there is a position where a peak is detected within a predetermined range. If no peak is detected within the predetermined range, control proceeds to step S103. The predetermined range can be set as appropriate; for example, it may be set to one line, or may be set to the sequence number of one line.

In this way, in step S94, it is determined whether there is a position where a peak has been detected in order from the oldest data, and if there is a position where a peak has been detected, in step S95, the grouping unit 51 Set the detection status to "detecting".
Next, in step S96, the grouping unit 51 stores the point where the peak was detected. This point is a coordinate in units of pixels, and can be indicated by, for example, a moving distance (which can also be called a line number) and a depth position. Note that this point corresponds to the starting point (●) in FIGS. 11 and 19.

Next, through step 103 and step S92, the next data is targeted for processing.
Next, in step S93, since the detection state is "detecting", control proceeds to step S97.
In step S97, the grouping unit 51 determines whether there is a position where a peak was detected within a predetermined range from the position stored in step S96. This predetermined range can be set, for example, within 5 pixels in the movement direction described in FIGS. 12(a) to 12(d), and within 5 pixels above and below. If the position where the peak was detected is within the predetermined range, in step S98, the grouping unit 51 stores the position as a continuous position.

Next, in step S99, the grouping unit 51 compares the previous Y coordinate (depth position) and 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, a positive (+) value is stored, indicating that the depth position is rising. Furthermore, if the current depth position is deeper than the previous depth position, a negative (-) is stored, indicating that the depth position is descending.

Next, through step S97 and step S92, the next data is targeted for processing.
Next, in step S93, since the detection state is "detecting", control proceeds to step S97.
In this step S97, it is detected whether or not there is a point at which a peak was detected within a predetermined range from the point previously stored in step S98, and if it exists, that point is stored in step S99. . Then, in step S100, the previous points and comparison results are stored. As a result, consecutive points are grouped in sequence as shown in FIG. 14, and whether the change to the next point is an increase or decrease is also stored.

Then, in step S97, if no peak is detected within the predetermined range, control proceeds to step S101.
In step S101, the grouping unit 51 determines that there are no consecutive points, and stores the detection results up to that point. Note that the last detected point corresponds to the end point (■) in FIGS. 11 and 19.
Next, in step S102, the grouping unit 51 sets the detection state to "undetected".
Then, in step S103, when it is determined that all data of the lines acquired in the past have been processed, the process ends.

(b. Chattering removal process)
The chattering removal process in step S82 in FIG. 28 will be explained. FIG. 30 is a flow diagram showing chattering removal processing.

The chattering removal process is performed on all data as a result of grouping.
When the chattering removal process is started, in step S111, the chattering removal unit 52 selects data in order from the starting point side of the grouped data. For example, in step S111, the chattering removal unit 52 processes the data of the change from the first to the second shown in FIG.

Next, in step S112, the chattering removal unit 52 reads out the comparison results 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 removal unit 52 determines whether all three consecutive comparison results are greater than zero. In the data shown in Table 152 of 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 greater than 0, the chattering removal unit 52 As shown in Table 153 of FIG. 14, the state of change from the first to the second after chattering is removed is positive (+) (it can be said that it is rising in a shallow direction).

Next, in step S113, the chattering removal unit 52 determines whether or not processing has been performed on all data as a result of grouping. If the processing has not been completed, control returns to step S111, and The data of the change from the 3rd to the 3rd is selected as the processing target.
In this way, processing is performed on changes in all grouped data.

In step S113, if any one of the three consecutive comparison results is less than or equal to 0, the control proceeds to step S115, and the chattering removal unit 52 determines whether all three consecutive comparison results are smaller than 0 or not. Determine whether When processing is performed from the 11th to the 12th, in table 152 of FIG. 14, the changes from the 11th to the 12th, from the 12th to the 13th, and from the 13th to the 14th are all Since it is smaller than 0, the chattering removal unit 52 sets the state of change from the 11th to the 12th after chattering removal to a negative (-) (if it is descending in the deep direction), as shown in Table 153 of FIG. ).

On the other hand, in step S115, if any one of the three consecutive comparison results is 0 or more, control proceeds to step S117.
In step S117, the chattering removal unit 52 sets the state after chattering removal to the previous state. For example, when processing changes from the 4th to the 5th, in Figure 14, the change from the 4th to the 5th is negative (-), and the change from the 5th to the 6th is positive (+). , and the change from the 6th to the 7th is positive (+). Therefore, the state of the fourth to fifth change is positive (+), which is the state after the previous third to fourth chattering processing, as shown in Table 153 of FIG.

In this way, the chattering removal unit 52 removes the n to n+1 changes when the n to n+1 changes, the n+1 to n+2 changes, and the n+2 to n+3 changes are all positive (+) changes. Judged as positive (+). Furthermore, when the n to n+1st changes, the n+1 to n+2nd changes, and the n+2 to n+3rd changes are all negative (+) changes, the chattering removal unit 52 converts the n to n+1th changes into negative (+) changes. +). The chattering removal unit 52 retains the n-1 to n-th changes when the n-th to n+1-th changes, the n+1-n+2-th changes, and the n+2-n+3-th changes do not match in sign.

Then, in step S118, when it is determined that all grouped data have been processed, the process ends. If all data has not been processed, control returns to step S111 and the next data is selected.
Through the above processing, the table 153 after chattering removal shown in FIG. 14 is obtained.

(c. Buried object determination processing)
The buried object determination process in step S83 in FIG. 28 will be explained. FIG. 31 is a flow diagram showing buried object determination processing.
The buried object determination process is performed on all data as a result of grouping.
When the buried object determination process is started, in step S121, the shape determination unit 53 selects data in order from the starting point side of the grouped data. For example, in step S121, the shape determining unit 53 processes the data after chattering removal of the change from the first to the second shown in FIG.

In step S122, the shape determination unit 53 reads the result after the chattering removal process of the change from the first to the second.
In step S123, the shape determining unit 53 determines whether the result of the change after the chattering removal process is positive (+). For example, since the result after the chattering removal process 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 determining unit 53 sets a - (minus) count to 0.
Next, in step S125, the shape determining unit 53 determines whether the + (plus) count is 0 or not. Since the + (plus) count is 0, control proceeds to step S126.
In step S126, the shape determination unit 53 stores the first Y coordinate (depth position) and sets the starting 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 data as a result of the grouping. If the processing has not been completed, the control returns to step S121 and the next The data (change from second to third) is selected for processing.

Then, in step S122, the shape determination unit 53 reads the result after the chattering removal process of the change from the second to the third.
Next, in step S123, the shape determining unit 53 determines whether the result of the change after the chattering removal process is positive (+). For example, since the result after the chattering removal process 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 the + (plus) count is 0 or not. Since the + (plus) count is +1, control proceeds to step S127.
Then, in step S127, the shape determining unit 53 adds +1 to the + (plus) count and sets it to +2.

In this way, steps S121 to S127 and step S138 are repeated. Then, in step S123, if the result of the change after the chattering removal process becomes negative (-), the control proceeds to step S128.
In step S128, the shape determining unit 53 determines whether the + count is 5 or more. Here, if the count is 5 or more, it means that condition 1 is satisfied, that is, the number of pixels is continuously increased by 5 pixels or more in the Y-axis direction.

In the data shown in FIGS. 13 and 14, for example, the result after chattering removal processing of the change from the 8th to the 9th is negative (-), and there are 7 positive (+) by that time, so The + count is 7. Therefore, control proceeds to step S129.
In step S129, the shape determining unit 53 determines whether the - (minus) count is 0 or not. Since the - (minus) count is 0, control proceeds to step S130.

In step S130, the shape determination unit 53 stores the previous depth position (also referred to as Y coordinate). That is, the shape determining unit 534 stores the Y coordinate of the top of the mountain (the point where the slope changes from + to -). In the data of FIGS. 13 and 14, the Y coordinate of the 8th point, which is the previous point in the change from the 8th to the 9th point, is stored.
Next, in step S131, the shape determining unit 53 adds +1 to the - (minus) count.

Next, in step S132, the shape determining unit 53 determines whether the - (minus) count is 5 or more. Here, if the count is 5 or more, it means that condition 2 is satisfied, that is, the number of pixels is continuously lowered by 5 pixels or more in the Y-axis direction. In the case of a change from the 8th to the 9th, the -count is +1, so the control proceeds to step S138, and via step S121, the result after the chattering process of the change from the 9th to the 10th is processed. Selected as a target.

In this way, the results are selected one after another, and when the result after the chattering process of the change from the 12th to the 13th is selected as the processing target, the - (minus) count in step S132 becomes +5 or more. Control proceeds to step S133.
In step S133, the shape determination unit 53 calculates the difference between the Y coordinate of the starting point and the Y coordinate of the vertex. In the data of FIGS. 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, if it is 10 or more, Condition 3 that the difference in the Y-axis direction is 10 pixels or more is satisfied.
If the calculated difference is 10 or more, in step S135, the shape determination unit 53 determines that the group is in the shape of a mountain, and determines that a buried object exists.

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

(d. Buried object determination process 2)
Next, buried object determination processing 2 in step S136 in FIG. 31 will be described. FIG. 32 is a flowchart showing buried object determination processing 2.
Buried object determination processing 2 is performed on all data as a result of grouping.
When buried object determination processing 2 is started, in step S141, the signal strength determination unit 54 selects data in order from the starting 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 (reception strength/AD value) of the first received data.

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

Then, the processes of steps S142 and S143 are performed on the second selected data. In this way, the determination is performed on all grouped data, and if the signal strength of all the data is smaller than the predetermined value, the signal strength determination unit 54 determines that a buried object exists in step S145. On the other hand, if even 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 a buried object, and the control ends.

In step S84 of FIG. 28, in the case of the examples shown in FIGS. 23 and 14, the display control unit 26 displays the image on the display unit 8 with an x mark placed at the position of the eighth data, which is the vertex ( (See Figure 19).
[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 changes can be made without departing from the gist of the invention.

(A)
In the above embodiment, the method of controlling the buried object detection device 1 and the main control module 6 (an example of a data processing device) has been explained using an example in which the control method is performed according to 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 for the buried object detection device 1 and the main control module 6 (an example of a data processing device), which is carried out according to the flowcharts shown in FIGS. 20 to 32. .

Further, one usage form of the program may be a mode in which the program is recorded on a computer-readable recording medium such as a ROM, and operates in cooperation with the computer.
Further, one usage form of the program may be a mode in which the program is transmitted through a transmission medium such as the Internet, or a transmission medium such as light, radio waves, or sound waves, is read by a computer, and operates in cooperation with the computer.
Further, the above-mentioned computer is not limited to hardware such as a CPU (Central Processing Unit), but may include firmware, an OS, and further peripheral devices.
Note that, as explained above, the method for controlling the power consumption body may be realized in software or hardware.

(B)
In the above embodiment, reinforcing bars were used as an example of the buried object, but it is not limited to reinforcing bars, and may be gas pipes, water pipes, wood, etc. The target object is not limited to concrete.

(C)
In the embodiment described above, black is set to indicate buried objects through gradation processing, but the present invention is not limited to this, and white may be set to indicate buried objects.

(D)
In the chattering removal process (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. Further, in the chattering removal process (step S82) in the buried object determination process, three pieces of data are used as an example of the predetermined number, but the number is not limited to three.

(E)
In this embodiment, the main control module 6 is provided within the buried object detection device 1, but the main control module 6 may be provided separately from the buried object detection device 1. In this case, for example, the buried object detection device is provided with a main body 2, a handle 3, wheels 4, an impulse control module 5, an encoder 7, etc., and a main control module 6 and a display section on a tablet or 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 buried object detection device of the present invention can remove noise components even when there is a change in material around the buried object, and have the effect of being able to detect the buried object in real time. This is useful for detecting buried objects in concrete.

1: Buried object detection device 2: Main body 3: Handle 4: Wheel 5: Impulse control module 6: Main control module (an example of a data processing device)
7: Encoder 8: Display section 10: Control section 11: Transmitting antenna 12: Receiving antenna 13: Pulse generating section 14: Delay section 15: Gate section 21: Receiving section (an example of a receiving section)
22: RF data management unit 23: Pre-processing 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: First-order differential processing unit (an example of a difference calculation unit)
35: Chattering removal section 36: Peak detection section (an example of a signal strength peak detection section)
37: Sequence number 41: Increase/decrease determination section 43: Step 51: Grouping section (an example of a grouping section)
52: Chattering removal section (an example of a noise removal section)
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: Buried object 101a: Buried object 101b: Buried object 101c: Buried object 101d: Buried object 151: Graph 202: Wood 534: Shape determination section

Claims (7)

A data processing device for detecting a buried object within the object using data regarding reflected waves of electromagnetic waves emitted toward the object while moving on the surface of the object,
a receiving unit that receives data regarding reflected waves measured at each timing associated with movement;
a signal strength peak detection unit that detects a peak of the signal strength in the depth direction of the target object at each of the timings with respect to the signal strength of data of the reflected wave inside the target object received by the receiving unit ;
Among the depth positions in the depth direction at the peaks of the signal strength detected at each of the timings, the depth positions at a plurality of peaks of the signal strength that are continuous within a predetermined interval in the moving direction are 1 a grouping section for forming two groups;
Noise included in the waveform of the group is removed based on whether the continuity of the upward trend or downward trend of the peaks in the moving direction is impaired as a change in the depth position of the plurality of peaks in the group. a noise removal unit that performs
a buried object detection unit that detects the presence or absence of the buried object based on the group from which the noise has been removed;
The buried object detection section includes:
It is determined whether the group has a predetermined mountain shape in a plane in the movement direction and the depth direction, and if it is determined that the group has a predetermined mountain shape, it is determined that the buried object exists. , comprising a shape determining unit that determines that the buried object does not exist when it is determined that the buried object does not have the predetermined mountain shape;
Data processing equipment. The grouping unit is configured to detect, in the movement direction, a positional change in the depth position of the peak at the predetermined timing from the depth position of the peak of data acquired at a timing immediately before the predetermined timing. determines whether the position change is in the depth direction or in the surface direction,
The noise removal unit removes noise based on the direction of the position change at the depth position of a predetermined number of adjacent peaks.
The data processing device according to claim 1. The noise removal section includes:
When the directions of the position changes at the depth positions of the predetermined number of adjacent peaks including the depth position of the predetermined peak match, the direction of the matched position change is changed to the predetermined depth. Adopted as a result of the direction of position change after noise removal processing in position,
If the directions of position changes at the depth positions of the predetermined number of adjacent peaks do not match , the direction of position change at the depth position of the peak of data acquired at the timing immediately before the predetermined peak is employing the result of the direction of position change after the noise removal process as the result of the direction of position change after the noise removal process at the depth position of the predetermined peak;
The data processing device according to claim 2. The shape determining section is
a first condition in which the depth position of the peak of the signal intensity is continuously shallower by a predetermined amount or more along the movement direction;
a second condition in which the depth position of the peak of the signal intensity is continuously deeper by a predetermined amount or more along the movement direction;
determining that the group has a mountain-shaped waveform when all conditions of a third condition that the width of the depth position of the group is equal to or more than a predetermined amount are satisfied;
The data processing device according to any one of claims 1 to 3. The buried object detection section includes:
If the first condition and the second condition are satisfied, but the third condition is not satisfied, 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 4. The shape determination unit detects a peak at the depth position of the group determined to be mountain-shaped.
The data processing device according to any one of claims 1 to 5. The data processing device according to claim 6;
a display section capable of displaying the mountain-shaped group;
The first display section displays a peak at the detected position along with the mountain-shaped group.
Buried object detection device.

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