Apparatus, system and method for determining deterioration

Abstract

The purpose of this disclosure is to make it possible to use a quantitative indicator to inspect a hidden part covered by a cover, or the like, even when there is backlight.　Disclosed are a device and method for assessing the deterioration of a metal structure having recesses and protrusions, wherein an image is acquired that represents recesses and protrusions on the surface of the metal structure that have been measured using terahertz waves and the deterioration of the metal structure is assessed through the analysis of the acquired image.

Description

[Technical field]

[0001] The present disclosure relates to an apparatus, system and method for determining degradation. [Background technology]

[0002] To provide communication services, outdoor facilities such as utility poles are installed, and their inspection is extremely important. Among these, the suspension wire and the support wire support the load of the cable to prevent breakage, and to support the tension so that the utility pole does not become unbalanced. Suspension wires are made of multiple steel wires twisted together (seven or so), and the surface is plated with zinc or other materials. Therefore, they are highly weather-resistant, but if they are installed outdoors for a long period of time, corrosion will progress and they will deteriorate. If this breaks, the cable will be severed, affecting communication services and causing secondary damage due to unbalanced loads on utility poles. Therefore, inspection of these is extremely important.

[0003] In the past, inspection of suspension and support wires was carried out visually by on-site workers, but in recent years, the method has been made more efficient by using images. When inspecting using images, the color is mainly used to judge the condition in relation to the current inspection indicators. There has been prior research into methods for viewing rust corrosion using images. [Prior art documents] [Non-patent literature]

[0004] [Non-Patent Document 1] V. Bondada, DK Pratihar, and CS Kumar, “Detection and quantitative assessment of corrosion on pipelines through image analysis,” Procedia Computer Science, vol. 133, pp. 804-811, 2018. [Non-Patent Document 2] C. Galamhos, J. Matas, and J. Kittler, “Progressive probabilistic Hough transform for line detection”, in Proc. Conf. Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 554-560, 1999. Summary of the Invention [Problem to be solved by the invention]

[0005] Conventional image-based assessment methods had the problem that they could not assess deterioration in backlit conditions, and could not assess invisible areas covered by covers, etc. Furthermore, there was a problem that the assessment method did not have a quantitative index, and the assessment results varied depending on the inspector. [Means for solving the problem]

[0006] The inventors have devised a deterioration determination method using an image captured by terahertz waves. Since the present disclosure uses an image captured by terahertz waves, it is possible to inspect invisible parts covered by a cover or the like even in backlighting. Furthermore, since the present disclosure is based on image analysis, it is possible to perform the determination using a quantitative index. Furthermore, since the present disclosure is a determination method that can obtain a certain determination result regardless of the presence or absence of a cover, it is possible to obtain a certain determination result using a quantitative index for invisible parts.

[0007] Specifically, the deterioration determination device and the deterioration determination method of the present disclosure include: A deterioration determination device for determining deterioration of a metal structure having a concave-convex structure, comprising: obtaining an image showing the unevenness of the surface of the metal structure measured using terahertz waves; The acquired images are analyzed to determine the deterioration of the metal structure.

[0008] Specifically, the deterioration determination system of the present disclosure includes: A deterioration determination device according to the present disclosure; A measuring unit for measuring unevenness on a surface of the metal structure; a mechanism for measuring unevenness on a surface of the metal structure by moving the measuring unit in a longitudinal direction of the metal structure and in a rotational direction perpendicular to the longitudinal direction; Equipped with The deterioration determining device determines the deterioration of the metal structure by using an image obtained from the data measured by the measuring unit.

[0009] The deterioration determination device of the present invention can also be realized by a computer and a program, and the program can be recorded on a recording medium or provided via a network. The program of the present disclosure is a program for realizing a computer as each functional unit of the deterioration determination device according to the present disclosure, and is a program for causing a computer to execute each step of the deterioration determination method executed by the deterioration determination device according to the present disclosure. Effect of the Invention

[0010] According to the present disclosure, it is possible to inspect invisible parts covered by a cover or the like using quantitative indicators, even in backlit conditions. [Brief description of the drawings]

[0011] [Figure 1] 2 is an example of a configuration of a deterioration determination system. [Diagram 2] 4 is an example of a flowchart of a measurement unit and a mechanism unit. [Diagram 3] 13 is an example of a flowchart of an image processing unit. [Figure 4] This is an example of image processing. [Diagram 5] This is an example of binarization and line detection. [Figure 6] 13 is an example of a flowchart of a determination processing unit. [Figure 7] 13 is an example of a determination process. [Figure 8] 3 is an example of a configuration of a mechanism section. [Figure 9]3 is an example of a configuration of a measurement unit. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, the embodiments of the present disclosure will be described in detail with reference to the drawings. Note that the present disclosure is not limited to the embodiments shown below. These implementation examples are merely illustrative, and the present disclosure can be implemented in various forms with various modifications and improvements based on the knowledge of those skilled in the art. Note that components with the same reference numerals in this specification and drawings are assumed to indicate the same components.

[0013] (First embodiment) Examples according to the present disclosure are described below. 1 shows the configuration of a deterioration determination system according to the present disclosure. The deterioration determination system according to the present disclosure includes a measurement unit 21, a mechanism unit 22, an image processing unit 23, a determination processing unit 24, and a display unit 25. The image processing unit 23 and the determination processing unit 24 function as the deterioration determination device according to the present disclosure, and can be realized by a computer and a program, and the program can be recorded on a recording medium or provided via a network.

[0014] The measuring unit 21 measures the measurement object using terahertz waves. The mechanical unit 22 changes the relative position of the measuring unit 21 with respect to the measurement object, and performs planar measurement of the measurement object. In this manner, in the present disclosure, the measuring unit 21 and the mechanical unit 22 work together to perform planar measurement of the measurement object using terahertz waves, and an image showing the unevenness of the surface of the measurement object is obtained. The image processing unit 23 analyzes the image obtained by the measuring unit 21 and the mechanical unit 22. The determination processing unit 24 determines the deterioration of the measurement object based on the analysis result of the image processing unit 23. The display unit 25 displays the result of the determination by the determination processing unit 24 .

[0015] Here, the measurement target is a metal structure having an uneven structure. In the present disclosure, in order to image the uneven structure on the surface of such a metal structure, the uneven structure on the surface of the metal structure is measured using terahertz waves. As a result, in the present disclosure, it is possible to obtain an image showing the unevenness on the surface of the metal structure even in an invisible part covered by a cover or the like. Hereinafter, in this embodiment, an example will be shown in which the metal structure is a linear structure in which multiple metal wires such as suspension wires or support wires are twisted together.

[0016] Specifically, while the measuring unit 21 irradiates the surface of the metal structure with terahertz waves, the relative position between the measuring unit 21 and the measurement target is changed. For example, when the measurement target is a linear structure, the measuring unit 21 is translated in the longitudinal direction of the linear structure, and is translated in a direction perpendicular to the longitudinal direction. In the present disclosure, this translation direction is referred to as the parallel direction, and the direction perpendicular to the longitudinal direction is referred to as the rotation direction.

[0017] FIG. 2 is a flow chart for explaining the operations of the measurement unit 21 and the mechanism unit 22. The measurement unit 21 irradiates a measurement object with terahertz waves from a transmission unit (S11) and acquires electromagnetic waves with a reception unit (S12). Here, the electromagnetic waves acquired by the reception unit include any electromagnetic waves generated by irradiating the measurement object with terahertz waves. Then, the reflection intensity of the terahertz waves irradiated to the measurement object is calculated (S13). The mechanical unit 22 performs this series of measurements using the measuring unit 21 in a planar manner, and repeats this until the planar measurement is completed (S14). As a result, image data is obtained that represents the distribution of the reflection intensity of the terahertz wave obtained by the measuring unit 21. The finally obtained image data is processed by the image processing unit 23.

[0018] Here, the reflection intensity of the terahertz waves represents the unevenness of the surface of the measurement object. If the measurement object is a linear structure in which multiple metal wires are twisted together, the terahertz waves are reflected by the surface of each metal wire. Therefore, the image processing unit 23 detects straight lines using areas of the image with high reflection intensity. This allows the image processing unit 23 to detect straight lines corresponding to the metal wires of the linear structure.

[0019] Specifically, the image processing unit 23 performs processing as shown in the flowchart in Fig. 3. After the data obtained as a result of the planar measurement is normalized by the maximum value (S21), it is binarized using a binarization threshold value (S23). The threshold value in step S23 may be a single value or multiple values. When multiple values ​​are used, an initial binarization threshold value, a binarization threshold variation amount, and a maximum binarization threshold value are set (S22).

[0020] Here, in the planar measurement, when measuring the reflection intensity of the terahertz wave on the surface of the measurement target, the normalization in step S21 normalizes the shading of the image with the maximum value of the reflection intensity. Note that the normalization in step S21 is not limited to the maximum value of the reflection intensity, and can be performed with any value according to the data obtained as a result of the planar measurement.

[0021] The image processing unit 23 performs line detection using the binarized image (S24). Any algorithm can be used for line detection, but for example, a Progressive Probabilistic Hough Transform algorithm (for example, see Non-Patent Document 2. Hereinafter, referred to as a PPHT algorithm) can be used. Here, if multiple thresholds are set as in step S22, line detection is performed for each threshold (S25 and S26).

[0022] FIG. 4 shows an embodiment of the process described in FIG. 3. The original data shown in FIG. 4(a) is an example of an image acquired by the measurement unit 21. In this example, five measurement objects are measured by the measurement unit 21, with the horizontal direction indicating the parallel direction and the vertical direction indicating the rotation direction. In this disclosure, five samples, from the first sample to the fifth sample, are used as an example of the measurement objects. The original data D1A is the first sample that is not deteriorated and is close to new, and the original data D5A is the fifth sample that is in the most deteriorated state among the five samples, with the deterioration progressing as the number increases.

[0023] An example of binarization of original data D1A, D2A, D3A, D4A, and D5A with a certain threshold value based on the flow of Fig. 3 is shown in Fig. 4(b), which is images D1B, D2B, D3B, D4B, and D5B after binarization processing. An example of the result of further performing line detection processing is shown in Fig. 4(c), which is images D1C, D2C, D3C, D4C, and D5C after line detection.

[0024] FIG. 5 shows the result of an embodiment of the repeated processing when the binarization threshold is changed by steps S25 and S26 in the flow of FIG. 3. FIG. 5(a) corresponds to a part of the image D1B of FIG. 4, and FIG. 5(e) is an image obtained by performing line detection from the binarized image shown in FIG. 5(a). By changing the binarization threshold for the binarized image shown in FIG. 5(a), the binarized images shown in FIG. 5(b) to FIG. 5(d) are obtained. FIGS. 5(f) to 5(h) show images obtained by performing line detection from the binarized images shown in FIG. 5(b) to FIG. 5(d). In this way, the image processing unit 23 may perform repeated binarization and line detection processing while changing the binarization threshold for the measurement object.

[0025] FIG. 6 shows a flowchart of the judgment processing unit 24. When the measurement object is a linear structure in which multiple metal wires are twisted together, each metal wire is arranged at an inclination determined for each measurement object with respect to the longitudinal direction, i.e., the horizontal direction, of the linear structure. In this disclosure, therefore, the inclination of the straight line output by the image processing unit 23 is obtained (S31). In order to determine whether this inclination is due to the twisted structure of the measurement object, a range of inclination values ​​is set, and it is determined whether the inclination falls within that range (S32). Straight lines whose inclination falls within the set range are straight lines corresponding to metal wires, and are therefore regarded as correct.

[0026] As the deterioration of the metal wire progresses, the straight lines corresponding to the metal wire become less clear, as shown in Fig. 4(b) and Fig. 4(c). In this disclosure, therefore, straight lines corresponding to the metal wire are extracted from the image, and the number of extracted lines, i.e., the number of correct answers, is used to determine the deterioration of the measurement object. Specifically, the accuracy rate is defined and calculated as the ratio of the total number of detected straight lines to the number of correct answers (S33). Here, as shown in step S22 of Fig. 3, if there are multiple binarization thresholds, the accuracy rate is calculated for each threshold.

[0027] Next, the deterioration of the measurement target is judged based on the calculated binarization threshold and the matching rate. If the matching rate is less than an arbitrary threshold A (Yes in S34), it is judged that the deterioration has progressed significantly and that the equipment needs to be replaced immediately (S37). If the matching rate is equal to or greater than threshold A (Yes in S34), and the matching rate is equal to threshold B (Yes in S35) and the binarization threshold is equal to or greater than threshold C (Yes in S36), it can be judged that there is no deterioration and that there is no need to replace it (S38). Furthermore, if the matching rate does not reach threshold B (No in S35), or if the matching rate reaches threshold B but the binarization threshold does not exceed threshold C (No in S36), it can be judged that there is deterioration but that there is no need for urgent disclosure and that follow-up observation is required (S39).

[0028] Fig. 7 is an example showing the relationship between the binarization threshold and the precision rate, using the precision rate calculated in step S33 in Fig. 6. In this example, the five samples shown in Fig. 4 were used as an example. In the figure, Sample 1 indicates the first sample, Sample 2 indicates the second sample, Sample 3 indicates the third sample, Sample 4 indicates the fourth sample, and Sample 5 indicates the fifth sample.

[0029] As shown in Fig. 7, in the first sample, the matching rate is high when the binarization threshold is 0.4 and 0.7 or more. In contrast, in the fifth sample, the matching rate does not increase even if the binarization threshold is adjusted. Thus, as degradation progresses, a high matching rate cannot be detected even if the binarization threshold is adjusted.

[0030] Therefore, in the present disclosure, as shown in the flow of Fig. 6, the binarization threshold is adjusted, and deterioration of the measurement object is judged based on the relevance rate after the binarization threshold is adjusted. Here, the relevance rate threshold for judging deterioration of the measurement object can be determined for each measurement object by obtaining in advance the relationship as shown in Fig. 7 using a sample of the measurement object. For example, Fig. 6 shows an example in which there are two relevance rate thresholds, A and B, but this threshold can be set to any number for each measurement object.

[0031] For example, in the flow shown in FIG. 6, if the thresholds A, B, and C are numerically limited to 0.5, 0.9, and 0.6, then according to the judgment flow, in the embodiment of FIG. 7, it can be determined that the first sample is not degraded, the second, third, and fourth samples require further observation, and the fifth sample requires updating.

[0032] The following parameters were used to calculate the accuracy rate: PPHT algorithm threshold: 5~20 minLineLngth:5~20 maxLineGap:1~3

[0033] Here, the Threshold in the PPHT algorithm is the threshold required to consider something to be a straight line. The Hough transform in the PPHT algorithm counts the number of straight lines that pass through each point in the binarized image. If there is a straight line that crosses multiple points, the line will be counted as many times as there are points. In other words, the line with the greatest number of overlaps is judged to be a straight line in the image. The Threshold indicates the threshold value for this overlap count. Values ​​greater than the Threshold are detected as straight lines, and values ​​below the Threshold are not detected.

[0034] minLineLngth is a parameter that specifies the length (number of pixels) of a line to be detected. Lines smaller than this value will not be detected. maxLineGap is the maximum length allowed when two lines are considered to be one line. Two lines smaller than this value will be considered to be one line.

[0035] As described above, this embodiment enables automatic and quantitative judgment regardless of whether a cover is present or not, which is expected to improve the efficiency of inspection work and eliminate uncertainty in the diagnostic results obtained by inspectors.

[0036] Second Embodiment 8 shows an example of the configuration of the mechanical section 22. In this example, in order to measure a sample 14 of a suspension wire to be measured, the mechanical section 22 is provided with a moving stage 17 that moves the sample 14 parallel to the longitudinal direction of the suspension wire, and a rotating stage 16 that rotates the sample 14 perpendicular to the longitudinal direction of the suspension wire. The rotating stage 16 is fixed to the moving stage 17. The mechanical section 22 is provided with a control section 18 that controls the rotating stage 16 and the moving stage 17.

[0037] With sample 14 fixed to rotation stage 16, measurement unit 21 irradiates sample 14 with terahertz waves, thereby acquiring electromagnetic waves generated in sample 14. Control unit 18 rotates rotation stage 16, allowing measurement unit 21 to acquire electromagnetic waves reflected at different positions in the rotation direction of sample 14. Control unit 18 moves moving stage 17, allowing electromagnetic waves reflected at different positions in the parallel direction of sample 14 to be acquired. In this way, by moving the position at which the terahertz waves are irradiated, planar image data having widths in the parallel and rotational directions, as shown in FIG. 4, can be acquired.

[0038] As another embodiment, a method of performing planar scanning using a galvanometer mirror or the like can also be adopted.

[0039] In addition, in the present embodiment, an example has been described in which the mechanism unit 22 includes the rotation stage 16 that rotates the sample 14, but the present disclosure is not limited to this. For example, the rotation stage 16 may rotate a transmitting unit and a receiving unit included in the measurement unit 21. This makes it possible to obtain image data of any measurement target, such as a suspension wire and a support wire laid outdoors.

[0040] (Third embodiment) FIG. 9 shows an embodiment of the terahertz wave transmission / reception section in the measurement section 21. Here, a method is shown in which a femtosecond laser is used to generate terahertz waves and the waves are received using time-domain spectroscopy of terahertz waves. A femtosecond laser 1 emits a pulsed terahertz wave, and a laser beam splitter 2 branches the light into two. One branched light (probe light) is incident on the light receiving section 13 via mirrors 3, 5, 8, 9 and an optical delay mechanism 6. The other branched light (pump light) is emitted from the transmission section 4, reflected by the measurement object 12, and then received by the light receiving section 13. This allows the measurement section 21 to measure the reflection intensity at the measurement object 12.

[0041] The measuring unit 21 is not limited to the one in this embodiment, and any configuration capable of acquiring image data representing the unevenness of the surface of the measurement target as shown in FIG. 4 using terahertz waves can be adopted. [Industrial Applicability]

[0042] The present disclosure can be applied to the information and communications industry. [Explanation of symbols]

[0043] 1: Femtosecond laser for excitation 2: Laser beam splitter 3: Mirror 4: Transmitter 5: Mirror 6: Optical delay mechanism for sampling 7: Probe light path 8: Mirror 9: Mirror 10: Optical path of terahertz waves 11: Terahertz wave beam splitter 12: Measurement target 13: Receiving section 14: Sample 15: Incident terahertz wave 16: Rotating stage 17: Moving Stage 18: Control unit 21: Measurement section 22: Mechanism section 23: Image processing unit 24: Judgment processing unit 25: Display section

Claims

1. A deterioration determination device for determining deterioration of a linear structure in which a plurality of metal wires are twisted together, comprising: an image processing unit that acquires an image of the surface of the linear structure measured using terahertz waves and binarizes the acquired image using a plurality of binarization thresholds; a determination processing unit that determines a conformance rate between a straight line included in a binary image obtained by the binarization and a straight line included in a binary image obtained when there is no deterioration in the plurality of metal wires for each of the binarization thresholds, and determines deterioration of the linear structure based on the conformance rate for the plurality of binarization thresholds; A deterioration determination device comprising:

2. The judgment processing unit extracts straight lines corresponding to the plurality of metal wires from the binarized image obtained by the binarization using a gradient of a straight line included in the binarized image obtained by the binarization, and calculates the matching rate using the number of extracted straight lines. The deterioration determining device according to claim 1 .

3. the image represents a reflection intensity of the terahertz wave irradiated onto the linear structure, The image processing unit extracts an area of ​​the image having a high reflection intensity by the binarization. The deterioration determining device according to claim 1 .

4. The image processing unit standardizes the image using a threshold determined by the reflection intensity, and binarizes the standardized image using a plurality of binarization thresholds. The deterioration determining device according to claim 3 .

5. The image processing unit extracts straight lines corresponding to the plurality of metal wires using a Progressive Probabilistic Hough Transform; The threshold of the Progressive Probabilistic Hough Transform is 5 or more and 20 or less; The deterioration determining device according to claim 2 .

6. A deterioration determination device according to any one of claims 1 to 5, a measuring unit that measures the linear structure by using terahertz waves; a mechanism for moving the measurement unit in a longitudinal direction of the linear structure and in a rotational direction perpendicular to the longitudinal direction; Equipped with the deterioration determination device determines deterioration of the linear structure by using an image obtained from the data measured by the measurement unit; Deterioration assessment system.

7. A deterioration determination method for determining deterioration of a linear structure in which a plurality of metal wires are twisted together, comprising the steps of: Obtaining an image of the surface of the linear structure measured using terahertz waves; The acquired image is binarized using a plurality of binarization thresholds. A matching rate between a straight line included in a binarized image obtained by the binarization and a straight line included in a binarized image obtained when there is no deterioration in the plurality of metal wires is calculated for each of the binarization thresholds; determining deterioration of the linear structure based on the matching rates for the plurality of binarization thresholds; Deterioration judgment method.

Images