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

Abstract

The invention provides a structure evaluation system, a structure evaluation device, and a structure evaluation method capable of suppressing a decrease in evaluation accuracy of a degraded state of a structure. A structure evaluation system according to an embodiment includes a plurality of sensors, a position calibration unit, a distribution generation unit, and an evaluation unit. The plurality of sensors detect elastic waves generated inside the structure. The position calibration unit calibrates the position 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 generation unit generates an elastic wave source density distribution indicating the density distribution of the one or more elastic wave generation sources on the basis of the position calibration results of the one or more elastic wave generation sources obtained by the position calibration unit. The evaluation unit 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 generation unit.

Description

Technical Field

[0001] Embodiments of the present invention relate to a structure evaluation system, a structure evaluation device, and a structure evaluation method. Background Art

[0002] By installing sensors on the surface of a structure such as a bridge, elastic waves generated inside the structure can be detected. Furthermore, by installing multiple sensors on the surface of the structure, the position of the source of the elastic waves (hereinafter referred to as "elastic wave source") can be calibrated based on the difference in arrival time of the elastic waves detected by each sensor. When an impact is applied to the surface of a structure from the outside, elastic waves are also generated inside the structure. In such a case, the position of the elastic wave source can also be calibrated based on the difference in arrival time of the elastic waves detected by each sensor.

[0003] In the case where there is damage to the propagation path of elastic waves inside a structure, the propagation of elastic waves is hindered. When the propagation of elastic waves is hindered by damage inside a structure, some sensors cannot detect the elastic waves. As a result, the accuracy of the calibration results of the elastic wave source decreases. In the case where an impact is uniformly applied in space to the surface of a structure, such as the collision of raindrops on the road during rainfall, and elastic waves are detected by sensors arranged on the opposite side, the density of elastic wave sources decreases in the area with internal damage and is observed. Such characteristics can be used to evaluate the degradation state of the structure (whether there is damage inside the structure). In particular, it is possible to detect damage inside a structure using elastic waves generated by a vehicle traveling on the road.

[0004] In the past, various correction methods for improving the accuracy of the evaluation results obtained by the above-mentioned method have been disclosed. For example, the following method is disclosed: in order to compare measurement results with different traffic volumes, information related to vehicles traveling at the place of measurement object is estimated, and the density of elastic wave sources is corrected using a correction value based on the ratio of the number of passing vehicles to the number of passing vehicles obtained from the structure as the comparison object.

[0005] In the position calibration process for determining the position of the elastic wave source, an algorithm called event extraction is used to determine whether multiple hits are generated from the same event (for example, the same impact). Specifically, the event extraction algorithm is a process that treats hits detected by more than two sensors approximately simultaneously within a predetermined time window as hits generated from the same event. However, the event extraction algorithm sometimes generates a pseudo-density distribution pattern that should not exist due to random noise generated under certain conditions. Therefore, sometimes due to such a pseudo-density distribution pattern, the accuracy of the evaluation of the degradation state of the structure is reduced.

[0006] Prior art literature

[0007] Patent Literature

[0008] Patent Document 1: International Publication No. 2017 / 217034

[0009] Patent Document 2: International Publication No. 2022 / 014004

[0010] Patent Document 3: Japanese Patent Application Publication No. 2022-70711 Summary of the invention

[0011] An object of 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 evaluation accuracy of the degradation state of a structure.

[0012] The structure evaluation system of the embodiment has a plurality of sensors, a position calibration unit, a distribution generating unit, and an evaluating unit. The plurality of sensors detect elastic waves generated inside the structure. The position calibration unit calibrates the positions of one or more elastic wave generation sources based on the plurality of elastic waves respectively detected by the plurality of sensors. The distribution generating unit generates an elastic wave source density distribution representing the density distribution of the one or more elastic wave generation sources based on the position calibration results of the one or more elastic wave generation sources obtained by the position calibration unit. The evaluating unit evaluates the damage of 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

[0013] Figure 1 It is a diagram showing the configuration of the structure evaluation system in the first embodiment.

[0014] Figure 2 It is a diagram showing a configuration example of a signal processing unit in the first embodiment.

[0015] Figure 3 It is a diagram for explaining the elastic wave measuring method in the first embodiment.

[0016] Figure 4 This is a flowchart showing the flow of a reference distribution generation process performed by the reference distribution generation unit in the first embodiment.

[0017] Figure 5A This is a diagram showing an example of a reference distribution obtained when the time window width is set to k=1 [μs].

[0018] Figure 5B This is a diagram showing an example of a reference distribution obtained when the time window width is set to k=10 [μs].

[0019] Figure 5CThis is a diagram showing an example of a reference distribution obtained when the time window width is set to k=100 [μs].

[0020] Figure 5D This is a diagram showing an example of a reference distribution obtained when the time window width is set to k=200 [μs].

[0021] Figure 5E This is a diagram showing an example of a reference distribution obtained when the time window width is set to k=500 [μs].

[0022] Fig. 5F This is a diagram showing an example of a reference distribution obtained when the time window width is set to k=1000 [μs].

[0023] Figure 6 is a diagram showing the relationship between the time window width k and the characteristic quantity related to the calibration accuracy of the elastic wave source density distribution.

[0024] Fig. 7A This is a diagram for explaining a method of calculating an index of uncertainty of a positioning result in the first embodiment.

[0025] Figure 7B This is a diagram for explaining a method of calculating an index of uncertainty of a positioning result in the first embodiment.

[0026] Figure 7C This is a diagram for explaining a method of calculating an index of uncertainty of a positioning result in the first embodiment.

[0027] Figure 8 This is a sequence diagram showing the flow of a degradation state evaluation process performed by the structure evaluation system in the first embodiment.

[0028] Fig. 9 This is a diagram for explaining an overview of processing performed by a distribution selection unit in a modification of the first embodiment.

[0029] Fig.10 It is a diagram showing the configuration of a structure evaluation system in the second embodiment.

[0030] Fig.11 This is a sequence diagram showing the flow of a degradation state evaluation process performed by the structure evaluation system in the second embodiment.

[0031] Fig. 12A It is a diagram showing an example of elastic wave detection by each sensor in the simulation of each embodiment.

[0032] Fig. 12B It is a diagram showing an example of elastic wave detection by each sensor in a simulation in a modification of each embodiment.

[0033] (Explanation of symbols)

[0034] 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: waveform 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 calibration unit; 424: distribution generation unit; 425: reference distribution generation unit; 426, 426a: distribution selection unit; 427: correction unit; 428: evaluation unit. DETAILED DESCRIPTION

[0035] Hereinafter, a structure evaluation system, a structure evaluation device, and a structure evaluation method according to an embodiment will be described with reference to the drawings.

[0036] (First embodiment)

[0037] Figure 1 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 a structure 50, that is, the deterioration state of the structure 50, based on a certain criterion.

[0038] In the following description, the case where the structure 50 is a bridge is used as an example for explanation, but the structure 50 is not limited to a bridge. The structure 50 can be any structure as long as it is accompanied by the generation or deepening of cracks or external impact (such as rain, artificial rain, etc.) to generate elastic waves 11. In addition, bridges are not limited to structures built on rivers, valleys, etc., but also include various structures set above the ground (such as viaducts of highways).

[0039] Damage that affects the evaluation of the deterioration state of the structure 50 includes damage inside the structure that hinders the propagation of the elastic wave 11, such as cracks, voids, and soil sandification. Here, the cracks include longitudinal cracks, transverse cracks, and oblique cracks. Longitudinal cracks refer to cracks that occur in a direction perpendicular to the road surface. Transverse cracks refer to cracks that occur in a direction horizontal to the road surface. Oblique cracks refer to cracks that occur in directions other than horizontal and vertical to the road surface. Soil sandification mainly refers to the deterioration of the concrete at the boundary between the asphalt and the concrete base plate, which changes into soil sand.

[0040] The structure evaluation system 100 includes a plurality of sensors 20-1 to 20-n (n is an integer greater than or equal to 2), a signal processing unit 30, and a structure evaluation device 40. The plurality of sensors 20-1 to 20-n are connected to the signal processing unit 30 by wires so as to be communicable. The signal processing unit 30 is connected to the structure evaluation device 40 by wires or wirelessly so as to be communicable. In the following description, when the sensors 20-1 to 20-n are not distinguished, they are described as sensors 20.

[0041] like Figure 1 As shown, when the vehicle 10 passes over the structure 50, a load is applied to the road surface due to the contact between the running part of the vehicle 10 and the road surface. Due to the deflection caused by the load, a large number of elastic waves 11 are generated inside the structure 50. Each sensor 20 provided on the lower surface of the structure 50 can detect the elastic waves 11 generated inside the structure 50.

[0042] The sensor 20 has a piezoelectric element and detects the elastic wave 11 generated from the inside of the structure 50. The sensor 20 is set 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 separately set at the same or different intervals on any surface of the road surface, the side surface, and the bottom surface, in the direction of the vehicle's driving axis and the direction orthogonal to the vehicle's driving axis. The direction of the vehicle's driving axis indicates the direction in which the vehicle is traveling on the road surface. The direction orthogonal to the vehicle's driving axis indicates the direction perpendicular to the direction of the vehicle's driving axis. The sensor 20 converts the detected elastic wave 11 into an electrical signal. In the following description, the case where the sensor 20 is set on the bottom surface of the structure 50 is taken as an example.

[0043] As the sensor 20, for example, a piezoelectric element having sensitivity in the range of 10 kHz to 1 MHz is used. The sensor 20 includes a resonance type having a resonance peak in the frequency range, a wide-band type suppressing resonance, and the like, but the type of the sensor 20 may be any. The sensor 20 may detect the elastic wave 11 by a voltage output type, a resistance change type, an electrostatic capacitance type, and the like, but any detection method may be used.

[0044] An acceleration sensor may be used instead of the sensor 20. In this case, the acceleration sensor detects the elastic wave 11 generated inside the structure 50. The acceleration sensor converts the detected elastic wave 11 into an electrical signal by performing the same processing as the sensor 20.

[0045] Between the sensor 20 and the signal processing unit 30, for example, an amplifier, a filter, and an analog-to-digital converter (not shown) are provided. The amplifier amplifies the electrical signal output from the sensor 20. The amplifier, for example, amplifies the electrical signal to a level that can be processed in the analog-to-digital converter. The amplifier outputs the amplified electrical signal to the filter. The filter removes noise components outside a predetermined frequency domain. The filter is, for example, a bandpass filter (BPF). The electrical signal after the noise is removed by the filter is input to the analog-to-digital converter. The analog-to-digital converter quantizes the electrical signal from which the noise is removed and converts it into a digital signal. The analog-to-digital converter outputs the digital signal to the signal processing unit 30.

[0046] The signal processing unit 30 receives the digital signal output from the analog-to-digital converter as input. The signal processing unit 30 performs signal processing on the input digital signal. The signal processing performed by the signal processing unit 30 is, for example, noise removal, extraction of characteristic quantities of elastic waves, etc. The signal processing unit 30 generates transmission data including the digital signal after signal processing. The signal processing unit 30 outputs the generated transmission data to the structure evaluation device 40.

[0047] The signal processing unit 30 is constructed using an analog circuit or a digital circuit. In addition, when the signal processing unit 30 is constructed by an analog circuit, an analog-to-digital converter may not be provided between the sensor 20 and the signal processing unit 30. That is, when the signal processing unit 30 is constructed by an analog circuit, an electrical signal after noise is removed by a filter is input to the signal processing unit 30. The digital circuit is implemented, for example, by an FPGA (Field Programmable Gate Array) or a microcomputer. The digital circuit can also be implemented by a dedicated LSI (Large-Scale Integration). In addition, the signal processing unit 30 can also be equipped with a non-volatile memory such as a flash memory or a removable memory. In the following description, the case where the signal processing unit 30 is constructed using a digital circuit is described.

[0048] Figure 2 3 is a diagram showing a configuration example of the signal processing unit 30 in the first embodiment. The signal processing unit 30 includes a waveform shaping filter 301 , a gate generation circuit 302 , an arrival time determination unit 303 , a feature quantity extraction unit 304 , a transmission data generation unit 305 , a memory 306 , and an output unit 307 .

[0049] The waveform shaping filter 301 removes noise components outside a predetermined frequency domain from the input digital signal. The waveform shaping filter 301 is, for example, a digital bandpass filter (BPF). The waveform shaping filter 301 outputs the digital signal after the noise component is removed (hereinafter referred to as "noise-removed signal") to the gate generation circuit 302 and the feature quantity extraction unit 304.

[0050] The gate generation circuit 302 receives the noise elimination signal output from the waveform shaping filter 301 as an input. The gate generation circuit 302 generates a gate signal based on the input noise elimination signal. The gate signal is a signal indicating whether the waveform of the noise elimination signal is continuous.

[0051] The gate generation circuit 302 is implemented, for example, by an envelope detector and a comparator. The envelope detector detects the envelope of the noise-removed signal. The envelope is extracted by, for example, squaring the noise-removed signal and performing a predetermined process (for example, processing using a low-pass filter or Hilbert transform) on the squared output value. The comparator determines whether the envelope of the noise-removed signal is above a predetermined threshold.

[0052] 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 continues to the arrival time determination unit 303 and the feature quantity 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 does not continue to the arrival time determination unit 303 and the feature quantity extraction unit 304. In addition, in the gate generation circuit 302, a configuration is shown in which whether the waveform of the noise-removed signal continues is determined based on the envelope, but the gate generation circuit 302 may also process the noise-removed signal itself or a signal to which an absolute value is applied. The threshold used for this gate generation is described as a measurement threshold.

[0053] 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 uses the clock input during the input of the first gate signal to determine the arrival time of the elastic wave. The arrival time determination unit 303 outputs the determined elastic wave arrival time as time information to the transmission data generation unit 305. The arrival time determination unit 303 does not perform any processing during the input of the second gate signal. The arrival time determination unit 303 generates the accumulated time information from the time when the power is turned on based on the signal from the clock source. Specifically, the arrival time determination unit 303 is set as a counter that counts the edges of the clock, and the value of the register of the counter is used as the time information. The register of the counter is determined in a manner having a predetermined bit length.

[0054] The feature quantity extraction unit 304 receives the noise removal signal output from the waveform shaping filter 301 and the gate signal output from the gate generation circuit 302 as input. The feature quantity extraction unit 304 uses the noise removal signal input during the period when the first gate signal is input, and extracts the feature quantity of the noise removal signal. The feature quantity extraction unit 304 does not perform processing during the period when the second gate signal is input. The feature quantity is information indicating the feature of the noise removal signal. That is, the feature quantity of the noise removal signal is the feature quantity of the elastic wave detected by the sensor 20.

[0055] The characteristic quantity is, for example, the amplitude [mV] of the waveform, the rise time [usec] of the waveform, the duration of the gate signal [usec], the number of zero crossing counts [times], the energy [arb.] of the waveform, the frequency [Hz], and the RMS (Root Mean Square) value. The characteristic quantity extraction unit 304 outputs the parameters related to the extracted characteristic quantity to the transmission data generation unit 305. When outputting the parameters related to the characteristic quantity, the characteristic quantity extraction unit 304 associates the sensor ID with the parameters related to the characteristic quantity. The sensor ID represents the identification information for identifying the sensor 20 provided in the area (hereinafter referred to as the "evaluation area") that is the evaluation object of the soundness of the structure 50.

[0056] The amplitude of the waveform is, for example, the value of the maximum amplitude in the noise removal signal. The rise time of the waveform is, for example, the time T1 from the rise of the gate signal to the time when the noise removal signal reaches the maximum value. The duration of the gate signal is, for example, the time from the rise of the gate signal to the time when the amplitude becomes smaller than a preset value. The zero crossing count is, for example, the number of times the noise removal signal crosses the zero value baseline.

[0057] The energy of a waveform is, for example, a value obtained by time-integrating a value obtained by squaring the amplitude of the noise-removed signal at each time point. In addition, the definition of energy is not limited to the above example, and may be, for example, a value approximated using the envelope of the waveform. The frequency is the frequency of the noise-removed signal. The RMS value is, for example, a value obtained by squaring the amplitude of the noise-removed signal at each time point and taking the square root.

[0058] The transmission data generation unit 305 receives the sensor ID, time information, and parameters related to the feature amount as input. The transmission data generation unit 305 generates transmission data including the input sensor ID, time information, and parameters related to the feature amount.

[0059] The memory 306 stores one or more transmission data generated by the transmission data generating unit 305. The memory 306 is, for example, a dual-port RAM (Random Access Memory).

[0060] The output unit 307 sequentially outputs one or more 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 wire, the output unit 307 outputs one or more transmission data stored in the memory 306 to the structure evaluation device 40 via the 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 transmission data stored in the memory 306 to the structure evaluation device 40 wirelessly.

[0061] Return to Figure 1 The structure evaluation device 40 includes a communication unit 41 , a control unit 42 , a storage unit 43 , and a display unit 44 .

[0062] The communication unit 41 receives one or more transmission data output from the signal processing unit 30 .

[0063] The control unit 42 controls the entire structure evaluation device 40. The control unit 42 is composed of 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 calibration unit 423, a distribution generation unit 424, a reference distribution generation unit 425, a distribution selection unit 426, a calibration unit 427, and an evaluation unit 428.

[0064] Part or all of the functional units of the acquisition unit 421, the event extraction unit 422, the position calibration 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 can be implemented by hardware such as ASIC (Application Specific Integrated Circuit), PLD (Programmable Logic Device), FPGA, etc., or by the collaboration of software and hardware. The program can also be recorded in a recording medium that can be read by a computer. The recording medium that can be read by a computer refers to, for example, non-temporary storage media such as flexible optical disks, optical magnetic disks, ROM (Read Only Memory), removable media such as CD-ROMs, and storage devices such as hard disks built into computer systems. The program can also be sent via an electrical communication line.

[0065] Part of the functions of the acquisition unit 421, the event extraction unit 422, the position calibration 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 on the structure evaluation device 40, and can also be achieved by installing an additional application in the structure evaluation device 40.

[0066] The acquisition unit 421 acquires various information. For example, the acquisition unit 421 acquires the transmission data received by the communication unit 41. In addition, the acquisition unit 421 acquires the transmission data for the evaluation target period. The acquisition unit 421 stores the acquired transmission data in the storage unit 43.

[0067] The event extraction unit 422 extracts the transmission data of one event from the transmission data of the evaluation object period stored in the storage unit 43. The event represents an elastic wave generation event generated in the structure 50. The elastic wave generation event in the present embodiment is, for example, the vehicle 10 passing through the road surface. In addition, the elastic wave generation event is not limited to the vehicle 10 passing through the road surface, but may also be the impact on the structure 50. The impact on the structure 50 may be caused by the collision of countless tiny objects, or by artificial behaviors such as the scattering of medicines, sprinkling of water, and a large number of blows using devices. Countless tiny objects are objects generated by meteorological phenomena such as raindrops, hail, and sleet. The impact on the structure 50 is preferably uniformly applied to the evaluation object area.

[0068] When an event occurs, multiple sensors 20 will detect elastic waves 11 at approximately the same time. That is, the storage unit 43 will store transmission data related to the 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 in one event. The event extraction unit 422 outputs the extracted transmission data in one event to the position calibration unit 423.

[0069] The range Tw of the time window can also be determined in a range of Tw≥dmax / v using the elastic wave propagation velocity v in the target structure 50 and the maximum sensor interval dmax. In order to avoid false detection, it is best to set Tw to the smallest value possible, so it can be substantially set to Tw=dmax / v. The elastic wave propagation velocity v can also be calculated in advance.

[0070] The position identification unit 423 identifies 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 plurality of transmission data extracted by the event extraction unit 422 .

[0071] The sensor position information includes information related to the installation position of the sensor 20 in correspondence with the sensor ID. The sensor position information includes, for example, latitude and longitude, or information related to the installation position of the sensor 20 such as the distance in the horizontal direction and the vertical direction from the position serving as the reference of the structure 50. The position calibration unit 423 retains the sensor position information in advance. The sensor position information can be stored in the position calibration unit 423 at any timing before the position calibration unit 423 calibrates the position of the elastic wave source.

[0072] The sensor position information may also be stored in the storage unit 43. In this case, the position calibration unit 423 obtains the sensor position information from the storage unit 43 at the timing of position calibration. The position calibration unit 423 outputs the position information of the elastic wave source obtained during the evaluation period to the distribution generation unit 424.

[0073] The distribution generating unit 424 receives the position information of the plurality of elastic wave sources output from the position calibration unit 423 as input. The distribution generating unit 424 generates an elastic wave source distribution using the input position information of the plurality of elastic wave sources. The elastic wave source distribution represents a distribution showing the positions of the elastic wave sources. More specifically, the elastic wave source distribution is a distribution in which the horizontal axis is set to the distance in the passing direction, the vertical axis is set to the distance in the width direction, and points showing the positions of the elastic wave sources are shown on virtual data representing the structure 50 to be evaluated.

[0074] 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 the distribution of the density value calculated according to the number of elastic wave sources contained in each region for each region predetermined in the elastic wave source distribution. Specifically, the distribution generating unit 424 first divides the elastic wave source distribution into a plurality of regions by dividing it into predetermined zones. 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 value of the density D 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 of the evaluation object region. In addition, in formula (1), Nev represents the number of elastic wave sources calibrated in the region, and S represents the area of ​​the region.

[0075] [Formula 1]

[0076]

[0077] The reference distribution generating unit 425 generates one or more reference distributions 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 a random number. The random number is a value for adding a random delay element to the arrival time of the elastic wave, and takes a value 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 for virtual setting. The elastic wave source density distribution generated by the simulation is a reference distribution.

[0078] The reference distribution generation unit 425 receives from the outside a speed condition indicating the propagation speed of the elastic wave of 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 each time a simulation is performed. The reference distribution generation unit 425 performs simulation based on the received conditions to calculate the time when the elastic wave reaches each sensor from the position of one or more elastic wave sources. At this time, the reference distribution generation unit 425 calculates the arrival time by adding a fluctuation in the time direction based on a random number to the theoretical time when the elastic wave reaches the position of each sensor from the position of each elastic wave source. The fluctuation in the time direction based on a random number is a random fluctuation in the time direction that is uniformly distributed within a predetermined time range. Thereafter, the reference distribution generation unit 425 performs position calibration based on the calculated difference in the time when the elastic wave reaches each sensor, and generates an elastic wave source density distribution based on the position calibration result. In addition, the method of position calibration is the same as the method used by the position calibration unit 423, and the method of generating the elastic wave source density distribution is the same as the method used by the distribution generation unit 424.

[0079] The reference distribution generation unit 425 generates a plurality of reference distributions by the above-mentioned method. For example, the reference distribution generation unit 425 generates a plurality of reference distributions that take into account fluctuations in the time direction based on the random numbers by using different random number values. The reference distribution generation unit 425 stores the generated plurality of reference distributions and the characteristic quantities related to the calibration accuracy of the elastic wave source density distribution in the storage unit 43 in correspondence. The characteristic quantities related to the calibration accuracy of the elastic wave source density distribution are indicators indicating the height of the calibration accuracy of the elastic wave source density distribution, such as the average value of the indicator of uncertainty of the position calibration result obtained for each predetermined area of ​​the elastic wave source density distribution, the median of the indicator of uncertainty of the position calibration result obtained for each predetermined area of ​​the elastic wave source density distribution, or the calibration rate.

[0080] The uncertainty index of the position calibration result is an index indicating the height of the accuracy of the position calibration, which means that the closer the value is to 0, the higher the accuracy of the position calibration. The calculation method of the uncertainty index of the position calibration result will be described later. The calibration rate indicates the ratio of the position calibration constant to the elastic wave source, for example, by dividing the number of collisions that will contribute to the position calibration by the total number of collisions, or by dividing the position calibration constant by the number of elastic wave sources.

[0081] The distribution selection unit 426 calculates the characteristic amount of the elastic wave source density distribution related to the calibration accuracy 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 the plurality of reference distributions stored in the storage unit 43 based on the calculated characteristic amount of the elastic wave source density distribution related to the calibration accuracy.

[0082] 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 for explanation. Specifically, the correction unit 427 compares the selected reference distribution with the elastic wave source density distribution, and performs correction in such a way that the density of the region in the elastic wave source density distribution is lower in a region with a higher density in the reference distribution, and performs correction in such a way that the density of the region in the elastic wave source density distribution is higher in a region with a lower density in the reference distribution. In this way, the correction unit 427 compares each predetermined size region at the same position in the reference distribution and the elastic wave source density distribution, and performs correction on each predetermined size region. In addition, the correction unit 427 can also perform correction by dividing the elastic wave source density distribution into a plurality of regions and performing operations such as subtraction and division on each divided region.

[0083] The evaluation unit 428 evaluates the degradation 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 where the density of the elastic wave source is greater than a threshold value in the corrected elastic wave source density distribution as a healthy region, and evaluates a region where the density of the elastic wave source is less than the threshold value as a damaged region.

[0084] The storage unit 43 stores the transmission data of the evaluation target 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 corresponding to the reference distribution and the feature quantity related to the calibration accuracy of the reference distribution are registered. The storage unit 43 is formed using a storage device such as a magnetic hard disk device or a semiconductor storage device.

[0085] The display unit 44 displays the evaluation result according to the control of the evaluation unit 428. As the evaluation result, for example, the display unit 44 can display the corrected elastic wave source density distribution, or can display the area regarded as the damaged area as another area by changing the display scheme. Furthermore, the display unit 44 displays the elastic wave source and the wavy line group representing the propagation path of the elastic wave to each sensor 20 according to the control of the evaluation unit 428, for example, by projection. The display unit 44 is an image display device such as a liquid crystal display, an organic EL (Electro Luminescence) display, etc. The display unit 44 can also be an interface for connecting the image display device to the structure evaluation device 40. In this case, the display unit 44 generates an image signal for displaying the evaluation result, and outputs the image signal to the image display device connected to itself.

[0086] (Method for measuring elastic waves)

[0087] Figure 3 FIG. 1 is a diagram for explaining the elastic wave measurement method in the first embodiment. Figure 4 As an example of a method for measuring elastic waves, consider evaluating the internal damage of a structure 50 based on the elastic waves generated by a running part W (e.g., a tire) of a vehicle 10 running on a road surface. Here, the case where the structure 50 is a road on which the vehicle 10 runs is described as an example. In addition, there is no particular limitation on the vehicle 10, and it may also be an ordinary running vehicle. By utilizing the elastic waves generated by an ordinary vehicle 10, there is no need to restrict the vehicle for inspection, which helps to improve the convenience of the user. The running part W of the vehicle 10 contacts the road surface, thereby applying a load to the road surface. As a result, elastic waves are generated in the structure 50. The generated elastic waves propagate inside the structure 50 and are detected by each sensor 20 provided on a surface different from the road surface (e.g., the bottom surface).

[0088] The structure 50 generally includes a paved portion 51 on which travel is possible and a bottom plate portion 52 supporting the paved portion 51. The paved portion 51 is, for example, asphalt, and the bottom plate portion 52 is, for example, concrete. The thickness of the ordinary paved portion 51 is about 80 mm, and the thickness of the bottom plate portion 52 is about 180 mm to 230 mm. The elastic wave (amplitude Asrc) generated by the interaction between the travel portion W of the vehicle 10 traveling on the road at a speed V and the surface of the paved portion 51 propagates toward the lower surface of the bottom plate portion 52. On the way, the elastic wave is partially reflected and partially transmitted at the interface 53 between the paved portion 51 and the bottom plate portion 52 due to the difference in acoustic impedance. Then, the elastic wave propagating to the lower surface of the bottom plate portion 52 reaches the sensor 20 and is detected by the sensor 20. A plurality of sensors 20 are provided on the lower surface of the bottom plate portion 52, and the elastic wave is detected by each sensor 20 with a different time difference. Based on the time difference when detected by each sensor, the position of the elastic wave source SR is calibrated.

[0089] (See how distribution is generated)

[0090] Next, use Figure 4 The flowchart shown in FIG. 1 illustrates a method for generating a reference distribution by the reference distribution generating unit 425 . Figure 4 4 is a flowchart showing the flow of the reference distribution generation process performed by the reference distribution generation unit 425 in the first embodiment. Figure 4 In FIG. 1 , an example is described in which a theoretical elastic wave source density distribution is simulated when uncertainty is mixed into the arrival time determination of impact data, assuming that a uniform elastic wave source exists, thereby generating a reference distribution.

[0091] The reference distribution generating unit 425 receives input of a velocity condition from the outside (step S11). The input velocity condition is preferably the same as the propagation velocity of the elastic wave of the evaluation target structure 50. For example, when the evaluation target structure 50 is concrete, the propagation velocity of the elastic wave is about 3000 m / s, so the reference distribution generating unit 425 receives input of the value of the propagation velocity of the elastic wave of 3000 m / s.

[0092] Next, the reference distribution generating unit 425 receives input of sensor conditions from the outside (step S12). The input sensor conditions are preferably the same as the installation positions of the sensors 20 installed in the structure 50 to be evaluated. In addition, the reference distribution generating unit 425 may also obtain information related to the installation positions of the sensors 20 represented by the sensor position information stored in the position calibration unit 423 as the sensor conditions. Here, the number of sensors is N (N is an integer greater than or equal to 1), and the sensor coordinates are S i (i=0,…,(N-1)).

[0093] Next, the reference distribution generation unit 425 accepts input of elastic wave source conditions from the outside (step S13). The number of elastic wave sources input as elastic wave source conditions is set to M, and M is set to 10000, for example. First, the reference distribution generation unit 425 randomly configures the j-th (j is an integer greater than or equal to 1) elastic wave source at one point in a two-dimensional space. The reference distribution generation unit 425 calculates the distance from the position where the elastic wave source is configured to the n-th sensor (step S14). Here, the distance between the position of the i-th sensor and the position of the j-th elastic wave source is set to d ij .

[0094] The generation time and amplitude of the elastic wave in the j-th elastic wave source are set as the generation time t j , amplitude a jIn the case of , the reference distribution generating unit 425 calculates the arrival time TOA of the impact data detected by the nth sensor based on the following equations (2) and (3): ij , amplitude A ij (Step S15 and Step S16). Here, α in Formula (2) is a distance attenuation coefficient (unit [dB / m]) indicating the influence 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 adds a noise term to the time window width k that determines the maximum value of the time delay. The noise term is a random number R that takes a random value in the range of 0 to 1 and multiplies each impact data. ij About R ij Therefore, the reference distribution generation unit 425 adds fluctuations in the time direction based on the random number to the theoretical time when the elastic wave reaches the position of each sensor from the position of each elastic wave source.

[0095] [Formula 2]

[0096] A ij =a j -α·d ij …(2)

[0097] [Formula 3]

[0098]

[0099] The generation time t of the jth elastic wave source in formula (3) is j For example, it can be set as shown in the following formula (4).

[0100] [Formula 4]

[0101]

[0102] Here, T in formula (4) s is a constant, for example, set to 5 [ms]. The amplitude a of the jth elastic wave source j For example, it can be set as in the following formula (5). src It is not limited to a constant, and is set to, for example, 100 [dB] (0 dB = 1 μV). j It is a random number or a pseudo-random number that takes a random value in the range of 0 to 1 for each elastic wave source.

[0103] [Formula 5]

[0104]

[0105] The reference distribution generating unit 425 can obtain the arrival time of the elastic wave generated from one elastic wave source at each sensor and the amplitude of the elastic wave according to the above order. The reference distribution generating unit 425 associates the obtained arrival time information with the information of the amplitude of the elastic wave and stores it as impact data. Afterwards, the reference distribution generating unit 425 determines whether the number of elastic wave sources set is M or more (step S17). For example, M is set to 10000 or more, so that the probability variation of the final reference distribution can be suppressed, so it is appropriate.

[0106] When it is determined that the number of elastic wave sources set by the reference distribution generating unit 425 is not greater than M (step S17-No), the reference distribution generating unit 425 performs the processing after step S13 again. In this case, the reference distribution generating unit 425 randomly arranges one point of the elastic wave source in the two-dimensional space in the processing of step S13. In this way, the reference distribution generating unit 425 repeatedly performs the processing of steps S13 to S16 until the number of elastic wave sources is greater than M, thereby generating a collision data group corresponding to the M elastic wave sources.

[0107] When it is determined that the number of elastic wave sources set by the reference distribution generation unit 425 is greater than M (step S17-yes), the reference distribution generation unit 425 ends the generation of impact data (step S18). The reference distribution generation unit 425 performs amplitude-based filtering on the impact data group corresponding to the M elastic wave sources stored (step S19). This is a process of excluding the impact data group that does not meet the predetermined threshold from the impact data. For example, the reference distribution generation unit 425 excludes the impact data with an amplitude less than 20 [dB] (0dB = 1μV). By performing such filtering, elastic waves that are highly attenuated and mixed with noise and are not detected in an actual environment are simulated. When the filtering is completed, the reference distribution generation unit 425 ends the generation process of the impact data (step S20).

[0108] The reference distribution generation unit 425 uses the impact data group that has not been filtered out to calibrate the position of the elastic wave source (step S21). In this way, the positions of multiple elastic wave sources are calibrated. After that, the reference distribution generation unit 425 uses the position information of multiple elastic wave sources obtained by the position calibration to generate an elastic wave source distribution. The reference distribution generation unit 425 uses the elastic wave source distribution to generate an elastic wave source density distribution. In this way, an elastic wave source density distribution that takes into account the fluctuation in the time direction based on a random number is generated as a reference distribution. The reference distribution generation unit 425 changes the random number and executes Figure 4The reference distribution generation unit 425 generates a plurality of reference distributions that take into account the fluctuation in the time direction of the random number. The reference distribution generation unit 425 outputs the generated plurality of reference distributions (step S22). For example, the reference distribution generation unit 425 stores the generated plurality of reference distributions in the storage unit 43.

[0109] FIG. 5A to FIG. 5F is a diagram showing an example of a reference distribution generated by the reference distribution generating unit 425 in the first embodiment. FIG. 5A to FIG. 5F In the graph, darker colors indicate lower density, and lighter colors indicate higher density. FIG. 5A to FIG. 5F The areas indicated by white have the highest density. Figure 5A is the reference distribution obtained when the time window width is set to k = 1 [μs], Figure 5B is the reference distribution obtained when the time window width is set to k = 10 [μs], Figure 5C is the reference distribution obtained when the time window width is set to k = 100 [μs], Figure 5D is the reference distribution obtained when the time window width is set to k = 200 [μs], Figure 5E is the reference distribution obtained when the time window width is set to k = 500 [μs], Fig. 5F This is a reference distribution obtained when the time window width is set to k=1000 [μs].

[0110] like FIG. 5A to FIG. 5F As shown, it can be seen that FIG. 5A to FIG. 5D In the case of Figure 5E as well as Fig. 5F The dummy pattern P1 is generated in the region where the dummy pattern P1 is generated. The density of the region where the dummy pattern P1 is generated is lower (darker) than the region where the dummy pattern P1 is not generated (white region). Figure 6 The relationship between the time window width k and the characteristic quantity of the elastic wave source density distribution related to the calibration accuracy is shown. Figure 6 , as an example of a characteristic quantity of elastic wave source density distribution related to calibration accuracy, the average value of uncertainty of the position calibration result and the calibration rate are shown. Figure 6 The line segment L1 in represents the change of the calibration rate relative to the value of the time window width k, and the line segment L2 represents the change of the average value of the uncertainty of the position calibration result relative to the value of the time window width k.

[0111] 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 position calibration result, and between the time window width k and the calibration rate. The larger the time window width k, the larger the average value of the uncertainty of the position calibration result, and the lower the calibration rate. The average value of the uncertainty of the position calibration result is a value that represents the degree of uncertainty of the position calibration result. The smaller it is, the higher the certainty of the position calibration result, and the larger it is, the less certain the position calibration result is. As mentioned above, refer to Figure 5E as well as Fig. 5F It can be seen that when k=500 [μs] or more, a clear pseudo pattern is generated. Figure 6 As shown in FIG. 1 , when k = 500 [μs], the average uncertainty of the position calibration result is approximately 500 [mm]. Figure 6 In , the mean value of the uncertainty of the position calibration results is related to the reference distribution.

[0112] (Calculation method of uncertainty index of position calibration result)

[0113] Next, use Figure 7A to Figure 7C , a method for calculating the uncertainty index of the position calibration result in the first embodiment is described. Fig. 7A As shown, it is assumed that an elastic wave is generated from the position of a certain 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 sensor 20-1 to 20-4. Here, the arrival time t1 to t4 of the elastic wave arriving at the sensors 20-1 to 20-4 is expressed as follows. In addition, tt1, tt2, tt3, and tt4 in the following represent propagation times.

[0114] t1=t0+tt1

[0115] t2=t0+tt2

[0116] t3=t0+tt3

[0117] t4=t0+tt4

[0118] exist Fig. 7A In FIG. 1 , assuming that the sensor 20 that first detects the elastic wave is the sensor 20 - 2 , the time difference between the time when the elastic wave reaches the sensor 20 - 2 that first detects the elastic wave and the time when the elastic wave reaches the other sensors 20 is expressed as follows.

[0119] Δt1=t1-t2

[0120] Δt2=t2-t2=0

[0121] Δt3=t3-t2

[0122] Δt4=t4-t2

[0123] The above Δt1 to Δt4 are observation values ​​at the time of arrival. By performing position calibration based on the observation values ​​Δt1 to Δt4 at the time of arrival, the elastic wave source SR1 is calibrated. The elastic wave source SR1 represents the position of the elastic wave source estimated based on the observation values. Figure 7C As shown, based on the positions of the sensors 20 - 1 to 20 - 4 and the position of the elastic wave source SR1 , distances d1 to d4 between the sensors 20 and the elastic wave source SR1 are calculated.

[0124] exist Figure 7C In FIG. 1 , assuming that the sensor 20 that is the shortest distance from the elastic wave source SR1 is the sensor 20 - 2 , the distance differences between the elastic wave source SR1 and each sensor 20 are expressed as follows.

[0125] Δd1=d1-d2

[0126] Δd2=d2-d2=0

[0127] Δd3=d3-d2

[0128] Δd4=d4-d2

[0129] The above Δd1 to Δd4 are calculated values ​​of the distance differences from the elastic wave source. Using the above observed values ​​and calculated values, the uncertainty of the positioning result is calculated based on the following equation (6). V in equation (6) represents the propagation velocity of the elastic wave.

[0130] [Formula 6]

[0131]

[0132] In formula (6), when the observed value and the calculated value are consistent, the uncertainty value of the position calibration result is 0. On the other hand, in formula (6), the farther the observed value and the calculated value are, the higher the uncertainty value of the position calibration result becomes. That is, in formula (6), the farther the observed value and the calculated value are, the lower the certainty of the position calibration result is.

[0133] Figure 8 1 is a sequence diagram showing the flow of the degradation state evaluation process performed by the structure evaluation system 100 in the first embodiment. Figure 8 The processing is executed, for example, in response to the vehicle 10 traveling on the structure 50 as the evaluation object.

[0134] When the vehicle 10 travels on the structure 50 as the evaluation object, the travel part of the vehicle 10 contacts the road surface. As a result, the elastic wave 11 is generated in the structure 50. The multiple sensors 20 respectively detect the elastic wave 11 generated in the structure 50 (step S101). The multiple sensors 20 respectively convert the detected elastic waves 11 into electrical signals and output them to the signal processing unit 30 (step S102). The electrical signals outputted from the multiple sensors 20 are amplified by an amplifier not shown in the figure. The amplified electrical signals are converted into digital signals by an A / D converter.

[0135] 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 uses the clock input during the input of the first gate signal to determine the arrival time of the elastic wave. The arrival time determination unit 303 outputs the determined elastic wave arrival time as time information to the transmission data generation unit 305. The arrival time determination unit 303 performs this processing on all the input digital signals.

[0136] The feature quantity extraction unit 304 of the signal processing unit 30 uses the noise removal signal as the digital signal input during the input of the first gate signal to extract the feature quantity of the noise removal signal (step S104). The feature quantity extraction unit 304 outputs the extracted parameter related to the feature quantity to the transmission data generation unit 305. The transmission data generation unit 305 generates transmission data including the sensor ID, time information, and the parameter related to the feature quantity (step S105). The output unit 307 sequentially outputs the transmission data to the structure evaluation device 40 (step S106).

[0137] 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 the transmission data in one event from the transmission data stored in the storage unit 43. The event extraction unit 422 outputs the extracted transmission data in one event to the position identification unit 423.

[0138] The position calibration unit 423 calibrates the position of the elastic wave source based on the sensor ID and time information contained in the transmission data output from the event extraction unit 422 and the pre-stored sensor position information (step S108). Specifically, the position calibration unit 423 first calculates the difference in arrival time when the elastic wave 11 arrives at the plurality of sensors 20. Next, the position calibration unit 423 uses the sensor position information and the information of the arrival time difference to calibrate the position of the elastic wave source.

[0139] The position calibration unit 423 performs the processing of step S108 each time the transmission data of one event is output from the event extraction unit 422 during the measurement period. Thus, the position calibration unit 423 calibrates the positions of the plurality of elastic wave sources. The position calibration unit 423 outputs the position information of the plurality of elastic wave sources to the distribution generation unit 424. The distribution generation unit 424 generates an elastic wave source distribution using the position information of the plurality of elastic wave sources output from the position calibration unit 423. Specifically, the distribution generation unit 424 generates an elastic wave source distribution by drawing the positions of the elastic wave sources represented by the obtained position information of the plurality of elastic wave sources onto virtual data.

[0140] The distribution generation unit 424 generates an elastic wave source density distribution using the generated elastic wave source distribution (step S109). Specifically, first, the distribution generation unit 424 divides the elastic wave source distribution into a plurality of zones by dividing it into predetermined zones. Next, the distribution generation unit 424 calculates the density of the elastic wave source for each zone. Then, the distribution generation unit 424 generates an elastic wave source density distribution by assigning the calculated value of the density of the elastic wave source for each zone to each zone. The distribution generation unit 424 outputs the generated elastic wave source density distribution to the distribution selection unit 426 and the correction unit 427.

[0141] The distribution selection unit 426 uses the elastic wave source density distribution output from the distribution generation unit 424 to calculate the characteristic quantity of the elastic wave source density distribution related to the calibration accuracy (step S110). For example, the distribution selection unit 426 calculates the average value of the uncertainty index of the position calibration result obtained for each predetermined area of ​​the elastic wave source density distribution as the characteristic quantity of the elastic wave source density distribution related to the calibration accuracy. In this case, the distribution selection unit 426 divides the elastic wave source density distribution into a plurality of areas. The distribution selection unit 426 calculates the value of the uncertainty of the position calibration result for each divided area. Then, the distribution selection unit 426 calculates the average value of the uncertainty value of the position calibration result calculated for each area.

[0142] The distribution selection unit 426 selects a reference distribution based on the calculated average value of the uncertainty index of the position calibration 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 the average value of the uncertainty index of the position calibration result closest to the calculated average value of the uncertainty index of the position calibration result is registered. The distribution selection unit 426 selects the reference distribution registered in the selected record. The distribution selection unit 426 outputs the selected reference distribution to the correction unit 427.

[0143] 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 as input. 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.

[0144] The evaluation unit 428 uses the corrected elastic wave source density distribution to evaluate the deterioration state of the structure (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). As the evaluation result, for example, the display unit 44 may display the corrected elastic wave source density distribution or may display the area regarded as the damaged area as another area by changing the display scheme.

[0145] In the structure evaluation system 100 constructed as described above, the damage of 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 the random numbers. That is, the reference distribution is a distribution that reflects the conditions of the actual environment. In the structure evaluation device 40, instead of using only the elastic wave source density distribution, an evaluation based on the elastic wave source density distribution is performed based on the conditions of the actual environment represented by the reference distribution. As a result, the deterioration state of the structure in a more actual environment can be evaluated. Therefore, the decrease in the evaluation accuracy of the deterioration state of the structure can be suppressed.

[0146] (Variation of the first embodiment)

[0147] In the above embodiment, the distribution selection unit 426 selects one reference distribution, but the distribution selection unit 426 may select a plurality of reference distributions. Fig. 9 , an overview of the processing in such a configuration is described. Fig. 9 4 is a diagram for explaining an overview of processing performed by the distribution selection unit 426 in a modified example of the first embodiment. First, the distribution selection unit 426 generates a plurality of divided regions by dividing the elastic wave source density distribution into a plurality of regions. Fig. 9 As shown in the figure above, the elastic wave source density distribution is divided into two based on the distance in the width direction. Thus, divided regions R1 and R2 based on the elastic wave source density distribution are generated. In addition, this is an example, and the direction in which the elastic wave source density distribution is divided and the number of divisions are not particularly limited.

[0148] Next, the distribution selection unit 426 calculates the feature quantity related to the calibration accuracy for each of the generated segmented regions R1 and R2. In addition, in the reference distribution table stored in the storage unit 43, the segmented regions of the reference distribution corresponding to the number of segmentations of the reference distribution and the feature quantity related to the calibration accuracy of each segmented region are associated with each other. The distribution selection unit 426 selects a different reference distribution for each of the segmented regions R1 and R2 based on the calculated feature quantity related to the calibration accuracy of each segmented region R1 and R2 and the reference distribution table.

[0149] Specifically, the distribution selection unit 426 compares the segmented areas of the elastic wave source density distribution and the segmented areas of the reference distribution in the same range. For example, the distribution selection unit 426 compares the feature quantity related to the calibration accuracy of the segmented area R1 of the elastic wave source density distribution with the feature quantity related to the calibration accuracy of the segmented area of ​​the reference distribution in the same range as the segmented area R1 of the elastic wave source density distribution. Fig. 9 In the example shown, there are reference distribution 1 and reference distribution 2, but the distribution selection unit 426 compares the feature quantity related to calibration accuracy of the segmented region R1 of the elastic wave source density distribution with the feature quantity related to calibration accuracy of the region R11 of the reference distribution 1, and compares the feature quantity related to calibration accuracy of the segmented region R1 of the elastic wave source density distribution with the feature quantity related to calibration accuracy of the region R21 of the reference distribution 1. Similarly, the distribution selection unit 426 compares the feature quantity related to calibration accuracy of the segmented region R2 of the elastic wave source density distribution with the feature quantity related to calibration accuracy of the region R12 of the reference distribution 1, and compares the feature quantity related to calibration accuracy of the segmented region R2 of the elastic wave source density distribution with the feature quantity related to calibration accuracy of the region R22 of the reference distribution 2.

[0150] Here, the distribution selection unit 426 determines that the feature quantity related to the calibration accuracy of the segmented region R1 of the elastic wave source density distribution is similar to the feature quantity related to the calibration accuracy of the region R11 of the reference distribution 1, and the feature quantity related to the calibration accuracy of the segmented region R2 of the elastic wave source density distribution is similar to the feature quantity related to the calibration 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 for correction of the segmented region R1 of the elastic wave source density distribution, and selects the region R22 of the reference distribution 2 as the reference distribution for correction of the segmented region R2. The distribution selection unit 426 outputs the selected region R11 of the reference distribution 1 and the selected region R22 of the reference distribution 2 to the correction unit 427.

[0151] The correction unit 427 receives as input the region R11 of the reference distribution 1 and the region R22 of the 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 the reference distribution 1 and the region R22 of the reference distribution 2. For example, the correction unit 427 corrects the segmented region R1 of the elastic wave source density distribution based on the region R11 of the reference distribution 1, and corrects the segmented region R2 of the elastic wave source density distribution based on the region R22 of the reference distribution 2.

[0152] (Second embodiment)

[0153] In the second embodiment, a configuration for selecting an appropriate reference distribution by template matching will be described.

[0154] Fig.10 1 is a diagram showing the structure of a structure evaluation system 100a in a second embodiment. The structure evaluation system 100a is used to evaluate the soundness of a structure 50. The structure evaluation system 100a includes a plurality of sensors 20-1 to 20-n (n is an integer greater than or equal to 2), a signal processing unit 30, and a structure evaluation device 40a. The structure evaluation system 100a is different from the structure evaluation system 100 in that it does not include the structure evaluation device 40 but includes the structure evaluation device 40a. The structure other than the structure evaluation device 40a is the same as the structure evaluation system 100. The following description will focus on the differences.

[0155] 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 functions as an acquisition unit 421, an event extraction unit 422, a position calibration unit 423, a distribution generation unit 424, a reference distribution generation unit 425, a distribution selection unit 426a, a calibration unit 427, and an evaluation unit 428 by executing a program.

[0156] The storage unit 43a stores the transmission data of the evaluation target period acquired by the acquisition unit 421 and the reference distribution table. The reference distribution table in the second embodiment is a table in which a plurality of reference distributions generated for each different random number 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.

[0157] The distribution selection unit 426a selects at least one reference distribution from the plurality of reference distributions based on the similarity between the elastic wave source density distribution generated by the distribution generation unit 424 and the plurality of reference distributions registered in the reference distribution table stored in the storage unit 43. More specifically, the distribution selection unit 426a performs template matching between the plurality of reference distributions and the elastic wave source density distribution, thereby calculating the similarity between the plurality of reference distributions and the elastic wave source density distribution, and selects the reference distribution with the highest similarity from the plurality of reference distributions. The distribution selection unit 426a outputs the selected reference distribution to the correction unit 427.

[0158] Fig.11 This is a sequence diagram showing the flow of the degradation state evaluation process performed by the structure evaluation system 100a in the second embodiment. Fig.11 The processing is performed, for example, when the vehicle 10 travels on the structure 50 to be evaluated. Fig.11 In, about Figure 8 Same process, append with Figure 8 The same symbols are used and their descriptions are omitted.

[0159] When the processing of step S101 to step S109 is 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 uses the elastic wave source density distribution to perform pattern matching with each reference distribution registered in the reference distribution table, thereby calculating the similarity for each reference 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.

[0160] The correction unit 427 receives as input 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.

[0161] According to the structure evaluation system 100a configured as described above, it is possible to obtain the same effects as those of the first embodiment by a method different from that of the first embodiment.

[0162] (Variation of the Second Embodiment)

[0163] In the above embodiment, the distribution selection unit 426a selects one reference distribution, but the distribution selection unit 426a may be configured to select multiple reference distributions. The outline of the processing in the case of such a configuration is described. Fig. 9The distribution selection unit 426a generates a plurality of segmented regions by dividing the elastic wave source density distribution into a plurality of regions. Fig. 9 As shown in the above figure, the elastic wave source density distribution is divided into two based on the distance in the width direction. Thus, segmented regions R1 and R2 based on the elastic wave source density distribution are generated. In addition, this is an example, and the direction in which the elastic wave source density distribution is divided and the number of divisions are not particularly limited. In addition, in the reference distribution table of the storage unit 43a, a plurality of reference distributions are registered.

[0164] The distribution selection unit 426a selects a different reference distribution for each segmented area R1, R2 based on each segmented area R1, R2 and the reference distribution table. Specifically, the distribution selection unit 426a performs pattern matching between the segmented area of ​​the elastic wave source density distribution and the area in the same range as the segmented area of ​​the elastic wave source density distribution in the reference distribution. For example, the distribution selection unit 426a performs pattern matching between the segmented area R1 of the elastic wave source density distribution and the areas R11 and R21 of the reference distribution that are in the same range as the segmented area R1 of the elastic wave source density distribution. Similarly, the distribution selection unit 426a performs pattern matching between the segmented area R2 of the elastic wave source density distribution and the areas R12 and R22 of the reference distribution that are in the same range as the segmented area R2 of the elastic wave source density distribution.

[0165] Here, the distribution selection unit 426a determines that the segmented region R1 of the elastic wave source density distribution has the highest similarity to the region R11 of the reference distribution 1, and the segmented region R2 of the elastic wave source density distribution has the highest similarity to the region R22 of the reference distribution 2. In this case, the distribution selection unit 426a selects the region R11 of the reference distribution 1 as the reference distribution for correction of the segmented region R1 of the elastic wave source density distribution, and selects the region R22 of the reference distribution 2 as the reference distribution for correction of the segmented region R2. The distribution selection unit 426a outputs the selected region R11 of the reference distribution 1 and the selected region R22 of the reference distribution 2 to the correction unit 427.

[0166] The correction unit 427 receives as input the region R11 of the reference distribution 1 and the region R22 of the 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 the reference distribution 1 and the region R22 of the reference distribution 2. For example, the correction unit 427 corrects the segmented region R1 of the elastic wave source density distribution based on the region R11 of the reference distribution 1, and corrects the segmented region R2 of the elastic wave source density distribution based on the region R22 of the reference distribution 2.

[0167] (Modification 1 common to each embodiment)

[0168] In the above embodiments, a plurality of sensors 20-1 to 20-n are connected to one signal processing unit 30, 30a, 30b. The structure evaluation system 100, 100a, 100b may include a plurality of signal processing units 30, 30a, 30b, and each sensor 20 may be connected to a different signal processing unit 30, 30a, 30b.

[0169] (Modification 2 common to each embodiment)

[0170] Part or all of the functional units of the structure evaluation devices 40 and 40b may be provided by other devices. For example, the display unit 44 provided by the structure evaluation devices 40 and 40b may be provided by other devices. In such a configuration, the structure evaluation devices 40 and 40b send the evaluation results to other devices provided with the display unit 44. The other devices provided with the display unit 44 display the received evaluation results.

[0171] (Variation 3 common to each embodiment)

[0172] In each of the above embodiments, a structure is shown in which a reference distribution is generated based on a simulation in which a delay corresponding to a random number is applied to the arrival time of an elastic wave. In contrast, in the 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 for the theoretical amplitude of the elastic wave reaching each sensor set in the simulation. Fig. 12A as well as Fig. 12B The following will be described in detail. Fig. 12A is a diagram showing an example of elastic wave detection by each sensor in the simulation of each of the above-mentioned embodiments, Fig. 12B FIG. 1 is a diagram showing an example of elastic wave detection by each sensor in a simulation in a modified example of each embodiment. Fig. 12A as well as Fig. 12B In the figure, the vertical axis represents amplitude and the horizontal axis represents time.

[0173] like Fig. 12A As shown in FIG. 1 , each sensor in the simulation detects the elastic wave at the timing when the amplitude of the elastic wave exceeds the threshold. Here, when noise is added to the elastic wave, as shown in FIG. Fig. 12B As shown, the amplitude of the elastic wave is Fig. 12A The amplitude of the elastic wave shown is low. Therefore, even if the threshold for detecting elastic waves is the same, Fig. 12B The amplitude of the elastic wave is also low, so the timing when the amplitude of the elastic wave exceeds the threshold is Fig. 12A That is, in Fig. 12B In the case of elastic waves, the timing ratio of Fig. 12AThis means that the delay corresponding to the random number is substantially the same as in the above-mentioned embodiments, which is applied to the arrival time of the elastic wave. Therefore, the reference distribution generation unit 425 may also add noise to the elastic waves arriving at each sensor in the simulation in such a way that the amplitude is reduced according to the random number, and generate a reference distribution in a manner that matches the actual environment.

[0174] (Variation 4 common to all embodiments)

[0175] In the first embodiment, a structure is shown in which a reference distribution is selected based on a feature quantity related to calibration accuracy, and in the second embodiment, a structure is shown in which a reference distribution is selected based on a similarity of pattern matching. It is also possible to configure the first embodiment and the second embodiment to select a reference distribution in combination. In such a configuration, the structure evaluation device 40, 40a can also switch which method in the first embodiment or the second embodiment is used as the method for selecting a reference distribution according to the setting.

[0176] Furthermore, the structure evaluation apparatus 40, 40a may use a different method of selecting a reference distribution for each segmented region obtained by segmenting the elastic wave source density distribution. Fig. 9 As illustrated in the example shown, the structure evaluation device 40, 40a may utilize the selection method shown in the first embodiment (a selection method based on a feature value related to calibration accuracy) for the segmented area R1 of the elastic wave source density distribution, and utilize the selection method shown in the second embodiment (a selection method based on pattern matching) for the segmented area R2 of the elastic wave source density distribution, and select a different reference distribution for each segmented area.

[0177] According to at least one embodiment described above, there is a position calibration unit 423 for calibrating the position of one or more elastic wave sources based on multiple sensors 20 for detecting elastic waves generated inside the structure 50 and multiple elastic waves respectively detected by the multiple sensors 20, a distribution generation unit 424 for generating a density distribution of the elastic wave sources based on the position calibration results of the one or more elastic wave sources obtained by the position calibration unit 423, and an evaluation unit 428 for evaluating damage to the structure 50 based on one or more reference distributions generated according to a simulation including random numbers and the elastic wave source density distribution generated by the distribution generation unit 424, thereby suppressing a decrease in the evaluation accuracy of the degradation state of the structure.

[0178] Several embodiments of the present invention are described, but 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 ways, and can be omitted, replaced, and changed in various ways without departing from the scope of the gist of the invention. These embodiments and their variations are included in the scope and gist of the invention, and are included in the invention described in the patent claims and their equivalents.

Claims

1. A structure evaluation system comprising: A plurality of sensors for detecting elastic waves generated inside the structure; a position calibration unit that calibrates the position of one or more elastic wave generation sources based on the plurality of elastic waves detected by the plurality of sensors; a distribution generating unit that generates an elastic wave source density distribution indicating a density distribution of the one or more elastic wave generation sources based on the position calibration results of the one or more elastic wave generation sources obtained by the position calibration unit; and 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 generation unit.

2. The structure evaluation system according to claim 1, wherein: The structure evaluation system further includes a reference distribution generating unit that generates the one or more reference distributions. The simulation is a simulation in which, based on one or more elastic wave generation sources set virtually, an elastic wave source density distribution representing the density distribution of the one or more elastic wave generation sources is generated as the one or more reference distributions, The reference distribution generating unit accepts input of information on one or more sources of elastic waves and information on the installation positions of multiple sensors as conditions for performing the simulation, and performs the simulation by adding fluctuations in the time direction based on random numbers to the theoretical moments when the elastic waves arrive at each sensor from the accepted sources of elastic waves, or by adding noise corresponding to random numbers to the theoretical amplitudes when the waves arrive at each sensor from the sources of elastic waves in the amplitude direction, thereby generating the one or more reference distributions.

3. The structure evaluation system according to claim 2, wherein: The fluctuation in the time direction based on the random number is a random fluctuation in the time direction uniformly distributed within a predetermined time range, The reference distribution generating unit generates the one or more reference distributions by adding fluctuations in the time direction based on the random number that is different for each of the predetermined time ranges.

4. The structure evaluation system according to any one of claims 1 to 3, wherein: The structure evaluation system further includes 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 correction in such a way that a region with a higher density in the one or more reference distributions has a lower density in the elastic wave source density distribution, and performs correction in such a way that a region with a lower density in the one or more reference distributions has a higher density in the elastic wave source density distribution, The evaluation unit evaluates damage to the structure using the elastic wave source density distribution corrected by the correction unit.

5. The structure evaluation system according to claim 4, wherein: The one or more reference distributions are multiple reference distributions generated under different conditions. The structure evaluation system further includes a distribution selection unit that selects at least one reference distribution from among the plurality of reference distributions based on a feature quantity related to calibration 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.

6. The structure evaluation system according to claim 5, wherein: The characteristic quantity related to the calibration accuracy is any one of the average value of the uncertainty index of the position calibration result within the predetermined area of ​​the elastic wave source density distribution, the median of the uncertainty index of the position calibration result, or the calibration rate within the predetermined area of ​​the elastic wave source density distribution.

7. The structure evaluation system according to claim 5, wherein: 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 feature quantity related to calibration accuracy of each generated divided region.

8. The structure evaluation system according to claim 4, wherein: The one or more reference distributions are multiple reference distributions generated under different conditions. The structure evaluation system further includes a distribution selection unit that selects at least one reference distribution from among the plurality of reference distributions based on similarities 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.

9. The structure evaluation system according to claim 8, wherein: The distribution selection unit calculates similarities 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 among the plurality of reference distributions.

10. The structure evaluation system according to claim 8, wherein: 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 degree of similarity between each of the generated divided regions and the plurality of reference distributions.

11. A structure evaluation device comprising: A position calibration unit calibrates the position of one or more elastic wave generation sources based on a plurality of elastic waves respectively detected by a plurality of sensors for detecting elastic waves generated inside the structure; a distribution generating unit that generates an elastic wave source density distribution indicating a density distribution of the one or more elastic wave generation sources based on the position calibration results of the one or more elastic wave generation sources obtained by the position calibration unit; and 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 generation unit.

12. A method for evaluating a structure, wherein: The position of one or more sources of the elastic waves is determined based on a plurality of elastic waves detected by a plurality of sensors that detect the elastic waves generated inside the structure. generating an elastic wave source density distribution indicating the density distribution of the one or more elastic wave generation sources based on the position calibration results of the one or more elastic wave generation sources, Damage to the structure is evaluated based on one or more reference distributions generated based on simulations including random numbers and the elastic wave source density distribution.

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