Damage detection device, damage detection system, and method for detecting damage

Abstract

To provide a damage detection device, a damage detection system, and a method for detecting damage that can improve the degree of freedom of sensors used for estimating the depth of damage and reduce sensor cost.SOLUTION: In an embodiment, a damage detection device includes a detection unit, a spectrum calculation unit, and a depth calculation unit. The detection unit detects an alternating current component of an envelope line by using at least one elastic wave generated by an impact applied to a structure. The spectrum calculation unit calculates a frequency spectrum on the basis of the detected alternating current component of the envelope line. The depth calculation unit calculates the depth of damage existing inside the structure on the basis of the frequency spectrum.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] FIELD Embodiments of the present invention relate to a damage detection device, a damage detection system, and a damage detection method. [Background technology]

[0002] In recent years, problems associated with the aging of industrial equipment and structures have become apparent. Because the damage caused by an accident involving industrial equipment or structures is immeasurable, technologies for monitoring the condition of industrial equipment and structures have been developed. In particular, inspection methods using elastic waves have been proposed for the purpose of detecting internal damage and the depth of the damage in concrete structures. One known inspection method using elastic waves is the impact echo method, which applies a predetermined impact to a concrete structure and detects the depth of the damage based on the peak frequency of the spectrum of the elastic wave generated by the impact.

[0003] Non-Patent Document 1 discloses the principles of the impact echo (IE) method. Patent Document 1 also discloses a method for visualizing internal damage using the principles of the impact echo method. A method for estimating the depth of damage based on the peak frequency due to longitudinal wave resonance of impact elastic waves and a known velocity requires a dedicated sensor with flat frequency characteristics in the frequency range from low frequencies to the acceleration sensor band. Therefore, it was not possible to use high-frequency sensors (e.g., AE (Acoustic Emission) sensors) whose accurate frequency characteristics in the acceleration sensor band are unknown, or low-cost sensors that have not been precisely calibrated.

[0004] As described above, a dedicated sensor is required to estimate the depth of damage, which may increase costs. Thus, in the past, the sensors used to estimate the depth of damage were sometimes limited to dedicated sensors. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Publication No. 2021-181919 [Non-patent literature]

[0006] [Non-Patent Document 1] Nicholas J. CARINO, “Impact Echo: The Fundamentals”, International Symposium Non-Destructive Testing in Civil Engineering (NDT-CE), 15-17 Sep 2015, Berlin, Germany. Summary of the Invention [Problem to be solved by the invention]

[0007] The problem to be solved by the present invention is to provide a damage detection device, a damage detection system, and a damage detection method that can improve the degree of freedom of sensors used to estimate damage depth and reduce sensor costs. [Means for solving the problem]

[0008] A damage detection device according to an embodiment includes a detection unit, a spectrum calculation unit, and a depth calculation unit. The detection unit detects AC components of an envelope using one or more elastic waves generated by an impact on a structure. The spectrum calculation unit calculates a frequency spectrum based on the detected AC components of the envelope. The depth calculation unit calculates the depth of damage present inside the structure based on the frequency spectrum. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram for explaining the difference between an AE sensor and a sensor used in the impact echo method. [Figure 2] FIG. 10 is a diagram showing simulation results of observed signals. [Figure 3]FIG. 1 is a diagram showing the configuration of a damage detection system according to a first embodiment. [Figure 4] FIG. 2 is a diagram showing an example of the configuration of a signal processing unit according to the first embodiment. [Figure 5] 3A and 3B are diagrams for explaining the difference between a conventional bandpass filter and the filter according to the first embodiment. [Figure 6] FIG. 3 is a diagram for explaining the dependency of the filter characteristics of a filter according to the first embodiment. [Figure 7] FIG. 3 is a diagram for explaining the dependency of the bandwidth characteristics of a filter in the first embodiment. [Figure 8] 5A and 5B are diagrams showing detection results of a reflection frequency according to a center frequency fc of a filter in the first embodiment. [Figure 9] 4 is a flowchart showing the flow of damage detection processing performed by the damage detection device according to the first embodiment. [Figure 10] 3A and 3B are diagrams showing signal waveforms resulting from damage detection processing performed by the damage detection device according to the first embodiment. [Figure 11] FIG. 1 shows frequency spectra obtained by the present method and the conventional impact-echo method for an actual structure. [Figure 12] FIG. 10 is a diagram showing the configuration of a damage detection system according to a second embodiment. [Figure 13] FIG. 10 is a diagram showing an example of the configuration of a signal processing unit according to a second embodiment. DETAILED DESCRIPTION OF THE INVENTION

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

[0011] (Principle of damage depth estimation using multiple reflections) First, before describing the contents of the embodiment, the principle of damage depth estimation using multiple reflections will be described. Conventionally, a depth estimation method using multiple reflections of elastic waves as shown in Non-Patent Document 1 has been proposed as a method for estimating damage depth. The damage depth means the depth from a certain surface (for example, the surface of the structure) to the position where the damage exists inside the structure. In the following description, the depth from the surface where an impact is applied to the structure to the position where the damage exists will be described as the damage depth.

[0012] In the method shown in Non-Patent Document 1, elastic waves are generated inside a structure by applying a sufficiently wide-band, high-intensity impact to the structure. The elastic waves generated inside the structure are subjected to multiple reflections at the internal voids of the structure and at the interface with the air. The speed of the elastic waves propagating inside the structure (elastic wave velocity) is defined as C p Then, the vibration waveform detected by the sensor installed on the surface of the structure has the elastic wave velocity C p A peak appears at a period of Δt, the travel time of the wave propagated by the ion. Therefore, the frequency f of the observed vibration is expressed as the following equation (1).

[0013]

number

[0014] That is, the elastic wave velocity C p If is known, the depth T at which reflection occurs can be expressed as the following equation (2):

[0015]

number

[0016] The frequency f in equation (2) can be obtained by performing a fast Fourier transform (FFT) on the vibration waveform observed by the sensor. Other methods such as the maximum entropy method (MEM) may also be used to calculate the frequency f.

[0017] The method described in Non-Patent Document 1 is based on the premise that the frequency characteristics of the sensor are flat. However, there are cases where the frequency characteristics of the sensor are not flat. When the frequency characteristics of the sensor are not flat, the spectrum of the time-series vibration waveform observed by the sensor is a spectrum in which the frequency spectrum of the elastic wave is added with the unknown frequency characteristics of the sensor. Unless the frequency spectrum of the sensor is known in advance, the frequency spectrum of the elastic wave is also unknown. It is clear that the method described in Non-Patent Document 1 implicitly assumes that the sensor has flat frequency characteristics, and therefore considers that the spectrum of the time-series vibration waveform observed by the sensor matches the frequency spectrum of the elastic wave.

[0018] (When using a sensor with unknown frequency characteristics: AE sensor example) If sensors with unknown frequency characteristics could be used, the sensor options would be expanded, which would be beneficial in terms of cost and convenience. One example of a sensor with a non-flat frequency characteristic is a resonant AE sensor. However, the frequency bands detected by AE sensors and those used in the impact echo method are different. For this reason, it is difficult to identify the reflected frequency using the signal detected by the AE sensor as is. This point will be explained in detail using Figure 1.

[0019] Figure 1 is a diagram illustrating the difference between an AE sensor and a sensor used in the impact-echo method. Figure 1(A) shows the waveform of an elastic wave detected by an AE sensor, and Figure 1(B) shows the waveform of an elastic wave detected by a sensor (displacement sensor) used in the impact-echo method. Figure 1(C) shows the frequency spectrum of the elastic wave detected by the AE sensor, and Figure 1(D) shows the frequency spectrum of the elastic wave detected by the sensor used in the impact-echo method. Figures 1(A) and 1(B) show elastic waves obtained by applying an impact with a steel ball to the same location on a 0.36m thick concrete structure.

[0020] As shown in Figure 1(A) and Figure 1(B), even though the sensors receive nearly the same elastic waves, the detected waveforms are significantly different due to the different frequency characteristics of the sensors. This is due to the difference in frequency sensitivity characteristics between the AE sensor and the sensor used in the impact echo method. The AE sensor is sensitive to high frequencies above 20 kHz, while the sensor used in the impact echo method (displacement sensor) has a flat sensitivity characteristic in the low-frequency range.

[0021] The multiple reflection frequency between the surface where the sensor is installed and the opposite surface of the structure (the surface opposite the surface where the sensor is installed) should be approximately 3.5 kHz according to the relationship in equation (1) above, assuming a structure thickness of 0.36 m and an elastic wave velocity of 2500 m / s. As shown in Figure 1(D), the multiple reflection frequency obtained by the sensor (displacement sensor) used in the impact-echo method peaks around 3.5 kHz, indicating that the reflected signal from the opposite surface was detected. On the other hand, as shown in Figure 1(C), the spectrum of the AE sensor has a peak around 30 kHz, making it impossible to identify the multiple reflection frequency from the peak frequency. In other words, it is difficult to identify the multiple reflection frequency based on the signal detected by the AE sensor using conventional impact-echo methods.

[0022] (Overview of this method) Next, a method for identifying multiple reflection frequencies using an AE sensor will be described. Note that in the following description, an AE sensor will be used as an example, but the present invention is not limited to an AE sensor, and other sensors with unknown frequency characteristics may also be used. Furthermore, the following description will be given using an example of an impact on a structure caused by a steel ball striking the structure.

[0023] The shorter the contact time of the steel ball, the closer the time function of the impact force approaches a delta function, and its Fourier spectrum contains a wide range of frequency components. c can be calculated using the diameter D of the steel ball according to Herz's contact theory as shown in the following formula (3).

[0024]

number

[0025] Therefore, it can be seen that the frequency characteristics of the elastic wave generated by hitting the steel ball depend on the diameter of the steel ball. Furthermore, the upper frequency limit f max has been related to the diameter D of the steel ball by Sansalone et al. as the following equation (4).

[0026]

number

[0027] As an example, when a steel ball with a diameter of 5 mm is used, the upper frequency limit is 58.2 kHz. This suggests that the frequency includes components with frequencies higher than the resonant frequency of 10 kHz to 50 kHz of the AE sensor used for concrete. Therefore, the inventors focused on detecting the excited elastic waves as a narrowband signal within the range of sensitivity of the AE sensor.

[0028] center frequency f c Consider the case where an elastic wave given as a narrowband burst signal of is reflected multiple times on the surface opposite to the surface on which it is applied. Figure 2 shows the time waveform of the simulated observed signal. Figure 2 shows the simulation results of the observed signal. Thickness T r The frequency of the signal reflected multiple times is f r Then, the burst signal has a period of 1 / f r It is observed repeatedly while decaying with f r = 1000Hz in the following explanation.

[0029] First, in this method, the observed signal is treated as a narrowband signal by the first bandpass filter. At this time, the center frequency of the first bandpass filter is, for example, 20 kHz. This is because the reflected frequency f r The frequency is sufficiently higher than the reflection frequency f rIt should be noted that the first bandpass filter does not need to have sensitivity in this band. Next, the observed signal that has been filtered by the first bandpass filter is subjected to processing to obtain the absolute value or square of the observed signal. Next, the second bandpass filter is used to detect the envelope of the observed signal and extract the AC component of the detected envelope. Here, the second bandpass filter is a filter that passes frequencies from 1 kHz to 10 kHz.

[0030] The second band-pass filter may be configured by connecting in series a low-pass filter with a cutoff frequency of 10 kHz for extracting the envelope and a high-pass filter with a cutoff frequency of 1 kHz for cutting the DC component in order to extract the AC component of the envelope. The second band-pass filter may also use a Hilbert transform to extract the envelope. In this case, the second band-pass filter may be configured by connecting in series a transform unit that performs a Hilbert transform on the observed signal and a high-pass filter that removes the DC component of the envelope obtained by the Hilbert transform.

[0031] Then, the AC component of the obtained envelope is Fourier transformed to obtain a reflection spectrum. This reflection spectrum includes the reflection frequency f r This reflection spectrum is equivalent to the spectrum obtained by a sensor with low frequency sensitivity, and can be treated in the same way as the spectrum obtained by the conventional impact echo method. In other words, based on the peak frequency of the reflection spectrum obtained by this procedure, the damage depth T can be easily calculated using equation (1). Here, the elastic wave velocity C p is assumed to be known, but the elastic wave velocity C p may be calculated by an existing method.

[0032] The above is the flow of the depth estimation process in this embodiment. A specific configuration for realizing the above process will now be described.

[0033] (First embodiment) 3 is a diagram showing the configuration of a damage detection system 100 according to the first embodiment. The damage detection system 100 is used to detect damage occurring inside a structure 50. The damage detection system 100 according to the first embodiment detects at least the depth (depth of damage) of an area where damage has occurred inside the structure 50 (hereinafter referred to as the "damaged area").

[0034] In the following description, the structure 50 is a bridge, but the structure 50 does not have to be limited to a bridge. The structure 50 may be any structure in which elastic waves are generated due to the occurrence or growth of a crack or an external impact (for example, rain, artificial rain, etc.). Note that bridges are not limited to structures built over rivers or valleys, but also include various structures built above the ground (for example, highway viaducts). Note that the target of damage detection is not particularly limited as long as it is a plate-like member rather than a structure.

[0035] The damage detection system 100 includes an impact applying unit 10, one or more sensors 20-1 to 20-n (n is an integer equal to or greater than 1), and a damage detection device 25. Each of the sensors 20-1 to 20-n is connected to the damage detection device 25 via a wire so that they can communicate with each other. In the following description, when there is no need to distinguish between the sensors 20-1 to 20-n, they will be referred to as sensors 20.

[0036] The impact applying unit 10 is installed, for example, on the same surface as the surface on which the sensor 20 is installed, and applies an impact to the structure 50. The impact applying unit 10 applies an impact to the structure 50, for example, by striking the structure 50. As described above, it is desirable that the impact applying unit 10 applies an impact that can generate a signal having a high frequency that can be detected by an AE sensor.

[0037] The method by which the impact applying unit 10 applies an impact to the structure 50 is not limited to using a steel ball, and any other type of impact may be applied to the structure 50 as long as it is an impact that can generate a high-frequency signal that can be detected by an AE sensor. The impact applying unit 10 applies an impact to the structure 50 by, for example, using a steel ball, core compression, or pulse excitation using a piezoelectric element. The impact applying unit 10 may be installed on a surface different from the surface on which the sensor 20 is installed. The surface different from the surface on which the sensor 20 is installed may be, for example, the surface opposite to the surface on which the sensor 20 is installed, a side surface of the structure 50, or the like.

[0038] Even when the impact applying unit 10 is installed on a surface different from the surface on which the sensor 20 is installed, the impact applying unit 10 applies an impact to generate an elastic wave, and the generated elastic wave is multiple-reflected and can be detected by the sensor 20. Therefore, the same effect can be obtained as when the impact applying unit 10 is installed on the same surface as the surface on which the sensor 20 is installed.

[0039] The sensor 20 has a piezoelectric element and detects elastic waves reflected from the inside or end surface of the structure 50. The sensor 20 is installed at a position on the surface of the structure 50 where it can detect elastic waves. For example, the sensors 20-1 to 20-n are installed on any one of the road surface, side surface, and bottom surface, spaced apart at equal or different intervals in the vehicle axis direction and in a direction perpendicular to the vehicle axis. The vehicle axis direction refers to the direction in which the vehicle travels on the road surface. The direction perpendicular to the vehicle axis direction refers to a direction perpendicular to the vehicle axis direction. The sensor 20 converts the detected elastic waves into an electrical signal. In the following explanation, a case in which the sensor 20 is installed on the bottom surface of the structure 50 will be described as an example.

[0040] The sensor 20 uses a piezoelectric element having sensitivity in the range of, for example, 10 kHz to 1 MHz. There are various types of sensors 20, such as a resonance type that has a resonance peak within a frequency range and a wideband type that suppresses resonance, but any type of sensor 20 may be used. The method by which the sensor 20 detects elastic waves includes a voltage output type, a resistance change type, and a capacitance type, but any detection method may be used. The sensor 20 is, for example, an AE sensor.

[0041] The sensor 20 is not limited to an AE sensor, and any other sensor with unknown frequency characteristics may be used. For example, an acceleration sensor may be used instead of the sensor 20. In this case, the acceleration sensor detects elastic waves generated inside the structure 50. The acceleration sensor then converts the detected elastic waves into an electrical signal by performing the same processing as the sensor 20.

[0042] The damage detection device 25 detects at least the depth of damage present inside the structure 50 based on the elastic waves detected by each sensor 20. The damage detection device 25 includes a signal processing unit 30, a spectrum calculation unit 40, and a depth calculation unit 45. While FIG. 3 shows the signal processing unit 30, the spectrum calculation unit 40, and the depth calculation unit 45 contained in a single housing, the signal processing unit 30, the spectrum calculation unit 40, and the depth calculation unit 45 may be installed in close proximity or remote locations. For example, the spectrum calculation unit 40 and the depth calculation unit 45 may be included in an information processing device as a function of a personal computer or the like. When the spectrum calculation unit 40 and the depth calculation unit 45 are included as a function of the information processing device, the spectrum calculation unit 40 and the depth calculation unit 45 are functions realized by executing a program. In this case, the signal processing unit 30 and the information processing device are connected to each other so as to be able to communicate with each other via wire or wirelessly.

[0043] The signal processing unit 30 receives the electrical signal output from the sensor 20. The signal processing unit 30 performs signal processing on the input electrical signal. The signal processing performed by the signal processing unit 30 includes, for example, detecting AC components of the envelope. The signal processing unit 30 outputs information indicating the detected AC components of the envelope to the spectrum calculation unit 40.

[0044] The signal processing unit 30 is configured using a digital circuit. The digital circuit is realized, for example, by an FPGA (Field Programmable Gate Array) or a microcomputer. The digital circuit may also be realized by a dedicated LSI (Large-Scale Integration). The signal processing unit 30 may also be equipped with a non-volatile memory such as a flash memory or a removable memory. In the following description, the case where the signal processing unit 30 is configured using a digital circuit will be described.

[0045] The spectrum calculation unit 40 receives as input information indicating the AC components of the envelope output from the signal processing unit 30. The spectrum calculation unit 40 calculates a frequency spectrum based on the input information indicating the AC components of the envelope.

[0046] The depth calculation unit 45 calculates the depth inside the structure 50 where damage has occurred, based on the frequency spectrum calculated by the spectrum calculation unit 40.

[0047] 4 is a diagram showing an example of the configuration of the signal processing unit 30 in the first embodiment. The signal processing unit 30 includes a waveform acquisition unit 31, a filter 32, a detection unit 33, and an output unit .

[0048] The waveform acquisition unit 31 is composed of an amplifier, an analog filter, and an analog-digital converter. The amplifier amplifies the electrical signal (analog signal) output from the sensor 20 to a level that allows it to be processed in the analog-digital converter. The amplifier outputs the amplified electrical signal to the analog filter. The analog filter removes noise components outside a predetermined band. The analog filter is, for example, a band pass filter (BPF). The band pass filter used here desirably has a pass bandwidth that is sufficiently wide so as not to distort the shape of the elastic wave (AE signal). The electrical signal from which noise has been removed by the analog filter is input to the analog-digital converter. The analog-digital converter quantizes the electrical signal from which noise has been removed and converts it into a digital signal. The analog-digital converter outputs waveform data, which is a digital signal, to the filter 32.

[0049] The filter 32 converts the waveform data output from the waveform acquisition unit 31 into a narrowband signal by performing a filtering process on the waveform data. The filter 32 is a bandpass filter, and is configured to convert the waveform data into a narrowband signal based on, for example, the thickness T of the structure 50 and the propagation velocity C of the elastic wave propagating inside the structure 50. p The reflection frequency f is calculated based on r (f r =C p The center frequency of the sensor 20 is set to a frequency higher than the reflection frequency f r It should be noted that it is not necessary for the sensor to have sensitivity in this band.

[0050] The filter 32 can switch the center frequency and bandwidth in response to an external command. For example, the center frequency of the filter 32 can be switched depending on the depth of the damage. The bandwidth of the filter 32 is preferably 100 Hz or more. The filter 32 is one aspect of a first band-pass filter.

[0051] The detection unit 33 detects the AC component of the envelope using the waveform data (narrowband signal) that has been filtered by the filter 32. The detection unit 33 is composed of, for example, a processing unit 35 and a filter 36. The processing unit 35 performs processing to take the absolute value or square of the filtered waveform data. The filtered waveform data is data that has amplitude in both positive and negative directions. Therefore, the processing by the processing unit 35 converts the filtered waveform data into data that has amplitude in the positive direction.

[0052] Filter 36 detects an envelope using waveform data processed by processing unit 35 and detects AC components of the detected envelope. Filter 36 is a band-pass filter, and passes, for example, a frequency band lower than that of filter 32. Filter 36 passes, for example, a frequency band of 1 kHz to 10 kHz. Filter 36 may be configured by connecting a low-pass filter and a high-pass filter in series. In this case, the low-pass filter is a filter with a cutoff frequency (e.g., 10 kHz) set for extracting the envelope, and the high-pass filter is a filter with a cutoff frequency (e.g., 1 kHz) set for cutting DC components in order to extract the AC components of the envelope. Filter 36 is one aspect of a second band-pass filter.

[0053] The detection unit 33 may be configured with a combination of a conversion unit 37 and a high-pass filter 38, instead of the combination of the processing unit 35 and the filter 36. The conversion unit 37 performs a Hilbert transform on the waveform data processed by the processing unit 35. The high-pass filter 38 is a filter with a cutoff frequency set to cut off the DC component of the envelope obtained by the conversion unit 37.

[0054] The output unit 34 generates transmission data including information indicating the AC component of the envelope extracted by the detection unit 33. The output unit 34 transmits the generated transmission data to the spectrum calculation unit 40 via wire or wirelessly.

[0055] FIG. 5 is a diagram illustrating the difference between a conventional bandpass filter and the filter 32 in the first embodiment. In FIG. 5, line segment L1 indicates the frequency band passed by the conventional bandpass filter, and line segment L2 indicates the frequency band passed by the filter 32. The conventional bandpass filter passes a relatively wide frequency band to remove noise, whereas the filter 32 passes a relatively narrow frequency band to convert waveform data into a narrowband signal. As shown in FIG. 5, the filter 32 passes a frequency band having a center frequency f c The frequency band ranging from Fc-(BW / 2) to Fc+(BW / 2) is passed, where Fc is the center frequency and BW is the bandwidth.

[0056] Next, the dependency of the filter characteristics of the filter 32 will be described with reference to FIG. 6. FIG. 6 is a diagram for explaining the dependency of the filter characteristics of the filter 32 in the first embodiment. The horizontal axis in (A) to (D) of FIG. 6 represents the true reflection frequency, and the vertical axis represents the reflection frequency estimated by the method in the embodiment. In (A) to (D) of FIG. 6, the center frequency f of the filter 32 is shown in the order of (A) to (D) of FIG. 6. c 10 shows the relationship between the true reflection frequency when the value of the reflection frequency is increased and the reflection frequency estimated by the method of the embodiment.

[0057] In Figure 6(A), the center frequency f c 6B shows the relationship between the true reflection frequency when the center frequency f is set to 20 kHz and the reflection frequency estimated by the method of the embodiment. c 6(C) shows the relationship between the true reflection frequency when the center frequency f is set to 30 kHz and the reflection frequency estimated by the method of the embodiment. c 6(D) shows the relationship between the true reflection frequency when the center frequency f is set to 40 kHz and the reflection frequency estimated by the method of the embodiment. c 10 shows the relationship between the true reflection frequency when the frequency is set to 50 kHz and the reflection frequency estimated by the method of the embodiment.

[0058] As shown in Figure 6(A) to Figure 6(D), the center frequency f c It can be seen that the higher the center frequency f of the filter 32 is, the more the reflection spectrum at a higher frequency can be detected. c It is desirable to set the frequency as low as possible within the required range, since the higher the frequency, the greater the scattering or attenuation.

[0059] Next, the dependency of the bandwidth characteristics of the filter 32 will be described. Fig. 7 is a diagram for explaining the dependency of the bandwidth characteristics of the filter 32 in the first embodiment. In Fig. 7(A) to Fig. 7(D), the horizontal axis represents the true reflection frequency, and the vertical axis represents the reflection frequency estimated by the method in the embodiment. Fig. 7(A) to Fig. 7(D) show the relationship between the true reflection frequency and the reflection frequency estimated by the method in the embodiment when the bandwidth BW of the filter 32 is increased in the order of Fig. 7(A) to Fig. 7(D).

[0060] FIG. 7A shows the relationship between the true reflection frequency when the bandwidth BW is 100 Hz and the reflection frequency estimated by the method of the embodiment. FIG. 7B shows the relationship between the true reflection frequency when the bandwidth BW is 1 kHz and the reflection frequency estimated by the method of the embodiment. FIG. 7C shows the relationship between the true reflection frequency when the bandwidth BW is 100 Hz and the reflection frequency estimated by the method of the embodiment. FIG. 7D shows the relationship between the true reflection frequency when the bandwidth BW is 20 kHz and the reflection frequency estimated by the method of the embodiment. In FIG. 7A to FIG. 7D, as an example, the center frequency f of the filter 32 is c is set to 40 kHz.

[0061] As shown in Figures 7A to 7D, when the bandwidth BW is narrowed (the bandwidth BW is made narrower), the detection range shifts to the lower frequency side, and when narrowed to about 100 Hz (for example, Figure 7A), detection becomes impossible. Therefore, it is desirable that the bandwidth BW of the filter 32 be 100 Hz or more.

[0062] Based on the results shown in FIGS. 6 and 7, the center frequency f c It can be seen that by switching between these frequencies, it is possible to accurately estimate the reflected frequency over a wide range. Here, a simulation was performed assuming various damage depths, and the results of damage depth estimation using this method are shown in FIG. 8. In FIG. 8, the center frequency of the filter 32 is set to 80 kHz when measuring shallower regions, with a depth of around 0.15 m as the boundary, and the center frequency is set to 40 kHz when measuring deeper regions. The horizontal axis in FIG. 8 represents the true damage depth assumed in the simulation, and the vertical axis represents the depth estimated using this method. FIG. 8 shows the results of a simulation performed using the center frequency f of the filter 32 in the first embodiment. c FIG. 10 is a diagram showing the detection results of the reflection frequency according to the

[0063] As shown in FIG. 8, the center frequency f c When the center frequency f of the filter 32 is 40 kHz (Low mode shown in FIG. 8), the low-frequency reflection frequency can be detected with high accuracy. c It can be seen that when the center frequency of the filter 32 is 80 kHz (High mode shown in Figure 8), high-frequency reflected frequencies can be detected with high accuracy. As such, the higher the center frequency of the filter 32, the better the detection performance in the high-reflection-frequency range, and the lower the center frequency, the better the detection performance in the deeper range. The estimated depth and true depth values ​​match well, demonstrating the validity of this method.

[0064] (Example of operation in the first embodiment) Fig. 9 is a flowchart showing the flow of damage detection processing performed by the damage detection device 25 in the first embodiment. The processing in Fig. 9 is executed when an impact is applied at a certain measurement point (for example, a position where damage exists) and an elastic wave is detected by the sensor 20. The processing in Fig. 9 will be described for the case where the detection unit 33 is composed of a processing unit 35 and a filter 36. Fig. 10 will also be referred to as appropriate in the description of Fig. 9. Fig. 10 is a diagram showing signal waveforms resulting from the damage detection processing performed by the damage detection device 25 in the first embodiment.

[0065] The waveform acquisition unit 31 acquires an electrical signal based on an elastic wave generated by an impact applied at a certain measurement point, from the output of the sensor 20. The waveform acquisition unit 31 acquires waveform data at the certain measurement point by amplifying the acquired electrical signal, filtering it, and performing analog-to-digital conversion (step S101). The waveform data acquired by this processing is shown in FIG. 10(A). The waveform acquisition unit 31 outputs the acquired waveform data to the filter 32.

[0066] The filter 32 performs a filtering process on the waveform data at a certain measurement point output from the waveform acquisition unit 31 (step S102). As a result, the waveform data is converted into a narrowband signal. The waveform data obtained by this process is shown in FIG. 10(B). The waveform data filtered by the filter 32 is input to the detection unit 33.

[0067] The processing unit 35 of the detection unit 33 performs squaring on the input waveform data (step S103). The waveform data obtained by this processing is shown in (C) of FIG. 10. Note that the processing unit 35 may perform absolute value processing instead of squaring. Thereafter, the processing unit 35 outputs the waveform data after squaring to the filter 36. The filter 36 performs filtering on the waveform data after squaring output from the processing unit 35 (step S104). For example, the filter 36 detects the envelope of the waveform data after squaring and extracts the AC component of the detected envelope. As a result, the AC component of the envelope in the waveform data after squaring is extracted. The waveform data obtained by this processing (e.g., information indicating the AC component of the envelope) is shown in (D) of FIG. 10. The waveform data filtered by the filter 36 is input to the output unit 34. The output unit 34 outputs transmission data including the input waveform data (e.g., information indicating the AC component of the envelope) to the spectrum calculation unit 40.

[0068] The spectrum calculation unit 40 calculates the frequency spectrum by performing a Fourier transform on the waveform data included in the transmission data output from the output unit 34 (step S105). As a result, the spectrum calculation unit 40 extracts a frequency spectrum such as that shown in (E) of FIG. 10 . The spectrum calculation unit 40 outputs information indicating the extracted frequency spectrum to the depth calculation unit 45. Here, the spectrum calculation unit 40 outputs information indicating a peak frequency as information indicating the frequency spectrum to the depth calculation unit 45. This peak frequency is calculated as the reflection frequency f r is.

[0069] The depth calculation unit 45 calculates the depth of the damage based on the information indicating the frequency spectrum output from the spectrum calculation unit 40 (step S106). Specifically, the depth calculation unit 45 calculates the depth of the damage based on the information indicating the frequency spectrum output from the spectrum calculation unit 40. p and the reflection frequency f r The depth of damage is calculated based on the above formula (2) using the depth T of the structure 50 having a thickness T. r If damage exists at the position, the thickness T calculated based on the above formula (2) is the damage depth Tr is equivalent to

[0070] The above-described method can calculate the depth of damage. To demonstrate the effectiveness of this method, Figure 11 shows the frequency spectra obtained on an actual structure using this method and the conventional impact-echo method. A 50 kHz resonant AE sensor was used in this method. Figure 11 (A) shows the frequency spectrum obtained using this method and the frequency spectrum obtained using the conventional impact-echo method. As shown in Figure 11, the two spectra are in good agreement, indicating that this method can obtain a reflection spectrum equivalent to that of the impact-echo method by using an AE sensor with a resonant frequency higher than the reflection frequency band. This method makes it possible to use the same sensor for both AE measurement and impact-echo measurement, thereby reducing the cost of sensor installation.

[0071] The damage detection system 100 configured as described above includes a detector 33 that detects an AC component of an envelope using one or more elastic waves generated by an impact on the structure 50, a spectrum calculator 40 that calculates a frequency spectrum based on the detected AC component of the envelope, and a depth calculator 45 that calculates the depth of damage present inside the structure 50 based on the frequency spectrum. This allows a reflection spectrum equivalent to that of the conventional impact-echo method to be obtained even when a sensor 20 having a resonant frequency higher than the reflection frequency band is used. Therefore, even when a sensor 20 having a resonant frequency higher than the reflection frequency band is used, the depth of damage present inside the structure 50 can be calculated using the conventional impact-echo method. In this way, other sensors can be used to estimate the damage depth, rather than dedicated sensors. This improves the flexibility of the sensor used to estimate the damage depth. Furthermore, since a dedicated sensor is not used, an inexpensive sensor can be used, thereby reducing sensor costs.

[0072] Furthermore, in the damage detection system 100, the center frequency of the filter 32 is determined by the thickness T of the structure 50 and the propagation velocity C of the elastic wave propagating inside the structure 50. p A frequency higher than the multiple reflection frequency calculated based on the above is set as the center frequency. The detection unit 33 detects the AC component of the envelope using one or more elastic waves filtered by the filter 32. As a result, even when a sensor sensitive to high frequencies such as an AE sensor is used, the reflection frequency can be calculated accurately by converting the signal into a narrowband signal using the filter 32. In this way, even when a sensor 20 having a resonant frequency higher than the reflection frequency band is used, a reflection spectrum equivalent to that of the conventional impact echo method can be obtained. Therefore, even when a sensor 20 having a resonant frequency higher than the reflection frequency band is used, the depth of damage present inside the structure 50 can be calculated using the conventional impact echo method. In this way, other sensors can be used instead of dedicated sensors to estimate the damage depth. This improves the flexibility of the sensor used to estimate the damage depth. Furthermore, since a dedicated sensor is not used, inexpensive sensors can be used, thereby reducing sensor costs.

[0073] Furthermore, in damage detection system 100, the frequency band of the frequency spectrum that can be detected varies depending on the center frequency of filter 32. Therefore, by switching the center frequency of filter 32 depending on the depth of damage to be detected, rather than using a fixed center frequency, the depth of damage can be calculated more accurately.

[0074] (Second embodiment) The first embodiment is effective when the location of damage inside a structure is known. However, even if damage has occurred inside a structure, the location of the damage inside the structure is often unknown. Therefore, in the second embodiment, a configuration will be described in which processing for identifying the damaged area is further performed.

[0075] Here, the process for identifying the damaged area inside the structure is, for example, measurement using the existing acoustic emission (AE) method. As explained in the first embodiment, even when a sensor having sensitivity to high frequencies such as an AE sensor is used, the depth of damage can be estimated using the impact echo method. The AE sensor is originally a sensor used for measurement using the AE method. Therefore, the same sensor can be used for both AE measurement and IE measurement (measurement using the impact echo method), which reduces the measurement work time and improves convenience.

[0076] In the second embodiment, first, planar measurement is performed using existing AE measurement. This identifies a damaged area within an inspection target area surrounded by multiple sensors. Then, in the identified damaged area, the depth of the damage is calculated using the method shown in the first embodiment. This makes it possible to perform both AE measurement and IE measurement by using one type of sensor, such as an AE sensor. Details are explained below.

[0077] 12 is a diagram showing the configuration of a damage detection system 100a according to the second embodiment. The damage detection system 100a is used to detect damage occurring inside a structure 50 and to evaluate the soundness of the structure 50. In the following description, evaluation means determining the degree of soundness of the structure 50, i.e., the state of deterioration of the structure 50, based on a certain criterion.

[0078] Damage that affects the assessment of the deterioration state of the structure 50 includes damage inside the structure that interferes with the propagation of elastic waves, such as cracks, cavities, and sedimentation. Here, cracks include vertical cracks, horizontal cracks, and diagonal cracks. Vertical cracks are cracks that occur in a direction perpendicular to the road surface. Horizontal cracks are cracks that occur horizontally to the road surface. Diagonal cracks are cracks that occur in a direction other than horizontal or vertical to the road surface. Sedimentation is deterioration in which concrete turns into sediment, mainly at the boundary between the asphalt and the concrete deck.

[0079] The damage detection system 100a includes an impact applying unit 10, a plurality of sensors 20-1 to 20-n, a signal processing unit 30a, and a structure evaluation device 60a. Each of the plurality of sensors 20-1 to 20-n and the signal processing unit 30a are connected to each other via wires so that they can communicate with each other. The signal processing unit 30a and the structure evaluation device 60a are connected to each other via wires or wirelessly so that they can communicate with each other.

[0080] The damage detection system 100a differs in configuration from the damage detection system 100 in that the spectrum calculation unit 40 and depth calculation unit 45 that were provided in the damage detection device 25 are provided in a structure evaluation device 60a, and in that a signal processing unit 30a is provided instead of the signal processing unit 30. The impact application unit 10 and sensor 20 are the same as those in the first embodiment. The following description will focus on the differences from the first embodiment.

[0081] The signal processing unit 30a performs the same processing as the signal processing unit 30 in the first embodiment. Furthermore, the signal processing unit 30a performs signal processing such as noise removal and extraction of elastic wave feature quantities on the input electrical signal. The signal processing unit 30a performs a first processing step to extract the AC component of the envelope shown in the first embodiment, and a second processing step to extract feature quantities to be used in AE measurement. The signal processing unit 30a operates by switching between the first processing step and the second processing step according to settings.

[0082] For example, when the signal processing unit 30a is set to perform the first processing, it generates transmission data including information obtained by performing the first processing (for example, information indicating the AC component of the envelope). The signal processing unit 30a outputs the generated transmission data to the structure evaluation device 60a. For example, when the signal processing unit 30a is set to perform the second processing, it generates transmission data including information obtained by performing the second processing (for example, information indicating the feature quantities of the elastic wave). The signal processing unit 30a outputs the generated transmission data to the structure evaluation device 60a.

[0083] The signal processing unit 30a is configured using a digital circuit. The digital circuit is realized, for example, by an FPGA or a microcomputer. The digital circuit may also be realized by a dedicated LSI. The signal processing unit 30a may 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 30a is configured using a digital circuit will be described.

[0084] The structure evaluation device 60a evaluates the deterioration state of the structure 50 based on the transmission data transmitted from the signal processing unit 30a. Furthermore, the structure evaluation device 60a calculates the depth of damage based on the transmission data transmitted from the signal processing unit 30a. The structure evaluation device 60a has, for example, a first mode for evaluating the deterioration state of the structure 50 and a second mode for calculating the depth of damage. In this way, the structure evaluation device 60a can perform both AE measurement and IE measurement. The structure evaluation device 60a is configured using an information processing device such as a personal computer.

[0085] 13 is a diagram showing an example of the configuration of a signal processing unit 30a in the second embodiment. The signal processing unit 30a includes a waveform acquisition unit 31, a filter 32, a detection unit 33, an output unit 34, a waveform shaping filter 301, a gate generation circuit 302, an arrival time determination unit 303, a feature extraction unit 304, a transmission data generation unit 305, and a memory 306. The signal processing unit 30a differs in configuration from the signal processing unit 30 in that it newly includes the waveform shaping filter 301, the gate generation circuit 302, the arrival time determination unit 303, the feature extraction unit 304, the transmission data generation unit 305, and the memory 306. The following description will focus on the differences from the signal processing unit 30.

[0086] The waveform acquisition unit 31 has the same configuration as the configuration shown in the first embodiment. When the waveform acquisition unit 31 is set to execute the first processing, it outputs waveform data, which is a digital signal, to the filter 32, and when the waveform acquisition unit 31 is set to execute the second processing, it outputs waveform data, which is a digital signal, to the waveform shaping filter 301.

[0087] The waveform shaping filter 301 removes noise components outside a predetermined band from the waveform data, which is a digital signal output from the waveform acquisition unit 31. The waveform shaping filter 301 is, for example, a digital band-pass filter (BPF). The waveform shaping filter 301 outputs the digital signal after the noise components have been removed (hereinafter referred to as the "noise-removed signal") to the gate generation circuit 302 and the feature extraction unit 304.

[0088] The gate generation circuit 302 receives the noise removal signal output from the waveform shaping filter 301. The gate generation circuit 302 generates a gate signal based on the received noise removal signal. The gate signal indicates whether the waveform of the noise removal signal is sustained.

[0089] The gate generation circuit 302 is realized by, for example, an envelope detector and a comparator. The envelope detector detects the envelope of the noise-removed signal. The envelope is extracted, for example, by squaring the noise-removed signal and performing a predetermined process (e.g., processing using a low-pass filter or a Hilbert transform) on the squared output value. The comparator determines whether the envelope of the noise-removed signal is equal to or greater than a predetermined threshold.

[0090] When the envelope of the noise-removed signal is equal to or greater than a predetermined threshold, the gate generation circuit 302 outputs a first gate signal indicating that the waveform of the noise-removed signal is sustained to the arrival time determination unit 303 and the feature extraction unit 304. On the other hand, when the envelope of the noise-removed signal is less than the predetermined threshold, the gate generation circuit 302 outputs a second gate signal indicating that the waveform of the noise-removed signal is not sustained to the arrival time determination unit 303 and the feature extraction unit 304. Note that while the gate generation circuit 302 is configured to determine whether the waveform of the noise-removed signal is sustained based on the envelope, 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 referred to as a measurement threshold.

[0091] The arrival time determination unit 303 receives as input a clock output from a clock source such as a crystal oscillator (not shown) and a gate signal output from the gate generation circuit 302. The arrival time determination unit 303 determines the elastic wave arrival time using the clock input while the first gate signal is being input. The arrival time determination unit 303 outputs the determined elastic wave arrival time as time information to the transmission data generation unit 305. The arrival time determination unit 303 does not perform any processing while the second gate signal is being input. The arrival time determination unit 303 generates cumulative time information since power-on based on the signal from the clock source. Specifically, the arrival time determination unit 303 may be a counter that counts clock edges, and the value of the counter's register may be used as the time information. The counter's register is determined to have a predetermined bit length.

[0092] The feature extraction unit 304 receives the noise-removed signal output from the waveform shaping filter 301 and the gate signal output from the gate generation circuit 302 as input. The feature extraction unit 304 extracts a feature of the noise-removed signal using the noise-removed signal input while the first gate signal is being input. The feature extraction unit 304 does not perform processing while the second gate signal is being input. The feature is information indicating the feature of the noise-removed signal. In other words, the feature of the noise-removed signal is a feature of the elastic wave detected by the sensor 20.

[0093] The feature quantity may be, for example, the amplitude [mV] of the waveform, the rise time [usec] of the waveform, the duration [usec] of the gate signal, the number of zero cross counts [times], the energy [arb.] of the waveform, the frequency [Hz], and the root mean square (RMS) value. The feature quantity extraction unit 304 outputs parameters related to the extracted feature quantity to the transmission data generation unit 305. When outputting the parameters related to the feature quantity, the feature quantity extraction unit 304 associates a sensor ID with the parameters related to the feature quantity. The sensor ID represents identification information for identifying the sensor 20 installed in the area (hereinafter referred to as the "evaluation area") to be evaluated for the soundness of the structure 50.

[0094] The waveform amplitude is, for example, the maximum amplitude value of the noise reduction signal. The waveform rise time is, for example, the time T1 from when the gate signal starts rising until the noise reduction signal reaches its maximum value. The gate signal duration is, for example, the time from when the gate signal starts rising until the amplitude becomes smaller than a preset value. The zero cross count is, for example, the number of times the noise reduction signal crosses a reference line that passes through a zero value.

[0095] The waveform energy is, for example, the value obtained by integrating the squared amplitude of the noise-removed signal at each time point over time. Note that the definition of energy is not limited to the above example, and may be approximated using, for example, the envelope of the waveform. The frequency is the frequency of the noise-removed signal. The RMS value is, for example, the value obtained by squaring the amplitude of the noise-removed signal at each time point and taking the square root.

[0096] The transmission data generation unit 305 receives the sensor ID, time information, and parameters related to the feature amount as input, and generates transmission data including the input sensor ID, time information, and parameters related to the feature amount.

[0097] The memory 306 stores one or more pieces of transmission data generated by the transmission data generating unit 305. The memory 306 is, for example, a dual-port RAM (Random Access Memory).

[0098] The output unit 34 generates transmission data including information indicating the AC component of the envelope extracted by the detection unit 33. The output unit 34 transmits the generated transmission data to the structure evaluation device 60a via a wired or wireless connection. Furthermore, the output unit 34 sequentially outputs one or more pieces of transmission data stored in the memory 306 to the structure evaluation device 60a. For example, when the signal processing unit 30a and the structure evaluation device 60a are connected via a wired connection, the output unit 34 outputs the transmission data including information indicating the AC component of the envelope or one or more pieces of transmission data stored in the memory 306 to the structure evaluation device 60a via a wired cable. When the signal processing unit 30a and the structure evaluation device 60a are connected wirelessly, the output unit 34 wirelessly outputs the transmission data including information indicating the AC component of the envelope or one or more pieces of transmission data stored in the memory 306 to the structure evaluation device 60a.

[0099] Continuing the explanation, returning to Fig. 12, the structure evaluation device 60a includes a communication unit 61, a control unit 62, a storage unit 63, and a display unit 64.

[0100] The communication unit 61 receives one or more pieces of transmission data transmitted from the signal processing unit 30a.

[0101] The control unit 62 controls the entire structure evaluation device 60a. The control unit 62 is configured using a processor such as a CPU (Central Processing Unit) and a memory. The control unit 62 executes a program to function as the spectrum calculation unit 40, the depth calculation unit 45, the acquisition unit 621, the event extraction unit 622, the position determination unit 623, the distribution generation unit 624, and the evaluation unit 625.

[0102] Some or all of the functional units of the spectrum calculation unit 40, depth calculation unit 45, acquisition unit 621, event extraction unit 622, position determination unit 623, distribution generation unit 624, and evaluation unit 625 may be realized by hardware such as an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), or an FPGA, or by a combination of software and hardware. The program may be recorded on a computer-readable recording medium. Examples of computer-readable recording media include portable media such as flexible disks, magneto-optical disks, read-only memories (ROMs), and CD-ROMs, and non-transitory storage media such as hard disks built into computer systems. The program may be transmitted via a telecommunications line.

[0103] Some of the functions of the spectrum calculation unit 40, the depth calculation unit 45, the acquisition unit 621, the event extraction unit 622, the position determination unit 623, the distribution generation unit 624, and the evaluation unit 625 do not need to be pre-installed in the structure evaluation device 60a, and may be realized by installing additional application programs in the structure evaluation device 60a.

[0104] The acquisition unit 621 acquires various types of information. For example, the acquisition unit 621 acquires one or more pieces of transmission data received by the communication unit 61. The acquisition unit 621 stores the acquired one or more pieces of transmission data in the storage unit 63. For example, the acquisition unit 621 acquires mode information that specifies the operation mode of the structure evaluation device 60a. The structure evaluation device 60a operates in either the first mode or the second mode based on the mode information acquired by the acquisition unit 621.

[0105] The spectrum calculation unit 40 and the depth calculation unit 45 are the same as those in the first embodiment. Note that the spectrum calculation unit 40 and the depth calculation unit 45 function when the structure evaluation device 60a operates in the second mode.

[0106] The event extraction unit 622, the position determination unit 623, the distribution generation unit 624, and the evaluation unit 625 function when the structure evaluation device 60a operates in the first mode.

[0107] The event extraction unit 622 extracts transmission data for one event from multiple pieces of transmission data stored in the memory unit 63. An event refers to an elastic wave generating event that occurs in the structure 50. In this embodiment, an elastic wave generating event is, for example, the application of an impact by the impact application unit 10. When one event occurs, multiple sensors 20 detect elastic waves at approximately the same time. In other words, the memory unit 63 stores transmission data related to elastic waves detected at approximately the same time. Therefore, the event extraction unit 622 sets a predetermined time window and extracts all transmission data whose arrival time falls within the range of the time window as transmission data for one event. The event extraction unit 622 outputs the extracted transmission data for one event to the position determination unit 623.

[0108] The time window range Tw may be determined using the elastic wave propagation velocity v in the target structure 50 and the maximum sensor spacing dmax so as to be in the range of Tw≧dmax / v. In order to avoid erroneous detection, it is desirable to set Tw to as small a value as possible, so that Tw can essentially be set to dmax / v. The elastic wave propagation velocity v may be determined in advance.

[0109] The position locating unit 623 locates the position of the elastic wave source based on the sensor position information and the sensor ID and time information included in each of the plurality of transmission data extracted by the event extracting unit 622.

[0110] The sensor position information includes information about the installation position of the sensor 20 associated with the sensor ID. The sensor position information includes information about the installation position of the sensor 20, such as latitude and longitude, or horizontal and vertical distances from a reference position of the structure 50. The positioning unit 623 holds the sensor position information in advance. The sensor position information may be stored in the positioning unit 623 at any timing before the positioning unit 623 locates the position of the elastic wave source.

[0111] The sensor position information may be stored in the storage unit 63. In this case, the position locating unit 623 acquires the sensor position information from the storage unit 63 at the timing of performing position locating. A Kalman filter, a least squares method, or the like may be used to locate the position of the elastic wave source. The position locating unit 623 outputs the position information of the elastic wave source obtained during the evaluation period to the distribution generating unit 624.

[0112] The distribution generation unit 624 receives as input the position information of the multiple elastic wave sources output from the position determination unit 623. The distribution generation unit 624 generates an elastic wave source distribution using the input position information of the multiple elastic wave sources. The elastic wave source distribution represents a distribution indicating the positions of the elastic wave sources. More specifically, the elastic wave source distribution is a distribution in which points indicating the positions of the elastic wave sources are displayed on virtual data representing the structure 50 to be evaluated, with the horizontal axis representing the distance in the traffic direction and the vertical axis representing the distance in the width direction.

[0113] The distribution generation unit 624 generates an elastic wave source density distribution using the elastic wave source distribution. The elastic wave source density distribution represents a distribution in which density values ​​calculated according to the number of elastic wave sources included in each predetermined region in the elastic wave source distribution are indicated. Specifically, the distribution generation unit 624 first divides the elastic wave source distribution into a plurality of regions by dividing the elastic wave source distribution into predetermined sections. Next, the distribution generation unit 624 calculates the density for each divided region generated by the division. For example, the distribution generation unit 624 calculates the density for each divided region by dividing the number of elastic wave sources located in the divided region by the area of ​​the divided region. Then, the distribution generation unit 624 generates the elastic wave source density distribution by assigning the calculated density value for each divided region to each divided region. In this way, the distribution generation unit 624 generates the elastic wave source density distribution by calculating the density for the region to be evaluated.

[0114] The evaluation unit 625 evaluates the deterioration state of the structure 50 using the elastic wave source density distribution generated by the distribution generation unit 624. For example, the evaluation unit 625 evaluates a region in the elastic wave source density distribution where the density of elastic wave sources is equal to or greater than a threshold as a healthy region, and evaluates a region where the density of elastic wave sources is less than the threshold as a damaged region. A healthy region refers to a region where no damage has occurred inside the structure 50, or where even if damage has occurred, the damage is relatively small.

[0115] The storage unit 63 stores one or more pieces of transmission data acquired by the acquisition unit 621. The storage unit 63 is configured using a storage device such as a magnetic hard disk drive or a semiconductor storage device. The storage unit 63 may also store an evaluation result obtained by the evaluation unit 625.

[0116] The display unit 64 displays the evaluation results under the control of the evaluation unit 625. For example, the display unit 64 may display, as the evaluation result, whether or not deterioration has occurred inside the structure 50, or may display an area where deterioration has occurred on the elastic wave propagation velocity distribution. The display unit 64 is an image display device such as a liquid crystal display or an organic EL (Electro Luminescence) display. The display unit 64 may be an interface for connecting the image display device to the structure evaluation device 60a. In this case, the display unit 64 generates a video signal for displaying the evaluation results and outputs the video signal to the image display device connected to the display unit 64.

[0117] (Example of operation in the second embodiment) Next, an example of the operation of the damage detection system 100a in the second embodiment will be described. In the damage detection system 100a, AE measurement is first performed. Therefore, the signal processing unit 30a is set to perform the second processing, and the structure evaluation device 60a is set to operate in the first mode. The signal processing unit 30a inputs the digital signal output from the analog-to-digital converter. The arrival time determination unit 303 of the signal processing unit 30a determines the arrival time of each elastic wave. Specifically, the arrival time determination unit 303 determines the elastic wave arrival time using the clock input while the first gate signal is input. 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 input digital signals.

[0118] The feature extraction unit 304 of the signal processing unit 30a extracts features of the denoising signal, which is a digital signal input while the first gate signal is being input. The feature extraction unit 304 outputs parameters related to the extracted features to the transmission data generation unit 305. The transmission data generation unit 305 generates transmission data including a sensor ID, time information, and the parameters related to the features. The transmission data generation unit 305 stores the generated transmission data in the memory 306. The output unit 34 sequentially outputs the transmission data stored in the memory 306 to the structure evaluation device 60a.

[0119] The communication unit 61 of the structure evaluation device 60a receives the transmission data output from the signal processing unit 30a. The acquisition unit 621 acquires the transmission data received by the communication unit 61. The acquisition unit 621 records the acquired transmission data in the storage unit 63. The acquisition unit 621 records all of the transmission data received during the evaluation period in the storage unit 63.

[0120] After the evaluation period has elapsed, or in response to an external instruction, the event extraction unit 622 extracts transmission data for one event from the transmission data for the evaluation period stored in the storage unit 63. The event extraction unit 622 outputs the extracted transmission data for one event to the position determination unit 623. The event extraction unit 622 performs extraction processing of transmission data for one event and output processing of the extracted transmission data for one event in chronological order.

[0121] The positioning unit 623 locates the position of the elastic wave source based on the sensor ID and time information included in the transmission data output from the event extraction unit 622 and pre-stored sensor position information. Specifically, the positioning unit 623 first calculates the difference in arrival time of the elastic wave at each of the multiple sensors 20. Next, the positioning unit 623 locates the position of the elastic wave source using the sensor position information and information on the difference in arrival time.

[0122] The position locating unit 623 locates the position of the elastic wave source every time transmission data of one event is output from the event extracting unit 622 during the evaluation period. In this way, the position locating unit 623 locates the positions of multiple elastic wave sources that occurred during the evaluation period. The position locating unit 623 outputs position information of the multiple elastic wave sources to the distribution generating unit 624.

[0123] The distribution generation unit 624 generates an elastic wave source distribution using the position information of the multiple elastic wave sources output from the position determination unit 623. Specifically, the distribution generation unit 624 generates the elastic wave source distribution by plotting the positions of the elastic wave sources indicated by the obtained position information of the multiple elastic wave sources on virtual data. The distribution generation unit 624 generates an elastic wave source density distribution using the generated elastic wave source distribution. The distribution generation unit 624 outputs the generated elastic wave source density distribution to the evaluation unit 625.

[0124] The evaluation unit 625 evaluates the deterioration state of the structure 50 using the elastic wave source density distribution output from the distribution generation unit 624. The evaluation unit 625 outputs the evaluation result to the display unit 64. The display unit 64 displays the evaluation result output from the evaluation unit 625. By looking at the evaluation result displayed on the display unit 64, the operator of the damage detection system 100a can understand which area of ​​the evaluation target area has deteriorated. Therefore, the operator calculates the depth of damage in the area where deterioration has occurred using the method described in the first embodiment.

[0125] In this case, the damage detection system 100a next performs IE measurement. Therefore, the signal processing unit 30a is set to perform the first processing, and the structure evaluation device 60a is set to operate in the second mode. The basic operation is the same as the operation shown in the first embodiment. Therefore, differences will be explained here. After the processing of step S104, the output unit 34 transmits transmission data including the input waveform data (e.g., information indicating the AC component of the envelope) to the structure evaluation device 60a via wired or wireless communication.

[0126] The communication unit 61 of the structure evaluation device 60a receives the transmission data output from the signal processing unit 30a. The acquisition unit 621 outputs the transmission data received by the communication unit 61 to the spectrum calculation unit 40. The spectrum calculation unit 40 calculates a frequency spectrum by performing a Fourier transform on the waveform data included in the transmission data output from the acquisition unit 621. The spectrum calculation unit 40 outputs information indicating the extracted frequency spectrum to the depth calculation unit 45. The depth calculation unit 45 calculates the depth of damage based on the information indicating the frequency spectrum output from the spectrum calculation unit 40.

[0127] According to the damage detection system 100a configured as above, it is possible to obtain the same effects as those of the first embodiment.

[0128] Furthermore, the damage detection system 100a can perform both IE measurement and AE measurement based on elastic waves detected by the same sensor 20. This eliminates the need to use a dedicated sensor for IE measurement, and the number of sensors used for measurement can be reduced. This makes it possible to reduce sensor costs. Furthermore, the damage detection system 100a can perform both IE measurement and AE measurement, thereby improving convenience.

[0129] (Modification 1 of the second embodiment) Some or all of the functional units included in the structure evaluation device 60a may be included in another device. For example, the display unit 64 included in the structure evaluation device 60a may be included in the other device. When configured in this manner, the structure evaluation device 60a transmits the evaluation results to the other device that includes the display unit 64. The other device that includes the display unit 64 displays the received evaluation results.

[0130] (Modification 2 of the second embodiment) In the above-described configuration, the structure evaluation device 60a performs both AE measurement and IE measurement. However, the structure evaluation device 60a may be configured to perform only AE measurement, with another device performing IE measurement. In this configuration, the structure evaluation device 60a does not need to include the spectrum calculation unit 40 and the depth calculation unit 45, and may not need to include the second mode for performing IE measurement. The other device may be, for example, the damage detection device 25 as in the first embodiment, or may be an information processing device different from the damage detection device 25. When the spectrum calculation unit 40 and the depth calculation unit 45 are included in the damage detection device 25, the signal processing unit 30a is configured to transmit transmission data to the spectrum calculation unit 40 during the first processing and to transmit transmission data to the structure evaluation device 60a during the second processing.

[0131] (Modification 3 of the second embodiment) In the above-described configuration, the structure evaluation device 60a is configured to evaluate the deterioration state of the structure. However, an operator can also identify areas where deterioration has occurred by viewing the elastic wave source density distribution. Therefore, the structure evaluation device 60a may display the elastic wave source density distribution on the display unit 64 without evaluating the deterioration state of the structure 50 based on the elastic wave source density distribution. In such a configuration, the structure evaluation device 60a does not need to include the evaluation unit 625. An operator may identify areas where deterioration has occurred by referring to the elastic wave source density distribution displayed on the display unit 64 of the structure evaluation device 60a, and may operate the structure evaluation device 60a to calculate the depth of damage in the areas where deterioration has occurred, as shown in the first embodiment.

[0132] (Modification 4 of the second embodiment) In the above-described configuration, the structure evaluation device 60a evaluates the deterioration state of the structure based on the elastic wave source density distribution. In this method, it is sufficient to identify the area where deterioration has occurred, so the method by which the structure evaluation device 60a evaluates the deterioration state of the structure is not limited to the above-described method. For example, an existing method based on the propagation velocity of elastic waves may be used, or a method described in Reference 1 below that evaluates the deterioration state of the structure 50 by combining the elastic wave propagation velocity distribution and the elastic wave source density distribution may be used, or other methods may be used. (Reference 1: International Publication No. 2017 / 199542)

[0133] The method described in Reference 1 provides at least four levels of evaluation results. Therefore, the operator can determine the area for which the damage depth is calculated based on the four levels of evaluation results obtained.

[0134] (Modification 5 of the second embodiment) The signal processing unit 30a may be integrated with the structure evaluation device 60a, that is, the structure evaluation device 60a may be configured to have all the functions performed by the signal processing unit 30a.

[0135] (Modification 1 common to the first and second embodiments) In each of the above embodiments, a configuration has been shown in which multiple sensors 20-1 to 20-n are connected to one signal processing unit 30. The damage detection system 100, 100a may include multiple signal processing units 30, 30a, and each sensor 20 may be connected to a different signal processing unit 30, 30a. In this case, the multiple signal processing units 30, 30a perform processing based on the elastic waves detected by the sensor 20 to which they are connected.

[0136] According to at least one of the embodiments described above, by having a detection unit 33 that detects the AC component of the envelope using one or more elastic waves generated by an impact on the structure 50, a spectrum calculation unit 40 that calculates a frequency spectrum based on the detected AC component of the envelope, and a depth calculation unit 45 that calculates the depth of damage present inside the structure 50 based on the frequency spectrum, it is possible to improve the degree of freedom of the sensor used to estimate the depth of the damage and reduce the sensor cost.

[0137] Some of the processing performed by the signal processing unit 30 in the above-described embodiment may be implemented by a computer. In this case, a program for implementing this function may be recorded on a computer-readable recording medium, and the program may be loaded into a computer system and executed. Note that the term "computer system" herein includes hardware such as an OS and peripheral devices. Furthermore, the term "computer-readable recording medium" refers to portable media such as flexible disks, optical magnetic disks, ROMs, and CD-ROMs, as well as storage devices such as hard disks built into a computer system. Furthermore, the term "computer-readable recording medium" may also include devices that dynamically store programs for a short period of time, such as communication lines used when transmitting programs via networks such as the Internet or telephone lines, or devices that store programs for a fixed period of time, such as volatile memory within a computer system serving as a server or client. The program may be designed to implement some of the above-described functions, or may be capable of implementing the above-described functions in combination with a program already stored in the computer system, or may be implemented using a programmable logic device such as an FPGA.

[0138] Although several embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, as well as within the scope of the invention described in the claims and their equivalents. [Explanation of symbols]

[0139] 10...impact application unit, 20, 20-1 to 20n...sensor, 30, 30a...signal processing unit, 31...waveform acquisition unit, 32...filter, 33...detection unit, 34...output unit, 35...processing unit, 36...filter, 37...conversion unit, 38...high-pass filter, 40...spectrum calculation unit, 45...depth calculation unit, 60a...structure evaluation device, 61...communication unit, 62...control unit, 63...storage unit, 64...display unit, 100, 100a...damage detection system, 621...acquisition unit, 622...event extraction unit, 623...position location unit, 624...distribution generation unit, 625...evaluation unit

Claims

1. a detection unit that detects an AC component of an envelope using one or more elastic waves generated by an impact on a structure; a spectrum calculation unit that calculates a frequency spectrum based on the detected AC component of the envelope; a depth calculation unit that calculates the depth of damage present inside the structure based on the frequency spectrum; A damage detection device comprising:

2. a first band-pass filter that has a center frequency set to a frequency higher than a multiple reflection frequency calculated based on a thickness of the structure and a propagation velocity of the elastic wave propagating inside the structure, and that performs filtering on the one or more elastic waves; the detection unit detects an AC component of an envelope using the one or more elastic waves that have been filtered by the first band-pass filter. The damage detection device according to claim 1 .

3. The detection unit a processing unit that performs processing to take the absolute value or square of the one or more elastic waves; a second band-pass filter that detects an envelope using the one or more elastic waves processed by the processing unit and detects an AC component of the detected envelope; The damage detection device according to claim 1 or 2, comprising:

4. The detection unit a transformer that performs a Hilbert transform on the one or more elastic waves; a high-pass filter for removing a DC component of the envelope obtained by the Hilbert transform; The damage detection device according to claim 1 or 2, comprising:

5. The first bandpass filter comprises: The center frequency is switched depending on the depth of the damage calculated by the depth calculation unit. The damage detection device according to claim 2 .

6. The one or more elastic waves are signals detected by a resonance type AE sensor. The damage detection device according to claim 1 or 2.

7. The resonance type AE sensor is a sensor having a resonance frequency of 10 kHz to 100 kHz. The damage detection device according to claim 6.

8. The bandwidth of the first bandpass filter is 100 Hz or more. The damage detection device according to claim 2 .

9. an impact applying unit that applies an impact to the structure; one or more sensors that detect one or more elastic waves generated by the impact applied by the impact application unit; a detection unit that detects an AC component of an envelope using one or more elastic waves generated by an impact on a damaged area inside the structure, the impact being estimated based on the one or more elastic waves detected by the one or more sensors; a spectrum calculation unit that calculates a frequency spectrum based on the detected AC component of the envelope; a depth calculation unit that calculates the depth of damage present inside the structure based on the frequency spectrum; A damage detection system comprising:

10. detecting an AC component of the envelope using one or more elastic waves generated by an impact on the structure; calculating a frequency spectrum based on the detected AC component of the envelope; Calculating the depth of damage present inside the structure based on the frequency spectrum. Damage detection methods.

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