Structure evaluation system, structure evaluation device, and structure evaluation method

Abstract

To provide a structure evaluation system, a structure evaluation device, and a structure evaluation method, which can suppress a decrease in evaluation accuracy of a deterioration state of a structure.SOLUTION: A structure evaluation system includes a plurality of sensors, a position locator, a distribution generator, and an evaluator. The plurality of sensors detect elastic waves generated inside a structure. The position locator locates positions of one or more elastic wave generation sources on the basis of a plurality of elastic waves detected by each of the plurality of sensors. The distribution generator generates an elastic wave source density distribution representing a density distribution of the one or more elastic wave generation sources on the basis of a position location result of the one or more elastic wave generation sources obtained by the position locator. The evaluator evaluates damage to the structure on the basis of one or more reference distributions generated on the basis of a simulation including a random number and the elastic wave source density distribution generated by the distribution generator.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] An embodiment of the present invention relates to a structure evaluation system, a structure evaluation device, and a structure evaluation method. [Background technology]

[0002] By installing a sensor on the surface of a structure such as a bridge, it is possible to detect elastic waves generated inside the structure. Furthermore, by installing multiple sensors on the surface of the structure, it is possible to locate the position of the source of the elastic waves (hereinafter referred to as the "elastic wave source") based on the difference in arrival time of the elastic waves detected by each sensor. Elastic waves are also generated inside the structure when an impact is applied to the surface of the structure from the outside. In such cases, too, it is possible to locate the position of the elastic wave source based on the difference in arrival time of the elastic waves detected by each sensor.

[0003] When there is damage to the propagation path of elastic waves inside a structure, the propagation of the elastic waves is impeded. When the propagation of elastic waves is impeded due to damage inside the structure, some sensors cannot detect the elastic waves. As a result, the accuracy of the location results of the elastic wave source is reduced. When a spatially uniform impact, such as the impact of raindrops on a road surface during rainfall, is applied to the surface of a structure and elastic waves are detected by sensors installed on opposite sides, a decrease in the density of elastic wave sources is observed in areas with internal damage. By utilizing such characteristics, the deterioration state of a structure (presence or absence of damage inside the structure) can be evaluated. In particular, damage inside a structure can be detected using elastic waves generated by vehicles traveling on the road surface.

[0004] Conventionally, various correction methods have been disclosed for improving the accuracy of the evaluation results obtained by the above-mentioned method. For example, a method has been disclosed in which, in order to compare measurement results with different traffic volumes, information about vehicles traveling at a measurement target location is estimated, and the density of elastic wave sources is corrected using a correction value based on the ratio between the number of passing vehicles and the number of passing vehicles obtained at a structure to be compared.

[0005] The location process for identifying the location of the elastic wave source uses an algorithm called event extraction, which determines whether multiple hits result from the same event (e.g., the same impact). Specifically, the event extraction algorithm is a process in which hits detected by two or more sensors at approximately the same time within a specified time window are considered to result from the same event. However, the event extraction algorithm may generate spurious density distribution patterns that should not actually exist due to random noise that occurs under certain conditions. Therefore, such spurious density distribution patterns may reduce the accuracy of the assessment of the deterioration state of a structure. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] International Publication No. 2017 / 217034 [Patent Document 2] International Publication No. 2022 / 014004 [Patent Document 3] Patent Publication No. 2022-70711 Summary of the Invention [Problem to be solved by the invention]

[0007] The problem to be solved by the present invention is to provide a structure evaluation system, a structure evaluation device, and a structure evaluation method that can suppress a decrease in the accuracy of evaluating the deterioration state of a structure. [Means for solving the problem]

[0008] A structure evaluation system according to an embodiment includes a plurality of sensors, a position locating unit, a distribution generating unit, and an evaluation unit. The plurality of sensors detect elastic waves generated inside a structure. The position locating unit locates a position of one or more elastic wave sources based on a plurality of elastic waves detected by each of the plurality of sensors. The distribution generating unit generates an elastic wave source density distribution representing a density distribution of the one or more elastic wave sources based on a position locating result of the one or more elastic wave sources by the position locating unit. The evaluation unit evaluates damage to the structure based on one or more reference distributions generated based on a simulation including random numbers and the elastic wave source density distribution generated by the distribution generating unit. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram showing the configuration of a structure evaluation system according to a first embodiment. [Diagram 2] FIG. 2 is a diagram showing an example of the configuration of a signal processing unit according to the first embodiment. [Diagram 3] 3A to 3C are diagrams for explaining a method of measuring an elastic wave in the first embodiment. [Figure 4] 5 is a flowchart showing the flow of a reference distribution generation process performed by a reference distribution generation unit in the first embodiment. [Figure 5A] FIG. 13 is a diagram showing an example of a reference distribution obtained when the time window width k is set to 1 [μs]. [Figure 5B] FIG. 13 is a diagram showing an example of a reference distribution obtained when the time window width k is set to 10 μs. [Figure 5C] FIG. 13 is a diagram showing an example of a reference distribution obtained when the time window width k is set to 100 μs. [Figure 5D] FIG. 13 is a diagram showing an example of a reference distribution obtained when the time window width k is set to 200 μs. [Figure 5E] FIG. 13 is a diagram showing an example of a reference distribution obtained when the time window width k is set to 500 [μs]. [Figure 5F] FIG. 13 is a diagram showing an example of a reference distribution obtained when the time window width k is set to 1000 [μs]. [Figure 6]13 is a graph showing the relationship between the time window width k and a feature value related to the location accuracy of the elastic wave source density distribution. [Figure 7A] 5 is a diagram for explaining a method for calculating an index of uncertainty of a position location result in the first embodiment. [Figure 7B] 5 is a diagram for explaining a method for calculating an index of uncertainty of a position location result in the first embodiment. [Figure 7C] 5 is a diagram for explaining a method for calculating an index of uncertainty of a position location result in the first embodiment. [Figure 8] FIG. 2 is a sequence diagram showing the flow of a deterioration state evaluation process performed by the structure evaluation system in the first embodiment. [Figure 9] FIG. 11 is a diagram for explaining an overview of a process performed by a distribution selection unit in a modified example of the first embodiment. [Figure 10] FIG. 13 is a diagram showing the configuration of a structure evaluation system according to a second embodiment. [Figure 11] FIG. 11 is a sequence diagram showing the flow of a deterioration state evaluation process performed by a structure evaluation system according to a second embodiment. [Figure 12A] 6A to 6C are diagrams showing examples of detection of elastic waves by each sensor in a simulation of each embodiment. [Figure 12B] FIG. 11 is a diagram showing an example of detection of an elastic wave by each sensor in a simulation according to the modified examples of each embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, a structure evaluation system, a structure evaluation device, and a structure evaluation method according to embodiments will be described with reference to the drawings.

[0011] (First embodiment) 1 is a diagram showing the configuration of a structure evaluation system 100 in the first embodiment. The structure evaluation system 100 is used to evaluate the soundness of a structure 50. In the following description, evaluation means determining the degree of soundness of the structure 50, i.e., the deterioration state of the structure 50, based on a certain criterion.

[0012] In the following description, the structure 50 is a bridge, but the structure 50 does not have to be limited to a bridge. The structure 50 may be any structure in which elastic waves 11 are generated due to the occurrence or growth of a crack, or an external impact (e.g., rain, artificial rain, etc.). Note that bridges are not limited to structures erected over rivers, valleys, etc., but also include various structures (e.g., highway viaducts) that are installed above the ground.

[0013] Damage that affects the evaluation of the deterioration state of the structure 50 includes damage inside the structure that impedes the propagation of elastic waves 11, such as cracks, cavities, and sedimentation. Here, the cracks include vertical cracks, horizontal cracks, and diagonal cracks. A vertical crack is a crack that occurs in a direction perpendicular to the road surface. A horizontal crack is a crack that occurs in a direction horizontal to the road surface. A diagonal crack is a crack that occurs in a direction other than horizontal and vertical to the road surface. Sedimentation is a deterioration in which concrete turns into sediment, mainly at the boundary between the asphalt and the concrete deck.

[0014] The structure evaluation system 100 includes a plurality of sensors 20-1 to 20-n (n is an integer equal to or greater than 2), a signal processing unit 30, and a structure evaluation device 40. Each of the plurality of sensors 20-1 to 20-n and the signal processing unit 30 are connected to each other via wires so as to be able to communicate with each other. The signal processing unit 30 and the structure evaluation device 40 are connected to each other so as to be able to communicate with each other via wires or wirelessly. In the following description, when there is no need to distinguish between the sensors 20-1 to 20-n, they will be referred to as sensors 20.

[0015] 1, when a vehicle 10 passes over a structure 50, a load is applied to the road surface due to contact between the running parts of the vehicle 10 and the road surface. A large number of elastic waves 11 are generated inside the structure 50 due to deflection caused by the load. Each sensor 20 installed on the underside of the structure 50 can detect the elastic waves 11 generated inside the structure 50.

[0016] The sensor 20 has a piezoelectric element and detects the elastic wave 11 generated from inside the structure 50. The sensor 20 is installed at a position where it can detect the elastic wave 11 on the surface of the structure 50. For example, the sensors 20-1 to 20-n are installed on any one of the road surface, side surface, and bottom surface at equal or different intervals in the vehicle travel axis direction and the vehicle travel axis perpendicular direction. The vehicle travel axis direction refers to the direction in which the vehicle travels on the road surface. The vehicle travel axis perpendicular direction refers to the direction perpendicular to the vehicle travel axis direction. The sensor 20 converts the detected elastic wave 11 into an electric signal. In the following description, a case where the sensor 20 is installed on the bottom surface of the structure 50 will be described as an example.

[0017] For example, a piezoelectric element having sensitivity in the range of 10 kHz to 1 MHz is used for the sensor 20. There are various types of sensors 20, such as a resonance type having a resonance peak within a frequency range and a wideband type with suppressed resonance, but any type of sensor 20 may be used. The method of the sensor 20 detecting the elastic wave 11 includes a voltage output type, a resistance change type, and a capacitance type, but any detection method may be used.

[0018] An acceleration sensor may be used instead of the sensor 20. In this case, the acceleration sensor detects the elastic waves 11 generated inside the structure 50. Then, the acceleration sensor performs the same process as the sensor 20 to convert the detected elastic waves 11 into an electrical signal.

[0019] Between the sensor 20 and the signal processing unit 30, for example, an amplifier, a filter, and an analog-digital converter (not shown) are provided. The amplifier amplifies the electrical signal output from the sensor 20. The amplifier amplifies the electrical signal to a level that allows processing in, for example, an analog-digital converter. The amplifier outputs the amplified electrical signal to the filter. The filter removes noise components outside a predetermined band. The filter is, for example, a band pass filter (BPF). The electrical signal from which noise has been removed by the filter is input to the analog-digital converter. The analog-digital converter quantizes the electrical signal from which noise has been removed and converts it into a digital signal. The analog-digital converter outputs the digital signal to the signal processing unit 30.

[0020] The signal processing unit 30 receives the digital signal output from the analog-digital converter. The signal processing unit 30 performs signal processing on the input digital signal. The signal processing performed by the signal processing unit 30 includes, for example, noise removal and extraction of elastic wave features. The signal processing unit 30 generates transmission data including the processed digital signal. The signal processing unit 30 outputs the generated transmission data to the structure evaluation device 40.

[0021] The signal processing unit 30 is configured using an analog circuit or a digital circuit. When the signal processing unit 30 is configured using an analog circuit, an analog-digital converter does not need to be provided between the sensor 20 and the signal processing unit 30. In other words, when the signal processing unit 30 is configured using an analog circuit, an electric signal from which noise has been removed by a filter is input to the signal processing unit 30. The digital circuit is realized, for example, by an FPGA (Field Programmable Gate Array) or a microcomputer. The digital circuit may also be realized by a dedicated LSI (Large-Scale Integration). The signal processing unit 30 may also be equipped with a non-volatile memory such as a flash memory or a removable memory. In the following description, a case where the signal processing unit 30 is configured using a digital circuit will be described.

[0022] 2 is a diagram showing an example of the configuration of the signal processing unit 30 in the first embodiment. The signal processing unit 30 includes a waveform shaping filter 301, a gate generating circuit 302, an arrival time determining unit 303, a feature extracting unit 304, a transmission data generating unit 305, a memory 306, and an output unit 307.

[0023] The waveform shaping filter 301 removes noise components outside a predetermined band from the input digital signal. The waveform shaping filter 301 is, for example, a digital band-pass filter (BPF). The waveform shaping filter 301 outputs the digital signal after the noise components have been removed (hereinafter referred to as the “noise-removed signal”) to the gate generation circuit 302 and the feature extraction unit 304.

[0024] The gate generation circuit 302 receives the noise removal signal output from the waveform shaping filter 301. The gate generation circuit 302 generates a gate signal based on the input noise removal signal. The gate signal is a signal that indicates whether the waveform of the noise removal signal is sustained or not.

[0025] The gate generation circuit 302 is realized by, for example, an envelope detector and a comparator. The envelope detector detects the envelope of the noise-removed signal. The envelope is extracted, for example, by squaring the noise-removed signal and performing a predetermined process (for example, a process using a low-pass filter or a Hilbert transform) on the squared output value. The comparator determines whether the envelope of the noise-removed signal is equal to or greater than a predetermined threshold.

[0026] When the envelope of the noise-removed signal is equal to or greater than a predetermined threshold, the gate generation circuit 302 outputs a first gate signal indicating that the waveform of the noise-removed signal is sustained to the arrival time determination unit 303 and the feature extraction unit 304. On the other hand, when the envelope of the noise-removed signal is less than a predetermined threshold, the gate generation circuit 302 outputs a second gate signal indicating that the waveform of the noise-removed signal is not sustained to the arrival time determination unit 303 and the feature extraction unit 304. Note that, although the gate generation circuit 302 has been configured to determine whether the waveform of the noise-removed signal is sustained based on the envelope, the gate generation circuit 302 may process the noise-removed signal itself or a signal to which an absolute value is applied. The threshold used in this gate generation is referred to as a measurement threshold.

[0027] The arrival time determination unit 303 receives as input a clock output from a clock source such as a crystal oscillator (not shown) and a gate signal output from the gate generation circuit 302. The arrival time determination unit 303 determines the elastic wave arrival time using the clock input while the first gate signal is being input. The arrival time determination unit 303 outputs the determined elastic wave arrival time to the transmission data generation unit 305 as time information. The arrival time determination unit 303 does not perform processing while the second gate signal is being input. The arrival time determination unit 303 generates cumulative time information from the time of power-on based on the signal from the clock source. Specifically, the arrival time determination unit 303 may be a counter that counts edges of the clock, and the value of the register of the counter may be the time information. The register of the counter is determined to have a predetermined bit length.

[0028] The feature extraction unit 304 receives the noise-removed signal output from the waveform shaping filter 301 and the gate signal output from the gate generation circuit 302. The feature extraction unit 304 extracts the feature of the noise-removed signal by using the noise-removed signal input while the first gate signal is being input. The feature extraction unit 304 does not perform processing while the second gate signal is being input. The feature is information indicating the feature of the noise-removed signal. In other words, the feature of the noise-removed signal is the feature of the elastic wave detected by the sensor 20.

[0029] The feature amount is, for example, the amplitude [mV] of the waveform, the rise time [usec] of the waveform, the duration [usec] of the gate signal, the number of zero cross counts [times], the energy [arb.] of the waveform, the frequency [Hz], and the root mean square (RMS) value. The feature amount extraction unit 304 outputs parameters related to the extracted feature amount to the transmission data generation unit 305. When outputting the parameters related to the feature amount, the feature amount extraction unit 304 associates a sensor ID with the parameters related to the feature amount. The sensor ID represents identification information for identifying the sensor 20 installed in the area (hereinafter referred to as the "evaluation area") to be evaluated for the soundness of the structure 50.

[0030] The amplitude of the waveform is, for example, the maximum amplitude value in the noise elimination signal. The rise time of the waveform is, for example, the time T1 from when the gate signal starts to rise until the noise elimination signal reaches its maximum value. The duration of the gate signal is, for example, the time from when the gate signal starts to rise until the amplitude becomes smaller than a preset value. The zero cross count is, for example, the number of times the noise elimination signal crosses a reference line that passes through a zero value.

[0031] The energy of the waveform is, for example, a value obtained by integrating the squared amplitude of the noise-removing signal at each time point over time. The definition of the energy is not limited to the above example, and may be, for example, an approximation using the envelope of the waveform. The frequency is the frequency of the noise-removing signal. The RMS value is, for example, a value obtained by squaring the amplitude of the noise-removing signal at each time point and taking the square root.

[0032] The sensor ID, time information, and parameters related to the feature amount are input to the transmission data generation unit 305. The transmission data generation unit 305 generates transmission data including the input sensor ID, time information, and parameters related to the feature amount.

[0033] The memory 306 stores one or more pieces of transmission data generated by the transmission data generating unit 305. The memory 306 is, for example, a dual-port RAM (Random Access Memory).

[0034] The output unit 307 sequentially outputs one or more pieces of transmission data stored in the memory 306 to the structure evaluation device 40. For example, when the signal processing unit 30 and the structure evaluation device 40 are connected by a wire, the output unit 307 outputs one or more pieces of transmission data stored in the memory 306 to the structure evaluation device 40 via a wired cable. When the signal processing unit 30 and the structure evaluation device 40 are connected wirelessly, the output unit 307 outputs one or more pieces of transmission data stored in the memory 306 to the structure evaluation device 40 wirelessly.

[0035] Continuing the explanation by returning to Fig. 1, the structure evaluation device 40 includes a communication unit 41, a control unit 42, a storage unit 43, and a display unit 44.

[0036] The communication unit 41 receives one or more pieces of transmission data output from the signal processing unit 30.

[0037] The control unit 42 controls the entire structure evaluation device 40. The control unit 42 is configured using a processor such as a CPU (Central Processing Unit) and a memory. The control unit 42 executes a program to function as an acquisition unit 421, an event extraction unit 422, a position determination unit 423, a distribution generation unit 424, a reference distribution generation unit 425, a distribution selection unit 426, a correction unit 427, and an evaluation unit 428.

[0038] Some or all of the functional units of the acquisition unit 421, the event extraction unit 422, the positioning unit 423, the distribution generation unit 424, the reference distribution generation unit 425, the distribution selection unit 426, the correction unit 427, and the evaluation unit 428 may be realized by hardware such as an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), or an FPGA, or may be realized by cooperation between software and hardware. The program may be recorded on a computer-readable recording medium. The computer-readable recording medium is, for example, a non-transitory storage medium such as a portable medium such as a flexible disk, a magneto-optical disk, a ROM (Read Only Memory), or a CD-ROM, or a storage device such as a hard disk built into a computer system. The program may be transmitted via an electric communication line.

[0039] Some of the functions of the acquisition unit 421, the event extraction unit 422, the position determination unit 423, the distribution generation unit 424, the reference distribution generation unit 425, the distribution selection unit 426, the correction unit 427 and the evaluation unit 428 do not need to be pre-installed in the structure evaluation device 40, and may be realized by installing an additional application program in the structure evaluation device 40.

[0040] The acquisition unit 421 acquires various information. For example, the acquisition unit 421 acquires transmission data received by the communication unit 41. The acquisition unit 421 acquires transmission data for an evaluation target period. The acquisition unit 421 stores the acquired transmission data in the storage unit 43.

[0041] The event extraction unit 422 extracts transmission data for one event from the transmission data for the evaluation period stored in the storage unit 43. An event refers to an elastic wave generating event that occurred in the structure 50. In this embodiment, the elastic wave generating event is, for example, the vehicle 10 passing over a road surface. Note that the elastic wave generating event is not limited to the vehicle 10 passing over a road surface, but may also be the application of an impact to the structure 50. The impact to the structure 50 may be caused by the collision of countless micro objects, or may be caused by an artificial action such as spraying a drug or water, or a large number of strikes using a device or the like. The countless micro objects are objects that are generated by meteorological phenomena such as raindrops, hail, and sleet. It is desirable that the impact to the structure 50 is applied uniformly to the evaluation target area.

[0042] When one event occurs, elastic waves 11 are detected by multiple sensors 20 at approximately the same time. That is, the storage unit 43 stores transmission data related to elastic waves 11 detected at approximately the same time. Therefore, the event extraction unit 422 sets a predetermined time window and extracts all transmission data whose arrival time is within the range of the time window as transmission data for one event. The event extraction unit 422 outputs the extracted transmission data for one event to the position determination unit 423.

[0043] The time window range Tw may be determined using the elastic wave propagation velocity v in the target structure 50 and the maximum sensor interval dmax so as to be in the range of Tw≧dmax / v. In order to avoid erroneous detection, it is desirable to set Tw to a value as small as possible, so that Tw=dmax / v can be practically satisfied. The elastic wave propagation velocity v may be obtained in advance.

[0044] The position locating unit 423 locates the position of the elastic wave source based on the sensor position information and the sensor ID and time information included in each of the multiple pieces of transmission data extracted by the event extracting unit 422.

[0045] The sensor position information includes information on the installation position of the sensor 20 in association with the sensor ID. The sensor position information includes information on the installation position of the sensor 20, such as latitude and longitude, or horizontal and vertical distances from a reference position of the structure 50. The positioning unit 423 holds the sensor position information in advance. The sensor position information may be stored in the positioning unit 423 at any timing before the positioning unit 423 performs positioning of the elastic wave source.

[0046] The sensor position information may be stored in the storage unit 43. In this case, the position locating unit 423 acquires the sensor position information from the storage unit 43 at the timing of performing position locating. A Kalman filter, a least squares method, or the like may be used to locate the position of the elastic wave source. The position locating unit 423 outputs the position information of the elastic wave source obtained during the evaluation period to the distribution generating unit 424.

[0047] The distribution generating unit 424 receives as input the position information of the multiple elastic wave sources output from the position determining unit 423. The distribution generating unit 424 generates an elastic wave source distribution using the input position information of the multiple elastic wave sources. The elastic wave source distribution represents a distribution indicating the positions of the elastic wave sources. More specifically, the elastic wave source distribution is a distribution in which the horizontal axis represents the distance in the traffic direction and the vertical axis represents the distance in the width direction, and indicates points indicating the positions of the elastic wave sources on virtual data representing the structure 50 to be evaluated.

[0048] The distribution generating unit 424 generates an elastic wave source density distribution using the elastic wave source distribution. The elastic wave source density distribution represents a distribution in which a density value calculated according to the number of elastic wave sources included in each predetermined region in the elastic wave source distribution is indicated. Specifically, the distribution generating unit 424 first divides the elastic wave source distribution into a plurality of regions by dividing the distribution into predetermined sections. Next, the distribution generating unit 424 calculates the density D of each region based on the following formula (1). Then, the distribution generating unit 424 generates an elastic wave source density distribution by assigning the calculated density D value of each region to each region. In this way, the distribution generating unit 424 generates an elastic wave source density distribution by calculating the density D for the region to be evaluated. In addition, in formula (1), N ev represents the number of elastic wave sources located in the domain, and S represents the area of ​​the domain.

[0049]

number

[0050] The reference distribution generating unit 425 generates one or more reference distributions to be used for comparison with the elastic wave source density distribution. Specifically, the reference distribution generating unit 425 generates one or more reference distributions based on a simulation including random numbers. The random numbers are values ​​used to add random delay elements to the arrival times of elastic waves, and take values ​​of, for example, 0 to 1. The simulation used by the reference distribution generating unit 425 is a simulation for generating an elastic wave source density distribution based on one or more elastic wave sources, based on one or more virtually set elastic wave sources. The elastic wave source density distribution generated by this simulation is the reference distribution.

[0051] When performing a simulation, the reference distribution generating unit 425 receives from the outside a speed condition indicating the propagation speed of the elastic wave in the target structure 50, a sensor condition indicating the installation positions of a plurality of sensors, and an elastic wave source condition indicating the number of one or more elastic wave sources. The reference distribution generating unit 425 calculates the arrival time from the position of one or more elastic wave sources to each sensor by executing a simulation based on each of the received conditions. At this time, the reference distribution generating unit 425 calculates the arrival time by adding a time-direction fluctuation based on a random number to the theoretical time at which the elastic wave arrives from the position of each elastic wave source to the position of each sensor. The time-direction fluctuation based on the random number is a random fluctuation in the time direction that is uniformly distributed within a predetermined time range. Thereafter, the reference distribution generating unit 425 performs position location based on the calculated difference between the arrival times at each sensor, and generates an elastic wave source density distribution based on the position location result. The position location technique is the same as the technique used by the position location unit 423, and the elastic wave source density distribution generation technique is the same as the technique used by the distribution generation unit 424.

[0052] The reference distribution generating unit 425 generates a plurality of reference distributions by the above method. For example, the reference distribution generating unit 425 generates a plurality of reference distributions in which fluctuations in the time direction based on random numbers are added by using different random number values. The reference distribution generating unit 425 stores the generated plurality of reference distributions in the storage unit 43 in association with a feature amount related to the location accuracy of the elastic wave source density distribution. The feature amount related to the location accuracy of the elastic wave source density distribution is an index indicating the level of location accuracy of the elastic wave source density distribution, and is, for example, an average value of the uncertainty index of the location result obtained for each predetermined region of the elastic wave source density distribution, a median value of the uncertainty index of the location result obtained for each predetermined region of the elastic wave source density distribution, or a location rate.

[0053] The index of uncertainty of the position location result is an index that indicates the accuracy of the position location, and the closer the value is to 0, the higher the accuracy of the position location. The calculation method of the index of uncertainty of the position location result will be described later. The location rate indicates the ratio of the position location constant to the elastic wave source, and can be obtained, for example, by dividing the number of hits that contributed to the position location by the total number of hits, or by dividing the position location constant by the number of elastic wave sources.

[0054] The distribution selection unit 426 calculates a feature amount related to the location accuracy of the elastic wave source density distribution by using the elastic wave source density distribution generated by the distribution generation unit 424. The distribution selection unit 426 selects at least one reference distribution from among a plurality of reference distributions stored in the storage unit 43 based on the feature amount related to the location accuracy of the calculated elastic wave source density distribution.

[0055] The correction unit 427 corrects the elastic wave source density distribution based on the elastic wave source density distribution generated by the distribution generation unit 424 and at least one reference distribution selected by the distribution selection unit 426. Here, it is assumed that one reference distribution is selected. Specifically, the correction unit 427 compares the selected reference distribution with the elastic wave source density distribution, and performs correction so that the density of the region in the elastic wave source density distribution becomes lower in the region with a higher density in the one reference distribution, and performs correction so that the density of the region in the elastic wave source density distribution becomes higher in the region with a lower density in the one reference distribution. In this way, the correction unit 427 compares the reference distribution and the elastic wave source density distribution for each region of a predetermined size at the same position, and performs correction for each region of a predetermined size. Note that the correction unit 427 can also perform correction by dividing the elastic wave source density distribution into a plurality of regions and performing calculations such as subtraction and division for each divided region.

[0056] The evaluation unit 428 evaluates the deterioration state of the structure 50 using the elastic wave source density distribution corrected by the correction unit 427. For example, the evaluation unit 428 evaluates a region in which the density of the elastic wave source is equal to or greater than a threshold in the corrected elastic wave source density distribution as a healthy region, and evaluates a region in which the density of the elastic wave source is less than the threshold as a damaged region.

[0057] The storage unit 43 stores the transmission data for the evaluation period acquired by the acquisition unit 421 and the reference distribution table. The reference distribution table is a table in which a plurality of records are registered in which the reference distribution and the feature amount related to the location accuracy of the reference distribution are associated with each other. The storage unit 43 is configured using a storage device such as a magnetic hard disk device or a semiconductor storage device.

[0058] The display unit 44 displays the evaluation result according to the control of the evaluation unit 428. For example, the display unit 44 may display the elastic wave source density distribution after correction as the evaluation result, or may display the area considered to be a damaged area in a different display mode from other areas. Furthermore, the display unit 44 displays the elastic wave source and a group of wave lines indicating the propagation path of the elastic wave to each sensor 20, for example, by a projection method, according to the control of the evaluation unit 428. The display unit 44 is an image display device such as a liquid crystal display or an organic EL (Electro Luminescence) display. The display unit 44 may be an interface for connecting the image display device to the structure evaluation device 40. In this case, the display unit 44 generates a video signal for displaying the evaluation result and outputs the video signal to the image display device connected to itself.

[0059] (Method of measuring elastic waves) FIG. 3 is a diagram for explaining a method for measuring elastic waves in the first embodiment. In FIG. 4, as an example of a method for measuring elastic waves, it is considered to evaluate internal damage of a structure 50 based on elastic waves generated by a running part W (for example, a tire) of a vehicle 10 running on a road surface. Here, a case where the structure 50 is a road on which the vehicle 10 runs will be described as an example. Note that the vehicle 10 is not particularly limited, and may be a general running vehicle. By using elastic waves generated by a general vehicle 10, there is no need to regulate vehicles for inspection, which contributes to improving convenience for users. When the running part W of the vehicle 10 comes into contact with the road surface, a load is applied to the road surface. As a result, an elastic wave is generated in the structure 50. The generated elastic wave propagates inside the structure 50 and is detected by each sensor 20 installed on a surface (for example, a bottom surface) different from the road surface.

[0060] The structure 50 is usually composed of a pavement 51 on which travel is possible and a deck 52 that supports the pavement 51. The pavement 51 is, for example, asphalt, and the deck 52 is, for example, concrete. The pavement 51 is generally about 80 mm thick, and the deck 52 is generally about 180 mm to 230 mm thick. An elastic wave (amplitude Asrc ) propagates toward the underside of the deck 52. Along the way, the elastic waves are partly reflected and partly transmitted at the interface 53 between the pavement 51 and the deck 52 due to the difference in acoustic impedance between them. The elastic waves that have propagated further to the underside of the deck 52 reach the sensor 20 and are detected by the sensor 20. Multiple sensors 20 are installed on the underside of the deck 52, and the elastic waves are detected by each sensor 20 with different time differences. The position of the elastic wave source SR is located based on the time differences when detected by each sensor.

[0061] (How to generate a reference distribution) Next, a method for generating a reference distribution by the reference distribution generating unit 425 will be described with reference to the flowchart shown in Fig. 4. Fig. 4 is a flowchart showing the flow of a reference distribution generation process performed by the reference distribution generating unit 425 in the first embodiment. Fig. 4 describes an example of generating a reference distribution by simulating a theoretical elastic wave source density distribution in the case where a uniform elastic wave source exists and uncertainty is mixed into the determination of the arrival time of hit data.

[0062] The reference distribution generating unit 425 receives an input of a velocity condition from the outside (step S11). The input velocity condition is desirably the same as the propagation velocity of an elastic wave in the structure 50 to be evaluated. For example, when the structure 50 to be evaluated is made of concrete, the propagation velocity of an elastic wave is approximately 3000 m / s, so the reference distribution generating unit 425 receives an input of a value of the propagation velocity of an elastic wave of 3000 m / s.

[0063] Next, the reference distribution generating unit 425 receives an input of sensor conditions from the outside (step S12). The input sensor conditions are desirably the same as the installation positions of the sensors 20 installed in the structure 50 to be evaluated. Note that the reference distribution generating unit 425 may acquire, as the sensor conditions, information on the installation positions of the sensors 20 indicated by the sensor position information held by the position determining unit 423. Here, the number of sensors is set to N (N is an integer equal to or greater than 1), and the sensor coordinates are set to S i Let (i=0,…,(N-1)).

[0064] Next, the reference distribution generating unit 425 receives input of elastic wave source conditions from outside (step S13). The number of elastic wave sources input as the elastic wave source conditions is defined as M, and M is, for example, 10,000. First, the reference distribution generating unit 425 randomly places a jth (j is an integer equal to or greater than 1) elastic wave source at a single point in two-dimensional space. The reference distribution generating unit 425 calculates the distance from the position of the placed elastic wave source to the nth sensor (step S14). Here, the distance between the position of the ith sensor and the position of the jth elastic wave source is defined as d ij Let us assume that.

[0065] The generation time and amplitude of the elastic wave at the jth elastic wave source are expressed as generation time t j , amplitude a j In this case, the reference distribution generating unit 425 calculates the arrival time TOA in the hit data detected by the n-th sensor. ij , amplitude A ij is calculated based on the following formulas (2) and (3) (steps S15 and S16). Here, α in formula (2) is a distance attenuation coefficient (unit [dB / m]) that represents the effect of signal attenuation due to distance. As shown in formula (3), in order to reproduce the uncertainty of the arrival time due to noise, the reference distribution generation unit 425 sets a random number R that takes a random value in the range of 0 to 1 for each hit data to a time window width k that determines the maximum time delay. ij A noise term multiplied by R ij It is convenient to use pseudo-random numbers for the time t1, t2, t3, t4, and t5. In this way, the reference distribution generating unit 425 adds fluctuations in the time direction based on the random numbers to the theoretical times at which elastic waves reach the positions of the sensors from the positions of the elastic wave sources.

[0066]

number

[0067]

number

[0068] The jth elastic wave source occurrence time t in Eq. (3) j can be set, for example, as shown in the following equation (4).

[0069]

number

[0070] Here, T in equation (4) s is a constant, set to, for example, 5 [ms]. The amplitude a of the jth elastic wave source j can be set, for example, as shown in the following formula (5). src is not limited to a constant, but is set to, for example, 100 [dB] (0 dB = 1 μV). R j is a random number or pseudorandom number that takes a random value in the range of 0 to 1 for each elastic wave source.

[0071]

number

[0072] The reference distribution generating unit 425 obtains the arrival time when the elastic wave generated from one elastic wave source arrives at each sensor and the amplitude of the elastic wave by the above procedure. The reference distribution generating unit 425 stores the obtained information on the arrival time and the information on the amplitude of the elastic wave as hit data in association with each other. Thereafter, the reference distribution generating unit 425 determines whether the number of set elastic wave sources is M or more (step S17). It is preferable to set M to, for example, 10,000 or more, since this can suppress stochastic fluctuations appearing in the final reference distribution.

[0073] When the reference distribution generating unit 425 determines that the number of elastic wave sources set is not M or more (step S17-NO), the reference distribution generating unit 425 executes the process from step S13 again. In this case, the reference distribution generating unit 425 randomly places one elastic wave source in two-dimensional space in the process of step S13. In this way, the reference distribution generating unit 425 generates a hit data group corresponding to M elastic wave sources by repeatedly executing the processes from step S13 to step S16 until the number of elastic wave sources becomes M or more.

[0074] When the reference distribution generating unit 425 determines that the number of elastic wave sources set is M or more (step S17-YES), the reference distribution generating unit 425 ends the generation of hit data (step S18). The reference distribution generating unit 425 performs amplitude filtering on the hit data group corresponding to the M stored elastic wave sources (step S19). This is a process of excluding hit data that does not meet a predetermined threshold from the hit data group. For example, the reference distribution generating unit 425 excludes hit data with an amplitude of less than 20 [dB] (0 dB = 1 μV). By performing such filtering, elastic waves that are highly attenuated and cannot be detected due to being mixed in noise in an actual environment are simulated. When the filtering is completed, the reference distribution generating unit 425 ends the hit data generation process (step S20).

[0075] The reference distribution generating unit 425 performs position location of the elastic wave source using the hit data group that is not excluded by filtering (step S21). As a result, the positions of the multiple elastic wave sources are located. Thereafter, the reference distribution generating unit 425 generates an elastic wave source distribution using the position information of the multiple elastic wave sources obtained by position location. The reference distribution generating unit 425 generates an elastic wave source density distribution using the elastic wave source distribution. In this manner, one elastic wave source density distribution that takes into account fluctuation in the time direction based on one random number is generated as a reference distribution. The reference distribution generating unit 425 generates multiple reference distributions that take into account fluctuation in the time direction based on the random number by executing the process shown in FIG. 4 with different random numbers. The reference distribution generating unit 425 outputs the multiple reference distributions that have been generated (step S22). For example, the reference distribution generating unit 425 stores the multiple reference distributions that have been generated in the storage unit 43.

[0076] 5A to 5F are diagrams showing an example of a reference distribution generated by the reference distribution generating unit 425 in the first embodiment. Note that in FIG. 5A to FIG. 5F, the darker the color, the lower the density, and the lighter the color, the higher the density. For example, the area shown in white in FIG. 5A to FIG. 5F has the highest density. FIG. 5A is a reference distribution obtained when the time window width k=1 [μs], FIG. 5B is a reference distribution obtained when the time window width k=10 [μs], FIG. 5C is a reference distribution obtained when the time window width k=100 [μs], FIG. 5D is a reference distribution obtained when the time window width k=200 [μs], FIG. 5E is a reference distribution obtained when the time window width k=500 [μs], and FIG. 5F is a reference distribution obtained when the time window width k=1000 [μs].

[0077] As shown in Figures 5A to 5F, while few pseudo patterns are generated in Figures 5A to 5D, pseudo pattern P1 is generated in Figures 5E and 5F. The area where this pseudo pattern P1 is generated has a lower density (darker color) than the area where the pseudo pattern P1 is not generated (white area). Figure 6 shows the relationship between the time window width k and the feature value related to the location accuracy of the elastic wave source density distribution. In Figure 6, the average value of the uncertainty of the location result and the location rate are shown as an example of the feature value related to the location accuracy of the elastic wave source density distribution. Line segment L1 in Figure 6 represents the change in the location rate with respect to the value of the time window width k, and line segment L2 represents the change in the average value of the uncertainty of the location result with respect to the value of the time window width k.

[0078] In the range of time window width k≦1000 [μs], there is a certain correlation between the time window width k and the average value of the uncertainty of the positioning result, and between the time window width k and the positioning rate. As the time window width k increases, the average value of the uncertainty of the positioning result increases and the positioning rate decreases. The average value of the uncertainty of the positioning result is a value that indicates the degree of uncertainty of the positioning result, and the smaller the value, the higher the accuracy of the positioning result, and the larger the value, the more uncertain the positioning result. As described above, referring to FIG. 5E and FIG. 5F, it can be seen that a clear pseudo pattern occurs when k=500 [μs] or more. As shown in FIG. 6, when k=500 [μs], the average value of the uncertainty of the positioning result corresponds to approximately 500 [mm]. In this way, it is possible to link the positioning feature (the average value of the uncertainty of the positioning result in FIG. 6) with the reference distribution.

[0079] (Calculation method for the uncertainty index of position location results) Next, a method for calculating an index of uncertainty of a position location result in the first embodiment will be described with reference to Figs. 7A to 7C. As shown in Fig. 7A, it is assumed that an elastic wave is generated from the position of an elastic wave source SR1. The position of the elastic wave source SR1 is unknown, and the generation time of the elastic wave generated from the position of the elastic wave source SR1 is set to t0. The elastic wave generated by the elastic wave source SR1 is detected by each of the sensors 20-1 to 20-4. Here, the arrival times t1 to t4 at which the elastic waves arrive at the sensors 20-1 to 20-4 are expressed as follows. In the following, tt1, tt2, tt3, and tt4 represent the propagation times.

[0080] t1=t0+tt1 t2=t0+tt2 t3=t0+tt3 t4=t0+tt4

[0081] In FIG. 7A, if the sensor 20 that first detects the elastic wave is sensor 20-2, the time difference between the arrival time of the elastic wave at sensor 20-2 that first detects the elastic wave and the arrival time of the elastic wave at another sensor 20 is expressed as follows.

[0082] Δt1=t1-t2 Δt2=t2-t2=0 Δt3=t3-t2 Δt4=t4-t2

[0083] The above Δt1 to Δt4 are the observation values ​​of the arrival times. The elastic wave source SR1 is located by performing position location based on the observation values ​​Δt1 to Δt4 of the arrival times. This elastic wave source SR1 represents the position of the elastic wave source estimated by the observation values. Then, as shown in FIG. 7C, the distances d1 to d4 between each sensor 20 and the elastic wave source SR1 are calculated based on the positions of the sensors 20-1 to 20-4 and the position of the elastic wave source SR1.

[0084] In FIG. 7C, if the sensor 20-2 is the sensor that is closest to the acoustic wave source SR1, the difference in distance between the acoustic wave source SR1 and each sensor 20 is expressed as follows.

[0085] Δd1=d1-d2 Δd2=d2-d2=0 Δd3=d3-d2 Δd4=d4-d2

[0086] The above Δd1 to Δd4 are the calculated values ​​of the distance difference between the elastic wave source and each point. The uncertainty of the position location result is calculated based on the following equation (6) using the above-mentioned observed and calculated values. V in equation (6) represents the propagation speed of the elastic wave.

[0087]

number

[0088] When the observed value and calculated value in equation (6) match, the uncertainty value of the position location result is 0. On the other hand, the greater the difference between the observed value and the calculated value in equation (6), the higher the uncertainty value of the position location result. In other words, the greater the difference between the observed value and the calculated value in equation (6), the lower the accuracy of the position location result.

[0089] Fig. 8 is a sequence diagram showing the flow of the deterioration state evaluation process by the structure evaluation system 100 in the first embodiment. The process in Fig. 8 is executed, for example, in response to the vehicle 10 traveling through the structure 50 to be evaluated.

[0090] When the vehicle 10 travels over the structure 50 to be evaluated, the traveling part of the vehicle 10 comes into contact with the road surface. This causes an elastic wave 11 to be generated within the structure 50. Each of the multiple sensors 20 detects the elastic wave 11 generated within the structure 50 (step S101). Each of the multiple sensors 20 converts the detected elastic wave 11 into an electrical signal and outputs it to the signal processing unit 30 (step S102). The electrical signal output from each of the multiple sensors 20 is amplified by an amplifier (not shown). The amplified electrical signal is converted into a digital signal by an A / D converter.

[0091] The signal processing unit 30 inputs the digital signal output from the A / D converter. The arrival time determination unit 303 of the signal processing unit 30 determines the arrival time of each elastic wave 11 (step S103). Specifically, the arrival time determination unit 303 determines the elastic wave arrival time using a clock input while the first gate signal is input. The arrival time determination unit 303 outputs the determined elastic wave arrival time to the transmission data generation unit 305 as time information. The arrival time determination unit 303 performs this process on all input digital signals.

[0092] The feature extraction unit 304 of the signal processing unit 30 extracts features of the noise-removed signal, which is a digital signal input while the first gate signal is being input (step S104). The feature extraction unit 304 outputs parameters related to the extracted features to the transmission data generation unit 305. The transmission data generation unit 305 generates transmission data including a sensor ID, time information, and parameters related to the features (step S105). The output unit 307 sequentially outputs the transmission data to the structure evaluation device 40 (step S106).

[0093] The communication unit 41 of the structure evaluation device 40 receives the transmission data output from the signal processing unit 30. The acquisition unit 421 acquires the transmission data received by the communication unit 41. The acquisition unit 421 records the acquired transmission data in the storage unit 43 (step S107). The event extraction unit 422 extracts transmission data for one event from the transmission data stored in the storage unit 43. The event extraction unit 422 outputs the extracted transmission data for one event to the position determination unit 423.

[0094] The positioning unit 423 locates the position of the elastic wave source based on the sensor ID and time information included in the transmission data output from the event extraction unit 422 and pre-stored sensor position information (step S108). Specifically, the positioning unit 423 first calculates the difference in arrival time of the elastic wave 11 to each of the multiple sensors 20. Next, the positioning unit 423 locates the position of the elastic wave source using the sensor position information and information on the difference in arrival time.

[0095] The position locating unit 423 executes the process of step S108 every time transmission data of one event is output from the event extracting unit 422 during the measurement period. In this way, the position locating unit 423 locates the positions of the multiple elastic wave sources. The position locating unit 423 outputs position information of the multiple elastic wave sources to the distribution generating unit 424. The distribution generating unit 424 generates an elastic wave source distribution using the position information of the multiple elastic wave sources output from the position locating unit 423. Specifically, the distribution generating unit 424 generates the elastic wave source distribution by plotting the positions of the elastic wave sources indicated by the obtained position information of the multiple elastic wave sources on virtual data.

[0096] The distribution generating unit 424 generates an elastic wave source density distribution using the generated elastic wave source distribution (step S109). Specifically, the distribution generating unit 424 first divides the elastic wave source distribution into a plurality of areas by dividing the elastic wave source distribution into predetermined sections. Next, the distribution generating unit 424 calculates the density of the elastic wave source for each area. Then, the distribution generating unit 424 generates an elastic wave source density distribution by assigning the calculated elastic wave source density value for each area to each area. The distribution generating unit 424 outputs the generated elastic wave source density distribution to the distribution selecting unit 426 and the correcting unit 427.

[0097] The distribution selection unit 426 calculates a feature quantity related to the location accuracy of the elastic wave source density distribution using the elastic wave source density distribution output from the distribution generation unit 424 (step S110). For example, the distribution selection unit 426 calculates an average value of the uncertainty index of the position location result obtained for each predetermined region of the elastic wave source density distribution as a feature quantity related to the location accuracy of the elastic wave source density distribution. In this case, the distribution selection unit 426 divides the elastic wave source density distribution into a plurality of regions. The distribution selection unit 426 calculates an uncertainty value of the position location result for each divided region. Then, the distribution selection unit 426 calculates an average value of the uncertainty values ​​of the position location result calculated for each region.

[0098] The distribution selection unit 426 selects a reference distribution based on the calculated average value of the uncertainty index of the position location result and the reference distribution table stored in the storage unit 43 (step S110). Specifically, the distribution selection unit 426 refers to the reference distribution table and selects a record in which an average value of the uncertainty index of the position location result closest to the calculated average value of the uncertainty index of the position location result is registered. The distribution selection unit 426 selects a reference distribution registered in the selected record. The distribution selection unit 426 outputs the selected reference distribution to the correction unit 427.

[0099] The correction unit 427 receives the reference distribution output from the distribution selection unit 426 and the elastic wave source density distribution output from the distribution generation unit 424. The correction unit 427 corrects the input elastic wave source density distribution based on the reference distribution (step S112). The correction unit 427 outputs the corrected elastic wave source density distribution to the evaluation unit 428.

[0100] The evaluation unit 428 evaluates the deterioration state of the structure using the corrected elastic wave source density distribution (step S113). The evaluation unit 428 outputs the evaluation result to the display unit 44. The display unit 44 displays the evaluation result output from the evaluation unit 428 (step S114). For example, the display unit 44 may display the corrected elastic wave source density distribution as the evaluation result, or may display an area considered to be a damaged area in a different display mode from other areas.

[0101] In the structure evaluation system 100 configured as described above, damage to the structure 50 is evaluated based on one or more reference distributions generated based on a simulation including random numbers and the elastic wave source density distribution. The reference distribution is a distribution that takes into account fluctuations in the time direction based on random numbers. In other words, the reference distribution is a distribution that reflects the situation in the real environment. The structure evaluation device 40 does not use only the elastic wave source density distribution, but performs evaluation based on the elastic wave source density distribution taking into account the situation in the real environment shown by the reference distribution. This makes it possible to evaluate the deterioration state of the structure in a more realistic environment. Therefore, it is possible to suppress a decrease in the evaluation accuracy of the deterioration state of the structure.

[0102] (Modification of the first embodiment) In the above-described embodiment, the distribution selection unit 426 has been configured to select one reference distribution, but may be configured to select multiple reference distributions. An overview of the process in this configuration will be described with reference to FIG. 9. FIG. 9 is a diagram for explaining an overview of the process performed by the distribution selection unit 426 in the modified example of the first embodiment. First, the distribution selection unit 426 generates multiple divided regions by dividing the elastic wave source density distribution into multiple regions. For example, as shown in the upper diagram of FIG. 9, the distribution selection unit 426 divides the elastic wave source density distribution into two based on the distance in the width direction. As a result, divided regions R1 and R2 based on the elastic wave source density distribution are generated. Note that this is just an example, and the direction in which the elastic wave source density distribution is divided and the number of divisions are not particularly limited.

[0103] Next, the distribution selection unit 426 calculates a feature value related to the orientation accuracy for each of the generated divided regions R1 and R2. The reference distribution table in the storage unit 43 is assumed to associate the divided regions of the reference distribution according to the division number of the reference distribution with the feature value related to the orientation accuracy for each divided region. The distribution selection unit 426 selects a different reference distribution for each of the divided regions R1 and R2 based on the calculated feature value related to the orientation accuracy for each of the divided regions R1 and R2 and the reference distribution table.

[0104] Specifically, the distribution selection unit 426 compares the divided regions of the elastic wave source density distribution and the divided regions of the reference distribution, which are in the same range. For example, the distribution selection unit 426 compares the feature amount related to the location accuracy of the divided region R1 of the elastic wave source density distribution with the feature amount related to the location accuracy of the divided region of the reference distribution, which is in the same range as the divided region R1 of the elastic wave source density distribution. In the example shown in FIG. 9, there are a reference distribution 1 and a reference distribution 2, and the distribution selection unit 426 compares the feature amount related to the location accuracy of the divided region R1 of the elastic wave source density distribution with the feature amount related to the location accuracy of the region R11 of the reference distribution 1, and compares the feature amount related to the location accuracy of the divided region R1 of the elastic wave source density distribution with the feature amount related to the location accuracy of the region R21 of the reference distribution 1. Similarly, the distribution selection unit 426 compares the features related to the location accuracy of the divided region R2 of the elastic wave source density distribution with the features related to the location accuracy of the region R12 of the reference distribution 1, and compares the features related to the location accuracy of the divided region R2 of the elastic wave source density distribution with the features related to the location accuracy of the region R22 of the reference distribution 2.

[0105] Here, the distribution selection unit 426 determines that the feature amount related to the location accuracy of the divided region R1 of the elastic wave source density distribution is close to the feature amount related to the location accuracy of the region R11 of the reference distribution 1, and that the feature amount related to the location accuracy of the divided region R2 of the elastic wave source density distribution is close to the feature amount related to the location accuracy of the region R22 of the reference distribution 2. In this case, the distribution selection unit 426 selects the region R11 of the reference distribution 1 as the reference distribution used to correct the divided region R1 of the elastic wave source density distribution, and selects the region R22 of the reference distribution 2 as the reference distribution used to correct the divided region R2. The distribution selection unit 426 outputs the selected region R11 of the reference distribution 1 and region R22 of the reference distribution 2 to the correction unit 427.

[0106] The correction unit 427 receives as input the region R11 of reference distribution 1 and the region R22 of reference distribution 2 output from the distribution selection unit 426, and the elastic wave source density distribution output from the distribution generation unit 424. The correction unit 427 corrects the input elastic wave source density distribution based on the region R11 of reference distribution 1 and the region R22 of reference distribution 2. For example, the correction unit 427 corrects the divided region R1 of the elastic wave source density distribution based on the region R11 of reference distribution 1, and corrects the divided region R2 of the elastic wave source density distribution based on the region R22 of reference distribution 2.

[0107] Second embodiment In the second embodiment, a configuration for selecting an appropriate reference distribution by template matching will be described.

[0108] FIG. 10 is a diagram showing the configuration of a structure evaluation system 100a in the second embodiment. The structure evaluation system 100a is used to evaluate the soundness of a structure 50. The structure evaluation system 100a comprises a plurality of sensors 20-1 to 20-n (n is an integer equal to or greater than 2), a signal processing unit 30, and a structure evaluation device 40a. The structure evaluation system 100a differs in configuration from the structure evaluation system 100 in that the structure evaluation system 100a comprises the structure evaluation device 40a instead of the structure evaluation device 40. The configuration other than the structure evaluation device 40a is the same as that of the structure evaluation system 100. The following description will focus on the differences.

[0109] The structure evaluation device 40a includes a communication unit 41, a control unit 42a, a storage unit 43a, and a display unit 44. The control unit 42a controls the entire structure evaluation device 40a. The control unit 42a is configured using a processor such as a CPU and a memory. The control unit 42a executes a program to function as an acquisition unit 421, an event extraction unit 422, a position determination unit 423, a distribution generation unit 424, a reference distribution generation unit 425, a distribution selection unit 426a, a correction unit 427, and an evaluation unit 428.

[0110] The storage unit 43a stores the transmission data for the evaluation period and the reference distribution table acquired by the acquisition unit 421. The reference distribution table in the second embodiment is a table in which a plurality of reference distributions generated for different random numbers by the reference distribution generation unit 425 are registered. The storage unit 43a is configured using a storage device such as a magnetic hard disk device or a semiconductor storage device.

[0111] The distribution selection unit 426a selects at least one reference distribution from among the multiple reference distributions based on the similarity between the elastic wave source density distribution generated by the distribution generation unit 424 and the multiple reference distributions registered in a reference distribution table stored in the storage unit 43. More specifically, the distribution selection unit 426a calculates the similarity between the multiple reference distributions and the elastic wave source density distribution by performing template matching between the multiple reference distributions and the elastic wave source density distribution, and selects the reference distribution with the highest similarity from among the multiple reference distributions. The distribution selection unit 426a outputs the selected reference distribution to the correction unit 427.

[0112] Fig. 11 is a sequence diagram showing the flow of the deterioration state evaluation process by the structure evaluation system 100a in the second embodiment. The process in Fig. 11 is executed, for example, in response to the vehicle 10 traveling through the structure 50 to be evaluated. In Fig. 11, the same processes as those in Fig. 8 are denoted by the same reference numerals as in Fig. 8, and the description thereof will be omitted.

[0113] When the processes from step S101 to step S109 are completed, the distribution selection unit 426a selects one or more reference distributions based on the elastic wave source density distribution output from the distribution generation unit 424 and the reference distribution table stored in the storage unit 43a (step S201). Specifically, the distribution selection unit 426a calculates a similarity for each reference distribution by performing pattern matching with each reference distribution registered in the reference distribution table using the elastic wave source density distribution. The distribution selection unit 426a selects the reference distribution with the highest similarity. The distribution selection unit 426a outputs the selected reference distribution to the correction unit 427.

[0114] The correction unit 427 receives the reference distribution output from the distribution selection unit 426a and the elastic wave source density distribution output from the distribution generation unit 424. The correction unit 427a corrects the input elastic wave source density distribution based on the reference distribution (step S202). The correction unit 427 outputs the corrected elastic wave source density distribution to the evaluation unit 428.

[0115] According to the structure evaluation system 100a configured as above, it is possible to obtain the same effect as in the first embodiment, but in a method different from that of the first embodiment.

[0116] (Modification of the second embodiment) In the above embodiment, the distribution selector 426a has been configured to select one reference distribution, but may be configured to select multiple reference distributions. An overview of the process in this configuration will be described. Here, it will be described with reference to FIG. 9. The distribution selector 426a generates multiple divided regions by dividing the elastic wave source density distribution into multiple regions. For example, as shown in the upper diagram of FIG. 9, the distribution selector 426a divides the elastic wave source density distribution into two based on the distance in the width direction. As a result, divided regions R1 and R2 based on the elastic wave source density distribution are generated. Note that this is just an example, and the direction in which the elastic wave source density distribution is divided and the number of divisions are not particularly limited. Note that multiple reference distributions are registered in the reference distribution table of the storage unit 43a.

[0117] The distribution selection unit 426a selects a different reference distribution for each divided region R1, R2 based on each divided region R1, R2 and the reference distribution table. Specifically, the distribution selection unit 426a performs pattern matching between the divided region of the elastic wave source density distribution and a region in the reference distribution that has the same range as the divided region of the elastic wave source density distribution. For example, the distribution selection unit 426a performs pattern matching between the divided region R1 of the elastic wave source density distribution and regions R11, R21 of the reference distribution that have the same range as the divided region R1 of the elastic wave source density distribution. Similarly, the distribution selection unit 426a performs pattern matching between the divided region R2 of the elastic wave source density distribution and regions R12, R22 of the reference distribution that have the same range as the divided region R2 of the elastic wave source density distribution.

[0118] Here, it is assumed that the distribution selection unit 426a has determined that the similarity between the divided region R1 of the elastic wave source density distribution and the region R11 of the reference distribution 1 is the highest, and the similarity between the divided region R2 of the elastic wave source density distribution and the region R22 of the reference distribution 2 is the highest. In this case, the distribution selection unit 426a selects the region R11 of the reference distribution 1 as the reference distribution used to correct the divided region R1 of the elastic wave source density distribution, and selects the region R22 of the reference distribution 2 as the reference distribution used to correct the divided region R2. The distribution selection unit 426 outputs the selected region R11 of the reference distribution 1 and region R22 of the reference distribution 2 to the correction unit 427.

[0119] The correction unit 427 receives as input the region R11 of reference distribution 1 and the region R22 of reference distribution 2 output from the distribution selection unit 426a, and the elastic wave source density distribution output from the distribution generation unit 424. The correction unit 427 corrects the input elastic wave source density distribution based on the region R11 of reference distribution 1 and the region R22 of reference distribution 2. For example, the correction unit 427 corrects the divided region R1 of the elastic wave source density distribution based on the region R11 of reference distribution 1, and corrects the divided region R2 of the elastic wave source density distribution based on the region R22 of reference distribution 2.

[0120] (Modification 1 common to each embodiment) In each of the above embodiments, a configuration has been shown in which multiple sensors 20-1 to 20-n are connected to one signal processing unit 30, 30a, 30b. The structure evaluation systems 100, 100a, 100b may include multiple signal processing units 30, 30a, 30b, and each sensor 20 may be connected to a different signal processing unit 30, 30a, 30b.

[0121] (Modification 2 common to each embodiment) Some or all of the functional units of the structure evaluation device 40, 40b may be provided in another device. For example, the display unit 44 of the structure evaluation device 40, 40b may be provided in the other device. When configured in this manner, the structure evaluation device 40, 40b transmits the evaluation result to the other device equipped with the display unit 44. The other device equipped with the display unit 44 displays the received evaluation result.

[0122] (Modification 3 common to each embodiment) In each of the above-mentioned embodiments, a configuration was shown in which a reference distribution is generated based on a simulation in which a delay corresponding to a random number is given to the arrival time of an elastic wave. In contrast, in a simulation performed by the reference distribution generating unit 425, a reference distribution may be generated by including noise corresponding to a random number in the amplitude direction with respect to the theoretical amplitude of an elastic wave arriving at each sensor set in the simulation. A specific description will be given with reference to Figs. 12A and 12B. Fig. 12A is a diagram showing an example of detection of an elastic wave at each sensor in a simulation of each of the above-mentioned embodiments, and Fig. 12B is a diagram showing an example of detection of an elastic wave at each sensor in a simulation of a modified example of each embodiment. In Figs. 12A and 12B, the vertical axis represents amplitude, and the horizontal axis represents time.

[0123] As shown in FIG. 12A, each sensor in the simulation detects an elastic wave when the amplitude of the elastic wave exceeds a threshold. Here, when noise is added to the elastic wave, the amplitude of the elastic wave is lowered as shown in FIG. 12B compared to the amplitude of the elastic wave shown in FIG. 12A. As a result, even if the threshold for detecting the elastic wave is the same, the timing at which the amplitude of the elastic wave exceeds the threshold is delayed in FIG. 12B compared to FIG. 12A due to the lower amplitude of the elastic wave. That is, in FIG. 12B, the timing at which the elastic wave is detected is delayed compared to FIG. 12A. This means that it is substantially the same as giving a delay according to a random number to the arrival time of the elastic wave in each of the above embodiments. Therefore, the reference distribution generating unit 425 may add noise to the elastic wave arriving at each sensor in the simulation so as to reduce the amplitude according to a random number, and generate a reference distribution to match the actual environment.

[0124] (Modification 4 common to each embodiment) In the first embodiment, a configuration is shown in which a reference distribution is selected based on a feature amount related to the orientation accuracy, and in the second embodiment, a configuration is shown in which a reference distribution is selected based on a similarity obtained by pattern matching. The first embodiment and the second embodiment may be combined to select a reference distribution. When configured in this way, the structure evaluation device 40, 40a may switch between the first embodiment and the second embodiment as a method for selecting a reference distribution by settings.

[0125] Furthermore, the structure evaluation device 40, 40a may use a different reference distribution selection method for each divided region obtained by dividing the elastic wave source density distribution. For example, in the example shown in Fig. 9, the structure evaluation device 40, 40a may select a different reference distribution for each divided region by using the selection method shown in the first embodiment (selection method based on a feature amount related to the location accuracy) for the divided region R1 of the elastic wave source density distribution, and the selection method shown in the second embodiment (selection method based on pattern matching) for the divided region R2 of the elastic wave source density distribution.

[0126] According to at least one of the embodiments described above, by having a plurality of sensors 20 that detect elastic waves generated inside the structure 50, a position determination unit 423 that determines the positions of one or more elastic wave sources based on the plurality of elastic waves detected by each of the plurality of sensors 20, a distribution generation unit 424 that generates an elastic wave source density distribution based on the position determination results of the one or more elastic wave sources by the position determination unit 423, and an evaluation unit 428 that evaluates damage to the structure 50 based on one or more reference distributions generated based on a simulation including random numbers and the elastic wave source density distribution generated by the distribution generation unit 424, it is possible to suppress a decrease in the accuracy of evaluation of the deterioration state of the structure.

[0127] Although some embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope of the invention and its equivalents described in the claims, as well as in the scope and spirit of the invention. [Explanation of symbols]

[0128] 20, 20-1 to 20-n...sensor, 30...signal processing unit, 40, 40a...structure evaluation device, 41...communication unit, 42, 42a...control unit, 43, 43a...storage unit, 44...display unit, 100, 100a...structure evaluation system, 301...wave shaping filter, 302...gate generation circuit, 303...arrival time determination unit, 304...feature extraction unit, 305...transmission data generation unit, 306...memory, 307...output unit, 421...acquisition unit, 422...event extraction unit, 423...position location unit, 424...distribution generation unit, 425...reference distribution generation unit, 426, 426a...distribution selection unit, 427...correction unit, 428...evaluation unit

Claims

1. A plurality of sensors for detecting elastic waves generated inside the structure; a position locating unit that locates a position of one or more elastic wave sources based on a plurality of elastic waves detected by each of the plurality of sensors; a distribution generating unit that generates an elastic wave source density distribution representing a density distribution of the one or more elastic wave sources based on a result of locating the position of the one or more elastic wave sources by the position locating unit; an evaluation unit that evaluates damage to the structure based on one or more reference distributions generated based on a simulation including random numbers and the elastic wave source density distribution generated by the distribution generation unit; A structure evaluation system comprising:

2. A reference distribution generation unit that generates the one or more reference distributions, The simulation is a simulation in which an elastic wave source density distribution representing a density distribution of one or more elastic wave generation sources is generated as the one or more reference distributions based on one or more virtually set elastic wave generation sources, The reference distribution generation unit receives, as conditions for performing the simulation, input information on one or more elastic wave sources and information on installation positions of a plurality of sensors, and executes the simulation by adding fluctuations in the time direction based on random numbers to the theoretical time at which each elastic wave arrives at each sensor from the received elastic wave source, or adding noise in the amplitude direction corresponding to random numbers to the theoretical amplitude at which each elastic wave arrives at each sensor from the received elastic wave source, thereby generating the one or more reference distributions. The structure evaluation system according to claim 1 .

3. the random number-based fluctuation in the time direction is a random fluctuation in the time direction that is uniformly distributed within a predetermined time range, the reference distribution generation unit generates the one or more reference distributions by taking into account fluctuation in a time direction based on the random numbers that differ for each of the predetermined time ranges. The structure evaluation system according to claim 2 .

4. A correction unit that corrects the elastic wave source density distribution based on the one or more reference distributions, the correction unit compares the one or more reference distributions with the elastic wave source density distribution, and performs a correction such that the density of a region in the elastic wave source density distribution becomes lower in a region having a higher density in the one or more reference distributions, and performs a correction such that the density of a region in the elastic wave source density distribution becomes higher in a region having a lower density in the one or more reference distributions, The evaluation unit evaluates damage to the structure using the elastic wave source density distribution corrected by the correction unit. The structure evaluation system according to any one of claims 1 to 3.

5. The one or more reference distributions are a plurality of reference distributions generated under different conditions, A distribution selection unit that selects at least one reference distribution from the plurality of reference distributions based on a feature amount related to the location accuracy of the elastic wave source density distribution, The correction unit corrects the elastic wave source density distribution using at least one reference distribution selected by the distribution selection unit. The structure evaluation system according to claim 4.

6. The feature amount related to the location accuracy is any one of an average value of an uncertainty index of the location result within a predetermined region of the elastic wave source density distribution, a median value of an uncertainty index of the location result, or a location rate within a predetermined region of the elastic wave source density distribution. The structure evaluation system according to claim 5 .

7. The distribution selection unit generates a plurality of divided regions by dividing the elastic wave source density distribution into a plurality of regions, and selects a different reference distribution for each of the divided regions based on a feature amount related to the location accuracy of each of the generated divided regions. The structure evaluation system according to claim 5 .

8. The one or more reference distributions are a plurality of reference distributions generated under different conditions, A distribution selection unit that selects at least one reference distribution from the plurality of reference distributions based on a similarity between the plurality of reference distributions and the elastic wave source density distribution, The correction unit corrects the elastic wave source density distribution using at least one reference distribution selected by the distribution selection unit. The structure evaluation system according to claim 4.

9. the distribution selection unit calculates a similarity between the plurality of reference distributions and the elastic wave source density distribution by performing template matching between the plurality of reference distributions and the elastic wave source density distribution, and selects a reference distribution having the highest similarity from the plurality of reference distributions. The structure evaluation system according to claim 8.

10. the distribution selection unit generates a plurality of divided regions by dividing the elastic wave source density distribution into a plurality of regions, and selects a different reference distribution for each divided region based on a similarity between each of the generated divided regions and the plurality of reference distributions. The structure evaluation system according to claim 8.

11. a position locating unit that locates a position of one or more elastic wave sources based on a plurality of elastic waves detected by a plurality of sensors that detect elastic waves generated inside the structure; a distribution generating unit that generates an elastic wave source density distribution representing a density distribution of the one or more elastic wave sources based on a result of locating the position of the one or more elastic wave sources by the position locating unit; an evaluation unit that evaluates damage to the structure based on one or more reference distributions generated based on a simulation including random numbers and the elastic wave source density distribution generated by the distribution generation unit; A structure evaluation device comprising:

12. Locating a position of one or more sources of elastic waves based on a plurality of elastic waves detected by a plurality of sensors that detect elastic waves generated inside the structure; generating an elastic wave source density distribution representing a density distribution of the one or more elastic wave sources based on the location results of the one or more elastic wave sources; A structure evaluation method for evaluating damage to the structure based on one or more reference distributions generated based on a simulation including random numbers and the elastic wave source density distribution.

Images