Acoustic diagnostic device, acoustic diagnostic method, and acoustic diagnostic program

Abstract

To provide an acoustic diagnosis device, an acoustic diagnosis method, and an acoustic diagnosis program for acoustically exciting a structure to diagnose the structure in a non-contact manner.SOLUTION: An acoustic diagnosis device has an acoustic excitation unit, an acoustic excitation signal generation unit, a sound receiving unit, an impulse response calculation unit, a structure state analysis unit, and a structure state diagnosis unit. The acoustic excitation unit acoustically excites an object to be diagnosed. The acoustic excitation signal generation unit generates acoustic excitation signals and continuously inputs the signals to the acoustic excitation unit. The sound receiving unit receives evaluation target sounds including sound waves reflected from the object to be diagnosed and vibration radiation sounds from the object to be diagnosed, and outputs sound receiving signals. The impulse response calculation unit calculates impulse responses based on the sound receiving signals. The structure state analysis unit calculates acoustic characteristics by using the impulse responses, captures a change in the sound receiving signals, and analyzes the state of the object to be diagnosed. The structure state diagnosis unit diagnoses the state of the object to be diagnosed based on a result of the analysis conducted by the structure state analysis unit.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] An embodiment of the present invention relates to an acoustic diagnosis apparatus, an acoustic diagnosis method, and an acoustic diagnosis program. [Background technology]

[0002] In buildings and infrastructure structures, deterioration over time can occur in the form of changes in rigidity due to changes in welding or joining conditions of the structure, changes in structural damping characteristics due to peeling of internal coatings such as vibration-damping materials, and changes in strength due to rust, cracks, cavities, etc. in the internal structure. Conventionally, deterioration evaluations have been performed by periodic hammering, etc. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2015-219138 A [Patent Document 2] Patent No. 6457456 [Patent Document 3] Patent Publication No. 2021-124439 [Patent Document 4] Japanese Patent Application Publication No. 05-118965 Summary of the Invention [Problem to be solved by the invention]

[0004] An object of the present invention is to provide an acoustic diagnostic apparatus, an acoustic diagnostic method, and an acoustic diagnostic program for acoustically exciting a diagnosis target such as a structure and diagnosing the same in a non-contact manner. [Means for solving the problem]

[0005] The acoustic diagnostic device of the embodiment includes an acoustic excitation unit, an acoustic excitation signal generation unit, a sound receiving unit, an impulse response calculation unit, a structural condition analysis unit, and a structural condition diagnosis unit. The acoustic excitation unit acoustically excites the diagnosis object. The acoustic excitation signal generation unit generates an acoustic excitation signal and continuously inputs the acoustic excitation signal to the acoustic excitation unit. The sound receiving unit receives an evaluation target sound including a sound wave reflected from the diagnosis object and a vibration radiation sound from the diagnosis object, and outputs a received sound signal. The impulse response calculation unit calculates an impulse response based on the received sound signal. The structural condition analysis unit calculates acoustic characteristics using the impulse response, and captures changes in the received sound signal to analyze the state of the diagnosis object. The structural condition diagnosis unit diagnoses the state of the diagnosis object based on the analysis result of the structural condition analysis unit. The acoustic excitation signal generator continuously inputs the Logss signal, which can separate nonlinear characteristics, to the acoustic excitation unit. In the first step, the structural state analyzer extracts the waveforms of the linear characteristic section and each distortion characteristic section from the impulse response calculated by the impulse response calculation unit, and in the second step, performs single microphone frequency characteristic evaluation 1, single microphone frequency characteristic evaluation 2, two microphone intensity evaluation 1, and two microphone intensity evaluation 2.

[0006] An acoustic diagnosis method according to an embodiment includes continuously inputting an acoustic vibration signal to an acoustic excitation unit to acoustically vibrate an object to be diagnosed, calculating an impulse response based on a received signal output by a sound receiving unit that receives an evaluation target sound including sound waves reflected from the object to be diagnosed and vibration radiation sound from the object to be diagnosed, calculating acoustic characteristics using the impulse response, capturing changes in the received signal to analyze the condition of the object to be diagnosed, and diagnosing the condition of the object to be diagnosed based on the analysis results. To acoustically excite the object to be diagnosed, a Logss signal capable of separating nonlinear characteristics is continuously input to the acoustic excitation unit. To analyze the state of the object to be diagnosed, in the first step, the linear characteristic section and each distortion characteristic section are extracted from the impulse response, and in the second step, single microphone frequency characteristic evaluation 1, single microphone frequency characteristic evaluation 2, two microphone intensity evaluation 1, and two microphone intensity evaluation 2 are performed.

[0007] The acoustic diagnosis program of the embodiment causes a computer having a processor and a storage device to execute the functions of the acoustic excitation signal generating unit, the impulse response calculating unit, the structural condition analyzing unit, and the structural condition diagnosing unit of the acoustic diagnosis apparatus. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a block diagram of an acoustic diagnostic apparatus according to an embodiment. [Diagram 2] FIG. 2 is a diagram illustrating hardware of the diagnostic processing unit in FIG. [Diagram 3] FIG. 3 is a diagram showing four exemplary configurations of the acoustic excitation unit. [Figure 4]FIG. 4 is a schematic diagram showing five example single-microphone configurations applied to each of the microphones of the sound receiving section. [Diagram 5] FIG. 5 is a diagram showing two exemplary configurations of the first and second microphones. [Figure 6] FIG. 6 is a diagram showing two exemplary configurations of the sound receiving section. [Figure 7] FIG. 7 is a flowchart showing the procedure of the diagnostic process executed by the diagnostic processing unit. [Figure 8] FIG. 8 is a flowchart showing the processing procedure of single-microphone frequency characteristic evaluation 1. [Figure 9] FIG. 9 is a flowchart showing the processing procedure of single-microphone frequency characteristic evaluation 2. [Figure 10] FIG. 10 is a flowchart showing the processing procedure for the two-microphone intensity evaluation 1. [Figure 11] FIG. 11 is a flowchart showing the processing procedure for the two-microphone intensity evaluation 2. [Figure 12] FIG. 12 is a flowchart showing the procedure of the auxiliary structural condition analysis. [Figure 13] FIG. 13 is a diagram showing a Logss signal based on the equation (3) in which a predetermined value is set. [Figure 14] FIG. 14 is a diagram showing a Logss signal obtained by shifting the signal in FIG. 13 by a predetermined amount. [Figure 15] FIG. 15 is a spectrogram of the Logss signal after the shift shown in FIG. [Figure 16] FIG. 16 is a diagram showing the relationship between time and frequency in the spectrogram of the Logss signal expressed by equations (6) to (8). [Figure 17] FIG. 17 shows a spectrogram when harmonic distortion occurs in the Logss signal that results in the spectrogram shown in FIG. [Figure 18] FIG. 18 shows an impulse response obtained by converting the response curve of the Logss signal, which is the spectrogram shown in FIG. 17, using the inverse characteristic of the Logss signal. [Figure 19]FIG. 19 is a diagram showing the results of calculating the occurrence times of the distortion characteristics shown in FIG. 18 based on equation (9). [Figure 20] FIG. 20 is a diagram showing the results of calculation of the occurrence times in the impulse response of the distortion characteristics shown in FIG. 18 based on equation (7). [Figure 21] FIG. 21 is a diagram illustrating an example of an impulse response. [Figure 22] FIG. 22 is an enlarged view of the region RB corresponding to the nonlinear characteristics of the impulse response. [Diagram 23] FIG. 23 is a graph showing an example of active intensity measurement. [Figure 24] FIG. 24 is a graph showing an example of reactive intensity measurement. [Diagram 25] FIG. 25 is a schematic diagram of a diagnostic object and one microphone in a basal state. [Figure 26] FIG. 26 is a diagram showing a schematic diagram of a state in which the sound absorption characteristics of the diagnosis object are deteriorated as compared with the reference state of FIG. [Figure 27] FIG. 27 is a diagram showing an example of an increase in the micro-vibration of the diagnosis object compared to the reference state of FIG. [Figure 28] FIG. 28 is a schematic diagram of a diagnostic object and two microphones in a basal state. [Figure 29] FIG. 29 is a diagram showing an example of an increase in the sound absorption characteristics of the diagnosis object compared to the reference state of FIG. [Diagram 30] FIG. 30 is a diagram showing a schematic diagram of a state in which the micro-vibrations of the diagnosis object are reduced as compared with the reference state of FIG. [Diagram 31] FIG. 31 is a diagram showing a schematic diagram of the movement of the speaker center and the contour line display of the measurement results. [Diagram 32] FIG. 32 is a graph showing baseline and measurement analysis data of the ratio of active intensity. [Diagram 33] FIG. 33 is a diagram showing an example of an increase in micro-vibrations of the diagnosis target 90 after the vibration-damping material is peeled off, compared to before the vibration-damping material is peeled off. [Diagram 34] FIG. 34 is a diagram showing a schematic diagram of a state in which the sound absorbing characteristics of the diagnosis object 90 are deteriorated after the vibration-damping material is peeled off, compared with before the vibration-damping material is peeled off. [Diagram 35] FIG. 35 is a diagram showing the relative positions of a speaker, a microphone, and an object to be diagnosed in an embodiment of diagnosis of separation of a damping material. [Diagram 36] FIG. 36 is a diagram showing a vibration-damping material attached to the bottom plate of a steel can. [Figure 37] FIG. 37 is a graph showing the results of LDV measurement in the wavelength band of 200 to 900 Hz. [Figure 38] FIG. 38 is a graph showing the difference in the results of LDV measurement in the frequency band of 200 to 900 Hz. [Figure 39] FIG. 39 is a graph showing the results of LDV measurement in the frequency band of 1500 to 4000 Hz. [Diagram 40] FIG. 40 is a graph showing the difference in the results of LDV measurement in the frequency band of 1500 to 4000 Hz. [Diagram 41] FIG. 41 is a graph showing the evaluation results of the differential transfer characteristic in the single-microphone frequency characteristic evaluation 1 for the linear characteristic below 1 KHz. [Diagram 42] FIG. 42 is a graph showing the evaluation results of the response differential transfer characteristic in the single-microphone frequency characteristic evaluation 2 for the linear characteristic below 1 KHz. [Diagram 43] FIG. 43 is a graph showing the evaluation results of active intensity by two-microphone intensity evaluation 1 in the wavelength band of 320 to 500 Hz, for linear characteristics below 1 KHz. [Diagram 44] FIG. 44 is a graph showing the evaluation results of active intensity by two-microphone intensity evaluation 1 in the wavelength band of 600 to 750 Hz, for linear characteristics below 1 KHz. [Diagram 45] FIG. 45 is a graph showing the evaluation results of the difference in active intensity in the two-microphone intensity evaluation 1 for linear characteristics below 1 KHz. [Diagram 46]FIG. 46 is a graph showing the evaluation results of the ratio of active intensity in the two-microphone intensity evaluation 1 for linear characteristics below 1 KHz. [Figure 47] FIG. 47 is a graph showing the evaluation results of response differential active intensity by two-microphone intensity evaluation 2 for linear characteristics below 1 KHz. [Figure 48] FIG. 48 is a graph showing the evaluation results of the difference in active intensity in the two-microphone intensity evaluation 1 for linear characteristics above 1 KHz. [Figure 49] FIG. 49 is a graph showing the evaluation results of the ratio of active intensity in the two-microphone intensity evaluation 1 for linear characteristics above 1 KHz. [Figure 50] FIG. 50 is a graph showing the evaluation results of the differential transfer characteristic by the single-microphone frequency characteristic evaluation 1 in the auxiliary structural state analysis. [Figure 51] FIG. 51 is a graph showing the evaluation results of the ratio of active intensity by the two-microphone intensity evaluation 1 in the auxiliary structural state analysis. [Figure 52] FIG. 52 is a graph showing the evaluation results of the difference in active intensity in the two-microphone intensity evaluation 1. [Diagram 53] FIG. 53 is a graph showing the evaluation results of the difference in reactive intensity in the two-microphone intensity evaluation 1. [Figure 54] FIG. 54 is a graph showing the evaluation results of the active intensity ratio at a sound pressure ratio of 6 dB / 3 dB using two-microphone intensity evaluation 1 in the auxiliary structural condition analysis. [Figure 55] FIG. 55 is a graph showing the evaluation results of the active intensity ratio at a sound pressure ratio of 9 dB / 3 dB using two-microphone intensity evaluation 1 in the auxiliary structural condition analysis. [Figure 56] FIG. 56 is a diagram showing the layout relationship between the speaker, microphone, and diagnosis object. [Figure 57]FIG. 57 is a flowchart showing the procedure of diagnostic processing based on an analysis method different from the analysis methods shown in FIGS. [Figure 58] FIG. 58 is a graph showing the evaluation results of the transfer characteristics in a frequency band of 1 KHz or less. [Figure 59] FIG. 59 is a graph showing the evaluation results of the differential transfer characteristics in a frequency band of 1 KHz or less. [Figure 60] FIG. 60 is a graph showing the evaluation results of the transfer characteristics in the frequency band of 1 KHz or more. [Figure 61] FIG. 61 is a graph showing the evaluation results of the differential transfer characteristic in a frequency band of 1 KHz or more. [Figure 62] FIG. 62 is a graph showing the evaluation results of active intensity in a frequency band of 1 KHz or less. [Figure 63] FIG. 63 is a graph showing the evaluation results of the difference in active intensity in a frequency band of 1 KHz or less. [Figure 64] FIG. 64 is a graph showing the evaluation results of active intensity in the frequency band above 1 KHz. [Figure 65] FIG. 65 is a graph showing the evaluation results of the difference in active intensity in the frequency band of 1 KHz or more. [Figure 66] FIG. 66 is a graph showing the evaluation results of sound absorption coefficient in the frequency band of 1 KHz or less. [Figure 67] FIG. 67 is a graph showing the evaluation results of the difference in sound absorption coefficient in the frequency band of 1 KHz or less. [Figure 68] FIG. 68 is a graph showing the evaluation results of sound absorption coefficient in the frequency band of 1 KHz or more. [Figure 69] FIG. 69 is a graph showing the evaluation results of the difference in sound absorption coefficient in the frequency band of 1 KHz or more. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0010] (Functional configuration) First, the functional configuration of an acoustic diagnostic device according to an embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram showing an example of the functional configuration of an acoustic diagnostic device 1 according to an embodiment. The acoustic diagnostic device 1 is a device that diagnoses a diagnosis object 90 using sound waves.

[0011] The acoustic diagnostic device 1 includes an acoustic excitation section 10, a sound receiving section 20, a diagnostic processing section 30, and a display 50.

[0012] The acoustic excitation unit 10 acoustically excites the diagnosis object 90. Here, acoustically exciting the diagnosis object 90 means emitting sound waves toward the diagnosis object 90 and applying vibration to the diagnosis object 90. For example, the acoustic excitation unit 10 has one or more speakers 11. The speakers 11 emit sound waves for acoustic excitation toward the diagnosis object 90.

[0013] The speaker 11 radiates sound waves forward from its front face 12. The speaker 11 is disposed so that its front face 12 faces an object to be diagnosed 90. The object to be diagnosed 90 has a plane 91. The speaker 11 is disposed so that its front face 12 is parallel to the plane 91 of the object to be diagnosed 90. Hereinafter, an axis passing through the sound source center of the speaker 11 and perpendicular to the front face 12 of the speaker 11 is referred to as the speaker axis 13. In addition, the direction on the speaker axis 13 away from the speaker 11 is referred to as the radiation direction of the sound waves for acoustic excitation.

[0014] The acoustic excitation unit 10 may also have a movement mechanism 18 that moves the speaker 11 on a plane perpendicular to the speaker axis 13 .

[0015] The sound receiving unit 20 has two or more microphones. Hereinafter, the microphones will be abbreviated to simply be referred to as microphones. For example, the sound receiving unit 20 has a first microphone 21 and a second microphone 22. The microphones 21 and 22 receive sound waves and output electrical sound receiving signals reflecting sound pressure. The sound waves received by the microphones 21 and 22 include evaluation target sounds including sound waves reflected from the diagnosis object 90 and vibration radiation sounds from the diagnosis object 90, radiation sounds from the speaker 11, and environmental reflection sounds.

[0016] The diagnosis processing unit 30 drives the speaker 11 and diagnoses the diagnosis target 90 based on the audio signals received by the microphones 21 and 22.

[0017] The display 50 displays the results of the diagnosis by the diagnosis processor 30 .

[0018] The diagnosis processing unit 30 includes an impulse response calculation unit 31, a structural condition analysis unit 32, a structural condition diagnosis unit 33, and an acoustic excitation signal generation unit .

[0019] The impulse response calculation unit 31 calculates the impulse response of each of the first microphone 21 and the second microphone 22 based on the sound signals received by the first microphone 21 and the second microphone 22 .

[0020] The structural condition analysis unit 32 calculates acoustic characteristics using the impulse responses of the first microphone 21 and the second microphone 22, and analyzes the condition of the diagnosis object 90.

[0021] The structural condition diagnosis section 33 evaluates the acoustic characteristics based on the analysis results of the structural condition analysis section 32 and diagnoses the condition of the diagnosis object 90 .

[0022] The acoustic excitation signal generating unit 34 generates an acoustic excitation signal for causing the speaker 11 to emit sound waves for acoustic excitation, and continuously inputs the acoustic excitation signal to the speaker 11. The speaker 11 emits sound waves for acoustic excitation in response to the input of the acoustic excitation signal. The acoustic excitation signal is a TSP (Time Stretched Pulse) signal. For example, the acoustic excitation signal is a Logss (Log Swept Sine) signal, which is a type of TSP signal and can separate nonlinear characteristics. When the Logss signal is used, it is possible to monitor not only linear characteristics but also changes in nonlinear characteristics.

[0023] The acoustic diagnostic device 1 acoustically vibrates the diagnosis object 90 using the acoustic excitation unit 10, measures the vibration of the diagnosis object 90 using the sound receiving unit 20, and evaluates the acoustic characteristics. However, this is not limiting, and if the vibration of the diagnosis object 90 can be measured using a laser Doppler vibrometer (LDV), LDV measurement may be performed. In the evaluation of acoustic characteristics, changes in the state of the back surface of the diagnosis object 90, which cannot be measured by LDV, can be evaluated by the intensity, which is correlated with the sound absorption coefficient, or the sound absorption coefficient.

[0024] (Hardware configuration) Next, a description will be given of the hardware configuration of the diagnostic processing unit 30. The diagnostic processing unit 30 is configured with a computer. For example, the diagnostic processing unit 30 is configured with a personal computer, a server computer, or the like.

[0025] Fig. 2 is a block diagram showing an example of a hardware configuration of the diagnostic processing unit 30 according to the embodiment. As shown in Fig. 2, the diagnostic processing unit 30 has an input I / F 41, a CPU 42, a storage device 45, and an output I / F 49. The worker allocation device may further have other peripheral devices in addition to these.

[0026] The input I / F 41, CPU 42, storage device 45, and output I / F 49 are electrically connected to one another via a bus BS, and exchange data and commands via the bus BS.

[0027] The input I / F 41 is a device that receives signals from the outside, converts them into data, and passes them to the CPU 42 and the storage device 45 .

[0028] The output I / F 49 is a device that receives data from the CPU 42 and the storage device 45, converts it into a signal, and outputs it.

[0029] The storage device 45 stores programs and data necessary for processing executed by the CPU 42. The CPU 42 reads out necessary programs and data from the storage device 45 and executes them to perform various types of processing.

[0030] The storage device 45 includes a ROM 46, a main storage device 47, and an auxiliary storage device 48. The main storage device 47 and the auxiliary storage device 48 exchange programs and data with each other.

[0031] The ROM 46 stores a program (BIOS) that controls the CPU 42 at startup.

[0032] The main storage device 47 stores programs and data temporarily required for processing by the CPU 42. For example, the main storage device 47 is configured with a volatile memory such as a RAM (Random Access Memory).

[0033] The auxiliary storage device 48 stores programs and data supplied via an external device or a network, and provides programs and data temporarily required for processing by the CPU 42 to the main storage device 47. For example, the auxiliary storage device 48 is configured with a non-volatile memory such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive).

[0034] The CPU 42 is a processor, and is hardware that processes data and instructions. The CPU 42 includes a control device 43 and an arithmetic unit 44.

[0035] The control device 43 controls the input I / F 41 , the arithmetic unit 44 , the storage device 45 and the output I / F 49 .

[0036] The arithmetic unit 44 reads the program and data from the main memory device 47 , executes the program to process the data, and provides the processed data to the main memory device 47 .

[0037] In such a hardware configuration, the CPU 42 and the storage device 45 constitute the various parts of the diagnosis processing unit 30, that is, the impulse response calculation unit 31, the structural condition analysis unit 32, the structural condition diagnosis unit 33, and the acoustic vibration signal generation unit .

[0038] For example, the CPU 42 loads a program for executing the functions of the diagnostic processing unit 30 from the auxiliary storage device 48 into the main storage device 47, and executes the loaded program to perform the operation of the diagnostic processing unit 30.

[0039] (Acoustic excitation unit 10) Next, referring to FIG. 3, a configuration example of the acoustic excitation unit 10 will be described. FIG. 3 is a diagram showing four configuration examples 3A, 3B, 3C, and 3D of the acoustic excitation unit 10. In the configuration example 3A, the acoustic excitation unit 10 has a single speaker 15. In the configuration example 3B, the acoustic excitation unit 10 has a directional single sound source in which an acoustic tube 16 is attached to the single speaker 15 to enhance the directivity. In the configuration example 3C, the acoustic excitation unit 10 has a speaker group in which a plurality of single speakers 15 are arranged on a circumference and driven in phase. In the configuration example 3D, the acoustic excitation unit 10 has a speaker group in which a plurality of single speakers are arranged on a grid and output a plane wave in a simulated manner. In addition, the acoustic excitation unit 10 may have a general-purpose planar speaker.

[0040] (Sound receiving section 20) As described above, the sound receiving unit 20 has two or more microphones. Here, referring to FIG. 4, configuration examples of each microphone will be described. FIG. 4 is a diagram showing five configuration examples 4A, 4B, 4C, 4D, and 4E of the single microphone 25 applied to each of the microphones 21 and 22. The single microphone 25 of the configuration example 4A is an omnidirectional microphone. The single microphone 25 of the configuration example 4B is a directional microphone. The single microphone 25 of the configuration example 4C is a gun microphone and has very high directivity. The single microphone 25 of the configuration example 4D is a line array microphone. The line array microphone has multiple microphones 25a, but outputs a delay sum output, so it can be said to be a single microphone. The single microphone 25 of the configuration example 4E is a circle array microphone. The circle array microphone has multiple microphones 25a, but outputs a sum output, so it can be said to be a single microphone.

[0041] Next, configuration examples of the first and second microphones 21, 22 of the sound receiving unit 20 will be described with reference to Fig. 5. Fig. 5 is a diagram that shows two configuration examples 5A and 5B of the first and second microphones 21, 22. In configuration example 5A, the first and second microphones 21, 22 are both omnidirectional microphones. In configuration example 5B, the first and second microphones 21, 22 are both directional microphones.

[0042] Next, with reference to Fig. 6, the difference between when the microphone of the sound receiving unit 20 is an omnidirectional microphone and when it is a directional microphone will be described. Fig. 6 is a diagram showing two configuration examples 6A and 6B of the sound receiving unit 20. The sound receiving unit 20A of the configuration example 6A has an omnidirectional microphone. The sound receiving unit 20B of the configuration example 6B is a directional microphone.

[0043] 6, arrow Sa represents sound radiated from speaker 11, arrow Sb represents sound reflected from diagnosis object 90, and arrow Sc represents vibration radiated sound from diagnosis object 90. The thickness of arrows Sa, Sb, and Sc represents the magnitude of sound waves received by sound receiving sections 20A and 20B.

[0044] The sound receiving unit 20A of the configuration example 6A has an omnidirectional microphone, and therefore receives a large amount of sound radiated from the speaker 11. On the other hand, the sound receiving unit 20B of the configuration example 6B has a directional microphone, and therefore receives a small amount of sound radiated from the speaker 11. For this reason, the sound receiving unit 20B having a directional microphone has a higher contribution to acquiring reflected sound and vibration radiated sound that indicate changes in acoustic characteristics of the diagnosis target 90, compared to the sound receiving unit 20A having an omnidirectional microphone.

[0045] (Diagnosis processing by diagnosis processing unit 30) Next, a procedure of diagnosis executed by the diagnosis processor 30 will be described with reference to Fig. 7. Fig. 7 is a flowchart showing the procedure of diagnosis executed by the diagnosis processor 30. Here, it is assumed that the acoustic excitation signal generator 34 continuously inputs a nonlinearly separable Logss signal to the speaker 11 as the acoustic excitation signal.

[0046] In step S1, the impulse response calculation unit 31 receives the sound signals from the microphones 21 and 22, and calculates the impulse responses of the microphones 21 and 22.

[0047] In step S2, the waveforms of the linear characteristic section and each distortion characteristic section are extracted from the impulse response.

[0048] Here, since a Logss signal is used as the acoustic excitation signal, the process of extracting the impulse response in step S2 is performed. However, when a TSP signal other than the Logss signal is used as the acoustic excitation signal, the process of extracting the impulse response in step S2 is omitted.

[0049] In step S3, the structural state analysis unit 32 performs structural state analysis based on the waveforms of the extracted linear characteristic section and each distortion characteristic section. The structural state analysis unit 32 performs structural state analysis based on four types of analysis methods. The four types of structural state analysis will be described later.

[0050] In step S4, the structural condition diagnosis unit 33 diagnoses the structural condition of the diagnosis object 90 based on the analysis by the structural condition analysis unit 32. The diagnosis method will be described later.

[0051] (Four types of analysis methods) Next, structural condition analyses based on four types of analysis methods implemented by the structural condition analysis unit 32 will be described. For convenience, the four types of analysis methods will be referred to as single-microphone frequency characteristic evaluation 1, single-microphone frequency characteristic evaluation 2, two-microphone intensity evaluation 1, and two-microphone intensity evaluation 2, respectively. In single-microphone frequency characteristic evaluation 1 and single-microphone frequency characteristic evaluation 2, a signal received from a single microphone, either the first or second microphone, is used to evaluate frequency characteristics. In two-microphone intensity evaluation 1 and two-microphone intensity evaluation 2, an intensity evaluation is performed using signals received from both the first and second microphones. Each structural condition analysis will be described below.

[0052] (Single microphone frequency response evaluation 1) First, a processing procedure of single-microphone frequency characteristic evaluation 1 will be described with reference to Fig. 8. Fig. 8 is a flowchart showing the processing procedure of single-microphone frequency characteristic evaluation 1.

[0053] Since the extracted impulse response has a short signal length, if FFT is performed on it as is, the frequency resolution will decrease. To avoid this, in step S11, 0s are inserted at the end of the extracted impulse response of a single microphone so that the signal length is equal to that before extraction, and FFT is performed on the impulse response after the insertion.

[0054] If the FFT results are used as is in the high frequency range above 1 kHz, the changes in the gain and phase characteristics will be noisy. To avoid this, in step S12, frequency characteristic smoothing is performed on the gain and phase characteristics. For example, averaging of ±several Hz is performed on each of the gain and phase characteristics.

[0055] Finally, in step S13, frequency characteristics are evaluated. Specifically, a comparison of the transfer characteristics with a reference state is displayed. For example, the transfer characteristics are displayed overlapping the reference state, or the difference between the transfer characteristics and the reference state is displayed.

[0056] (Single microphone frequency response evaluation 2) Next, a processing procedure of single-microphone frequency characteristic evaluation 2 will be described with reference to Fig. 9. Fig. 9 is a flowchart showing the processing procedure of single-microphone frequency characteristic evaluation 2.

[0057] First, in step S21, the difference between a reference measurement cut-out impulse response measured under a reference condition and a cut-out impulse response of a single microphone is calculated.

[0058] Since the extracted impulse response has a short signal length, if FFT is performed on it as is, the frequency resolution will decrease. To avoid this, in step S22, 0s are inserted at the end of the extracted differential impulse response so that the signal length is equal to that before extraction, and FFT is performed on the differential impulse response after the insertion.

[0059] If the FFT results are used as is in the high frequency range of 1 kHz or higher, the changes in the gain and phase characteristics will be noisy. To avoid this, in step S23, frequency characteristic smoothing is performed on the gain and phase characteristics. For example, averaging of ± several Hz is performed on each of the gain and phase characteristics.

[0060] Finally, in step S24, frequency characteristics are evaluated, for example, the differential transfer characteristics are displayed.

[0061] (2 mic intensity rating 1) Next, the processing procedure of the two-microphone intensity evaluation 1 will be described with reference to Fig. 10. Fig. 10 is a flowchart showing the processing procedure of the two-microphone intensity evaluation 1.

[0062] Since the extracted impulse response has a short signal length, if FFT is performed on it as is, the frequency resolution will decrease. To avoid this, in step S31, 0s are inserted at the end of the extracted impulse response of each of the two microphones so that the signal length is equal to that before extraction, and FFT is performed on the impulse response after insertion.

[0063] If the FFT results are used as is in the high frequency range above 1KHz, the changes in the gain and phase characteristics will be noisy, and the intensity characteristics will not be displayed correctly. To avoid this, in step S32, frequency characteristic smoothing is performed on the gain and phase characteristics. For example, the gain and phase characteristics are each averaged at ± several Hz, and then converted to complex numbers for each frequency. Furthermore, the smoothed FFT values ​​are used to calculate the active intensity and reactive intensity.

[0064] Finally, in step S33, the intensity characteristics are evaluated. Specifically, the intensity characteristics are compared with a reference state and displayed. For example, the intensity characteristics are displayed overlapping with the reference state, or the difference or ratio between the intensity characteristics and the reference state is displayed.

[0065] (2 mic intensity rating 2) Finally, the procedure of the two-microphone intensity evaluation 2 will be described with reference to Fig. 11. Fig. 11 is a flowchart showing the procedure of the two-microphone intensity evaluation 2.

[0066] First, in step S41, the difference between a reference measurement cut-out impulse response measured in a reference state and each of the cut-out impulse responses of the two microphones is calculated.

[0067] Since the extracted impulse response has a short signal length, if FFT is performed on it as is, the frequency resolution will decrease. To avoid this, in step S42, 0 is inserted at the end of each of the extracted differential impulse responses of the two microphones so that the signal length is equal to that before extraction, and FFT is performed on each of the differential impulse responses of the two microphones after the insertion.

[0068] If the FFT results are used as is in the high frequency range above 1KHz, the changes in the gain and phase characteristics will be noisy, and the intensity characteristics will not be displayed correctly. To avoid this, in step S43, frequency characteristic smoothing is performed on the gain and phase characteristics. For example, an averaging process of ± several Hz is performed on each of the gain and phase characteristics, and then the characteristics are converted into complex numbers for each frequency. Furthermore, the smoothed FFT values ​​are used to calculate the active intensity and reactive intensity.

[0069] Finally, in step S44, the intensity characteristics are evaluated, for example, the active intensity and the reactive intensity are displayed.

[0070] (auxiliary structural state analysis) Here, the processing procedure of the auxiliary structural condition analysis will be described with reference to Fig. 12. Fig. 12 is a flowchart showing the processing procedure of the auxiliary structural condition analysis. This auxiliary structural condition analysis is applied auxiliary to the above-mentioned single-microphone frequency characteristic evaluation 1 or two-microphone intensity evaluation 1, and is not necessarily required to be performed.

[0071] First, in step S51, the speaker 11 is acoustically excited while changing the acoustic excitation volume (+0 dB (reference volume is 0 dB), +3 dB, +6 dB, . . . ) in sequence.

[0072] In step S52, sound signals are received from the microphones 21 and 22, and the impulse responses of the microphones 21 and 22 are calculated.

[0073] In step S53, the waveforms of the linear characteristic section and each distortion characteristic section are extracted from the impulse response.

[0074] In step S54, single-microphone frequency characteristic evaluation 1 or two-microphone intensity evaluation 1 is performed.

[0075] In step S55, the acoustic excitation volume of +0 dB is set as the reference state, and the difference characteristic of the single microphone frequency characteristic evaluation 1 or the ratio characteristic of the two microphone intensity evaluation 1 at each volume is displayed.

[0076] In the evaluation of the linear characteristic section, linear changes are confirmed, and if there is a deviation, it can be determined that there is a problem with the measurement environment. In the nonlinear characteristic section (distortion characteristics), the change is not linear, so by monitoring the change in the characteristics in each state, it is possible to assist in diagnosing deterioration.

[0077] (acoustic excitation signal) As described above, the acoustic excitation signal is a TSP (Time Stretched Pulse) signal. Here, a Logss (Log Swept Sine) signal will be described as an example of a TSP signal. Also, a method for calculating the distortion occurrence time in a Logss signal will be described. For example, the definition equation of the frequency characteristic of a Logss signal is expressed by Equation (1) to Equation (3). Note that N is the Logss signal length, q is an arbitrary real number (J is a multiple of 2), N and q are setting variables, and j is an imaginary number.

[0078]

number

[0079] From equations (1) to (3), the Logss signal is expressed by equation (4). Re represents the real part, and IFFT represents the inverse Fourier transform.

[0080]

number

[0081] A commonly used TSP signal is expressed by the following equation (5): where m is an integer.

[0082]

number

[0083] At this time, the sampling frequency f s 44.1KHz, Logss signal length N is 65536(2 16 ), and q is 3 / 4, the signal of equation (4) is expressed as shown in FIG. 13. A signal obtained by shifting the signal shown in FIG. 13 by (NJ) / 2 is expressed as shown in FIG. 14. In FIG. 13 and FIG. 14, the vertical axis indicates the level of the voltage applied to the speaker (level adjusted by the connected speaker amplifier), and the horizontal axis indicates time [s]. A Logss signal is generated based on equations (1) to (4), and the signal shifted by (NJ) / 2 is used as an acoustic excitation signal, that is, an input signal to the speaker. Note that the amount of shift is not limited to the above-mentioned value, and for example, as shown in FIG. 14, it is possible to shift the signal from 0 s (1 tap) to 0.1 s (0.1×f s The tap values ​​of tap may be set so that the change in the value near the initial tap is small.

[0084] FIG. 15 shows a spectrogram of the Logss signal after the shift shown in FIG. 14. The vertical axis indicates frequency [Hz], and the horizontal axis indicates time [s]. In the spectrogram shown in FIG. 15, when the vertical and horizontal axes are interchanged, it can be seen that the spectrogram changes like a logarithmic function. That is, the logarithmic frequency is proportional to time, and the frequency is an exponential function of time. Therefore, the relationship between time and frequency in the spectrogram of the Logss signal is expressed by equations (6) to (8). Note that, t offset is the offset time, and shift is the shift amount of the Logss signal described above.

[0085]

number

[0086] Fig. 16 is a graph showing the relationship between time and frequency in the spectrogram of the Logss signal expressed by equations (6) to (8). In Fig. 16, the vertical axis represents frequency [Hz], and the horizontal axis represents time [s].

[0087] At this time, if harmonic distortion of the Logss signal occurs in a state where there is no dynamics characteristic, the graph shown in Fig. 17 will be obtained. Fig. 17 is a spectrogram when harmonic distortion occurs in the Logss signal having the spectrogram shown in Fig. 16. Line L1 is the fundamental wave response curve expressed by equations (6) to (8), line L2 is the second harmonic response curve (first-order distortion response curve), line L3 is the third harmonic response curve (second-order distortion curve), line L4 is the fourth harmonic response curve (third-order distortion curve), and line L5 is the fifth harmonic response curve (fourth-order distortion curve).

[0088] When such harmonic distortion of the Logss signal occurs, the measured response curve is converted by the inverse characteristic of the Logss signal to obtain the graph shown in FIG. 18. FIG. 18 shows an impulse response obtained by converting the response curve of the Logss signal, which is the spectrogram shown in FIG. 17, by the inverse characteristic of the Logss signal. The vertical axis indicates frequency [Hz], and the horizontal axis indicates time [s]. Line L1A, line L2A, line L3A, line L4A, and line L5A are the response curves of lines L1 to L5, respectively. Line L1B is an impulse response corresponding to the fundamental response. Line L2B is an impulse response (distortion characteristic of first-order distortion) corresponding to the second harmonic response. Line L3B is an impulse response (distortion characteristic of second-order distortion) corresponding to the third harmonic response. Line L4B is an impulse response (distortion characteristic of third-order distortion) corresponding to the fourth harmonic response. Line L5B is an impulse response (distortion characteristic of fourth-order distortion) corresponding to the fifth harmonic. The impulse response corresponding to the harmonic response calculated in this way appears in the time domain before time 0, that is, in the negative time domain (non-causal direction domain). However, if the distance between the speaker and the microphone is long, the rise time of the linear response is delayed, so that the impulse response corresponding to the harmonic response may occur in the positive time domain. Here, for simplicity, a description is given under the condition of no time delay (no dynamics characteristics). Then, the impulse response corresponding to the harmonic response is separated into distortions of each order in the non-causal direction domain. In this embodiment, by using a Logss signal as an input signal, the impulse response is separated into distortions of each order, and the distortions of each order can be analyzed using the distortion characteristics of the distortions of each order. In a normal TSP, only a linear response can be obtained.

[0089] Moreover, by separating the distortion characteristics as described above, the distortion characteristics of each order are separated into different time domains. At this time, the occurrence time (-t(num)) [s] of the distortion characteristic of each order is expressed by equation (7). Here, num is the order of distortion. For example, when set as described above, the occurrence time of the distortion characteristic shown in FIG. 18 will be as shown in FIG. 19. In FIG. 19, the horizontal axis is the distortion order, and the vertical axis is the time [s].

[0090]

number

[0091] Then, from the occurrence time of the distortion characteristic of each order based on the impulse response corresponding to the fundamental wave response, the distortion occurrence time in the derived impulse response is expressed by Equation (8) due to the repetitive nature of the discrete Fourier transform.

[0092]

number

[0093] Here, ta is the delay time of the dynamics characteristics (also called "dead time") and is determined as L / c by the distance L between the speaker and the microphone. Here, c is the speed of sound. Strictly speaking, the delay characteristics of the speaker and the system are also added to ta. ta corresponds to the rise time of the first wave in the causal direction that satisfies the causality rate, which is the opposite direction to the non-causal direction. For example, if the distance L between the speaker and the microphone is sufficiently short and ta can be considered to be 0, with the settings mentioned above, the time at which distortion occurs in the impulse response will be as shown in Figure 20. In Figure 20, the horizontal axis is the distortion order and the vertical axis is time [s].

[0094] (Method of calculating impulse response from TSP signal) The above-mentioned TSP signal is input to a speaker amplifier as a speaker application voltage to drive the speaker 11.

[0095] The microphones 21 and 22 of the sound receiving unit 20 measure, as sound pressure, the direct sound from the speaker 11 accompanying the speaker acoustic excitation, the reflected sound from the diagnosis object 90, and the vibration radiated sound from the diagnosis object 90. In the case of LDV measurement, the vibration velocity of the diagnosis object 90 is measured.

[0096] The impulse response calculation unit 31 calculates an impulse response based on the speaker applied voltage and the microphone acquired sound pressure response. The speaker applied voltage is generated based on a signal in which one TSP (Logss, etc.) signal is arranged a predetermined number of times. The impulse response calculation unit averages the sound pressure changes from the second time onwards in the received signal, with the signal length of the TSP (Logss, etc.) signal being one time. The impulse response calculation unit 31 performs a fast Fourier transform (FFT) on the averaged signal. In the frequency domain, the impulse response calculation unit multiplies the inverse characteristic of the TSP (Logss, etc.) signal in the speaker applied voltage by the signal after FFT processing. The impulse response calculation unit calculates an impulse response by performing an inverse fast Fourier transform (inverse FFT) on the signal after multiplication processing.

[0097] The TSP signal may be filtered by a bandpass filter to match the frequency band that the speaker 11 can output, and used as the speaker applied voltage. This allows the speaker output level (speaker amplifier) ​​to be increased. At this time, the impulse response calculation unit may appropriately correct the influence of filtering by the bandpass filter in the processing in the frequency domain.

[0098] FIG. 21 is a diagram showing an example of an impulse response calculated as described above with the above settings. In FIG. 21, the horizontal axis indicates time [s], and the vertical axis indicates the level of the impulse response. The impulse response shown in FIG. 21 is derived from the microphone response of the sound receiving unit 20 to the speaker acoustic excitation based on the Logss signal. The impulse response is a dynamics characteristic including the speaker characteristic, the acoustic space characteristic, and the acoustic characteristic of the diagnosis target object 90. Therefore, the linear characteristic of the dynamics characteristic appears in the region Ra, and the nonlinear characteristic (distortion characteristic) of the dynamics characteristic appears in the region Rb. The region Ra corresponds to the time (about several seconds) from a time slightly before the time corresponding to the peak value of the impulse response until the occurrence of the residual response (reverberation response) (linear characteristic section). The region Rb is set in a region other than the region Ra according to the distortion occurrence time in FIG. 20.

[0099] Fig. 22 is an enlarged view of a region Rb corresponding to the nonlinear characteristics of the impulse response. In Fig. 22, the horizontal axis indicates time and the vertical axis indicates the level of the impulse response. From Fig. 20, a first-order distortion p1, a second-order distortion p2, and a third-order distortion p3 appear in the order shown in Fig. 22.

[0100] (Intensity calculation method) Next, a method for finding the intensity on a line segment connecting a first microphone 21 and a second microphone 22 that are placed at an interval of a distance d will be described. Here, the first microphone 21 is set as a reference, and the microphones 21, 22 are arranged in the order of the first microphone 21 and the second microphone 22 in the positive direction of the intensity measurement axis.

[0101] During acoustic vibration measurement, if the transfer characteristic obtained through the first microphone 21 is G1(ω) and the transfer characteristic obtained through the second microphone 22 is G2(ω), the active intensity, which represents the flow of sound wave energy on the measurement axis, can be calculated using the following equation (11).

[0102]

number

[0103] Each transfer characteristic is calculated by applying FFT to the impulse response. If the TSP signal is a Logss signal, zeros are inserted into the extracted impulse response and the FFT is applied to calculate the transfer characteristic.

[0104] The measurement range frequency is f corresponding to λ=10d because the particle velocity is approximated using two microphones 21 and 22 spaced apart by a distance d. max Taking into account the measurement accuracy, the upper limit of the measurement frequency is set to approximately =c / (10d).

[0105] Moreover, the reactive intensity, which means the sound pressure squared gradient, is calculated by the following equation (12).

[0106]

number

[0107] As mentioned above, at high frequencies above 1 kHz, if the FFT value is used as is, the intensity characteristic display will be noisy, so the FFT value is converted to a complex number by averaging the gain and phase at a few Hz before and after the frequency, and then the intensity is calculated.

[0108] Measurement examples when the microphone distance d = 5 mm are shown in Figures 23 and 24. Figure 23 is a graph of an example of active intensity measurement. Figure 24 is a graph of an example of reactive intensity measurement. Note that the FFT values ​​used were obtained by averaging the gain and phase at around 20 Hz and then converting them back to complex numbers.

[0109] (Acoustic evaluation) Here, the change in sound pressure will be described with reference to Figs. 25 to 27. Fig. 25 is a diagram that shows a diagnosis object 90 in a basic state and one microphone 21. Fig. 26 is a diagram that shows a state in which the sound absorption characteristics of the diagnosis object 90 have decreased compared to the reference state. Fig. 27 is a diagram that shows a state in which the micro-vibrations of the diagnosis object 90 have increased compared to the reference state.

[0110] The physical meaning of the change in sound pressure from the base state (Figure 25) is that when the sound pressure of microphone 21 increases, it is assumed that the sound absorption characteristics have decreased (Figure 26) or that micro-vibrations have increased (Figure 27) compared to the reference state. Conversely, when the sound pressure of microphone 21 decreases, it is assumed that the sound absorption characteristics have increased or that micro-vibrations have decreased compared to the reference state. However, with sound pressure evaluation, changes may not be captured accurately due to the effects of environmental reflection, and there are also issues with high dependency on the measurement point, such as sound wave interference. Even if an accurate evaluation is not obtained, the tendency of change can be captured.

[0111] Next, changes in active intensity will be described with reference to Figs. 28 to 30. Fig. 28 is a diagram that typically shows a diagnosis object 90 and two microphones 21 and 22 in a basic state. Fig. 29 is a diagram that typically shows an increase in the sound absorption characteristics of the diagnosis object 90 compared to the reference state. Fig. 30 is a diagram that typically shows a decrease in the micro-vibrations of the diagnosis object 90 compared to the reference state.

[0112] The physical meaning of the intensity change (positive direction: toward the diagnosis target 90) from the base state (Fig. 28) is that when the measured active intensity value increases, it is assumed that the sound absorption characteristics have increased compared to the reference state (Fig. 29) or that micro-vibrations have decreased (Fig. 30). Conversely, when the measured active intensity value decreases, it is assumed that the sound absorption characteristics have decreased compared to the reference state or that micro-vibrations have increased. Because the flow of energy on the measurement axis is acquired, the effects of environmental reflections can be reduced compared to a single microphone, and changes in the acoustic characteristics of the diagnosis target 90 can be captured more accurately.

[0113] In addition, since reactive intensity means the gradient of the square of sound pressure, it is difficult to interpret the change in value, but it can similarly capture the change in the acoustic characteristics of the object to be diagnosed.

[0114] Furthermore, the acoustic excitation center may be moved on a plane using, for example, the moving mechanism 18 shown in FIG. 1. FIG. 31 is a diagram showing the movement of the acoustic excitation center, i.e., the speaker center 11a, and the contour display of the measurement results. The speaker center 11a is moved along a trajectory T31 on a plane P31 parallel to the plane of the diagnosis object. The intensity measurement results are displayed as contour lines C29 for the intensity at each measurement point for each frequency of interest. The display using the contour lines C29 makes it easy to compare with the reference state. In addition, since reactive intensity means the sound pressure squared gradient, it can be used to determine the position of the sound source (vibration radiation sound, etc.).

[0115] (Structural condition diagnosis) Next, a description will be given of diagnostic methods executed by the structural condition diagnostic unit 33. Three diagnostic methods will be described here.

[0116] The first diagnostic method is a commonly used method for deterioration diagnosis, and involves comparison with a baseline. In this method, measurements are carried out in advance when failure modes (reduction in bonding strength, welding defects, cracks, and cavities) occur, and a baseline within the allowable range is also measured. The measurement and analysis data obtained by the structural condition analysis unit 32 is compared with the baseline to determine whether the condition has shifted to the danger line.

[0117] For example, Fig. 32 is a graph showing the baseline and measurement analysis data of the ratio of active intensity. This graph was obtained by the two-microphone intensity evaluation 1 of Fig. 10. In Fig. 32, line L300 is a baseline curve. Lines L301, L302, and L303 are curves of measurement analysis data of the ratio of active intensity obtained in measurements 1, 2, and 3, respectively. Here, measurement 1 represents the measurement performed first, measurement 2 represents the measurement performed after measurement 1, and measurement 3 represents the measurement performed after measurement 2.

[0118] Line L301 of measurement 1 is generally below baseline line L300 at all frequencies. On the other hand, line L302 of measurement 2 and line L303 of measurement 3 are significantly above baseline line L300 in the frequency band of 640 to 680 Hz. For this reason, measurement 1 is determined to be normal, and measurements 2 and 3 are determined to be abnormal.

[0119] Here, a method for determining that there is an abnormality when the measurement analysis data exceeds the baseline has been shown, but there is also a method for determining that there is an abnormality when the measurement analysis data falls below the baseline.

[0120] The second diagnostic method is a diagnosis of the progression of deterioration due to aging, in which time-series change monitoring is used to detect whether the measurement analysis data obtained by the structural condition analysis unit 32 is on an increasing or decreasing trend, and an abnormality is determined. For example, in the graph of Fig. 32, in the frequency band of 640 to 680 Hz, line L302 of measurement 2 is higher than line L302 of measurement 1, and line L303 of measurement 3 is higher than line L302 of measurement 2, confirming that the active intensity ratio is on an increasing trend, and an abnormality is determined.

[0121] The third diagnostic technique is a method of diagnosing the peeling of vibration-damping material attached to the diagnostic object 90, in which the diagnostic object 90, such as a board material (surface material), obtains sound-absorbing characteristics by vibrating.

[0122] Fig. 33 is a diagram showing an increase in the micro-vibrations of the diagnosis object 90 after the vibration-damping material is peeled off (right side) compared to before the vibration-damping material is peeled off (left side). Fig. 34 is a diagram showing an increase in the sound absorption characteristics of the diagnosis object 90 after the vibration-damping material is peeled off (right side) compared to before the vibration-damping material is peeled off (left side).

[0123] Generally, when the damping material peels off, the plate becomes vibratory (Fig. 33) and the sound absorption characteristics increase (Fig. 34). In other words, the reflected sound decreases, so the sound pressure tends to decrease and the measured intensity increases. Here, the positive direction of measurement is the direction toward the diagnosis target 90.

[0124] However, in frequency bands where vibration radiation sound is prominent, the sound pressure tends to increase and the measured intensity may decrease, but since the contribution of vibration radiation sound is low in low frequency bands, monitoring the change in intensity can indirectly capture the change in sound absorption characteristics. Also, since the fluctuation in the natural frequency of the plate material occurs in the difference or ratio from the reference characteristic in the form of anti-resonance / resonance or resonance / anti-resonance, when these shapes occur, it can also be diagnosed as the effect of delamination. Of course, it is also possible to obtain and compare the frequency at which the maximum intensity is obtained in the frequency band near the natural frequency.

[0125] As described above, in the embodiment, the object to be diagnosed is acoustically excited, and signs of deterioration of the object to be diagnosed are detected from changes in acoustic characteristics (mainly linear characteristics). Since changes in acoustic characteristics are also caused by changes in the inside or back surface of a structure, it is possible to detect changes that cannot be evaluated by image diagnosis that diagnoses surface changes. Furthermore, when a Logss signal is used as the TSP signal, it is possible to perform not only linear characteristic evaluation, but also evaluation of distortion characteristics such as "chatter vibration". EXAMPLES

[0126] The validity of acoustic diagnosis according to the embodiment will be described below. An example of diagnosis of peeling of damping material will be described. First, various conditions of the peeling diagnosis will be described with reference to Figs. 35 and 36. Fig. 35 is a diagram showing the positional relationship of speaker 11, microphones 21 and 22, and diagnosis target 90 in an example of diagnosis of peeling of damping material. Fig. 36 is a diagram showing damping materials 361, 362, 363, and 364 attached to bottom plate 351a of steel can 351.

[0127] As shown in FIG. 35, the speaker 11 was placed on a stand 355. The diagnosis target 90 was a steel can 351 with a bottom plate 351a covered with a plastic cap 352. The steel can 351 was supported by a stand 353 placed on a stand 354. The speaker 11 and the diagnosis target 90 were arranged so that the front surface 12 of the speaker 11 and the plane 91 of the diagnosis target 90 were parallel to each other, and the distance D between the front surface 12 and the plane 91 was 300 mm. The first microphone 21 and the second microphone 22 were supported by an arm stand (not shown) at a distance of 5 mm and arranged between the speaker 11 and the diagnosis target 90. The measurement axis m12 passing through the first microphone 21 and the second microphone 22 was arranged on the speaker axis 13. The distance between the second microphone 22 and the plane 91 of the diagnosis target 90 was adjusted to 50 mm. The intensity measurement was performed by the first microphone 21 and the second microphone 22. The positive direction of measurement was the direction toward the diagnostic object 90.

[0128] In order to evaluate the validity of the intensity measurement, an LDV was placed on the opposite side of microphones 21 and 22 with respect to diagnosis target object 90, and LDV measurement was also performed from the back. Steel can 351 has bottom plate 351 covered with plastic cap 352, making it difficult to perform LDV measurement. In other words, the bottom plate vibration surface cannot be measured.

[0129] As shown in FIG. 36, measurements were taken for the following states: four vibration-damping materials 361-364 attached to the bottom plate 351a of steel can 351; three vibration-damping materials 361-363 attached; two vibration-damping materials 361-362 attached; one vibration-damping material 361 attached; and none of the vibration-damping materials 361-364 attached.

[0130] Hereinafter, for convenience, a state in which none of the damping materials 361 to 364 are attached will be referred to as a state in which 0 damping materials are attached. Also, a state in which n damping materials (n=0, 1, 2, 3, 4) are attached will be expressed simply as n. The state in which four damping materials 361 to 364 are attached will be defined as a reference state.

[0131] (LDV measurement) The results of the LDV measurement are shown in Figures 37 to 40. The LDV measurement was carried out at the center of the bottom plate 351a.

[0132] 37 is a graph showing the results of LDV measurement in the frequency band of 200 to 900 Hz. Lines L370, L371, L372, L373, and L374 are plots of the measurement results when the numbers of vibration-damping materials 361 to 364 are 0, 1, 2, 3, and 4, respectively.

[0133] 38 is a graph showing the difference in the results of LDV measurement in the frequency band of 200 to 900 Hz. Lines L380, L381, L382, and L383 are plots of the difference between the measurement results when the number of vibration-damping materials 361 to 364 is 0, 1, 2, and 3, respectively, and the measurement results when there are 4 reference materials.

[0134] 39 is a graph showing the results of LDV measurement in the frequency band of 1500 to 4000 Hz. Lines L390, L391, L392, L393, and L394 are plots of the measurement results when the numbers of vibration-damping materials 361 to 364 are 0, 1, 2, 3, and 4, respectively.

[0135] 40 is a graph showing the difference in the LDV measurement results in the frequency band of 1500 to 4000 Hz. Lines L400, L401, L402, and L403 are plots of the difference between the measurement results when the number of vibration-damping materials 361 to 364 is 0, 1, 2, and 3, respectively, and the measurement results in a reference state with 4 pieces.

[0136] In the graphs of Figures 37 to 40, a change in natural frequency due to peeling of the vibration-damping material can be seen in the frequency band around 400 Hz, and a decrease in damping due to peeling of the vibration-damping material can be seen in the frequency bands of 650 Hz to 750 Hz, 1600 to 1700 Hz, 2000 to 2200 Hz, and 3400 to 3600 Hz.

[0137] (acoustic excitation, acoustic measurement) Next, we will show whether some of the signs of deterioration among these characteristic changes can be detected by acoustic excitation and acoustic measurement. In other words, we will show that the above-mentioned changes in the back surface condition can be accurately detected as changes in acoustic characteristics.

[0138] (Evaluation of linear characteristics below 1KHz) First, the linear characteristics below 1KHz are evaluated in four ways: single microphone frequency characteristics evaluation 1, single microphone frequency characteristics evaluation 2, two microphone intensity evaluation 1, and two microphone intensity evaluation 2. In single microphone frequency characteristics evaluation 1 and single microphone frequency characteristics evaluation 2, a second microphone (mic A) was used for acoustic measurement.

[0139] (Single microphone frequency response evaluation 1,2) First, the evaluation results of the single-microphone frequency characteristic evaluation 1 are shown in FIG. 41, and the evaluation results of the single-microphone frequency characteristic evaluation 2 are shown in FIG.

[0140] 41 is a graph showing the evaluation results of differential transfer characteristics by single-microphone frequency characteristic evaluation 1. Lines L410, L411, L412, and L413 are plots of the differences between the measurement results when the numbers of damping materials 361-364 are 0, 1, 2, and 3, respectively, and the measurement results when the numbers are 4, which is a reference state.

[0141] 42 is a graph showing the evaluation results of response differential transfer characteristics by single-microphone frequency characteristic evaluation 2. Lines L420, L421, L422, and L423 are plots of the differences between the measurement results when the numbers of damping materials 361-364 are 0, 1, 2, and 3, respectively, and the measurement results in a reference state with 4 damping materials.

[0142] In both graphs showing the evaluation results of single microphone frequency characteristic evaluation 1 (Figure 41) and single microphone frequency characteristic evaluation 2 (Figure 42), changes due to peeling of the vibration-damping material can be confirmed in the frequency bands of 420 to 430 Hz and 650 to 700 Hz.

[0143] (2 mic intensity rating 1) Next, the evaluation results of the two-microphone intensity evaluation 1 are shown in Figs. 43, 44, 45, and 46.

[0144] 43 is a graph showing the evaluation results of active intensity by two-microphone intensity evaluation 1 in the frequency band of 320 to 500 Hz. Lines L430, L431, L432, L433, and L434 are plots of measurement results when the numbers of vibration-damping materials 361 to 364 are 0, 1, 2, 3, and 4, respectively.

[0145] 44 is a graph showing the evaluation results of active intensity in the 600 to 750 Hz frequency band by two-microphone intensity evaluation 1. Lines L440, L441, L442, L443, and L444 are plots of measurement results when the numbers of vibration-damping materials 361 to 364 are 0, 1, 2, 3, and 4, respectively.

[0146] 45 is a graph showing the evaluation results of the difference in active intensity I by the two-microphone intensity evaluation 1. Lines L450, L451, L452, and L453 are plots of the differences between the measurement results when the numbers of damping materials 361-364 are 0, 1, 2, and 3, respectively, and the measurement results when the numbers are 4, which is a reference state.

[0147] 46 is a graph showing the evaluation results of the ratio of active intensity I by the two-microphone intensity evaluation 1. Lines L460, L461, L462, and L463 are plots of the ratios of the measurement results when the number of vibration-damping materials 361-364 is 0, 1, 2, and 3, respectively, to the measurement result in the reference state where the number is 4.

[0148] In the graphs of Figures 45 and 46, it can be seen that in the frequency band of 400 to 450 Hz, the change in natural frequency due to the peeling of the damping material occurs in the shape of anti-resonance / resonance as described above. Also, in the frequency band of 650 to 700 Hz, an increase in active intensity due to the increase in sound absorption characteristics caused by the peeling of the damping material can be seen.

[0149] (2 mic intensity rating 2) Next, the evaluation results of the two-microphone intensity evaluation 2 are shown in Fig. 47. Fig. 47 is a graph showing the evaluation results of the response differential active intensity in the two-microphone intensity evaluation 2. Lines L470, L471, L472, and L473 are plots of the differences between the measurement results when the numbers of damping materials 361-364 are 0, 1, 2, and 3, respectively, and the measurement results in a reference state with 4 damping materials.

[0150] Unlike dual-microphone intensity evaluation 1, dual-microphone intensity evaluation 2 does not have a positive or negative physical meaning. However, in the graph of Figure 47, changes due to peeling of the vibration-damping material can also be confirmed in the frequency bands of 400 to 450 Hz and 650 to 700 Hz.

[0151] (summary) From the above, all four methods, Single Microphone Frequency Response Evaluation 1, Single Microphone Frequency Response Evaluation 2, Two Microphone Intensity Evaluation 1, and Two Microphone Intensity Evaluation 2, can obtain results equivalent to those of LDV measurement, and can be said to be effective measurement and diagnostic methods that can be used even in cases where LDV measurement is difficult (such as in this case, when the object to be diagnosed is not exposed). In particular, Two Microphone Intensity Evaluation 1 can reduce the effects of environmental reflections, and has positive and negative directions, leading to an understanding of the phenomenon of change, so it can be said to be a particularly effective evaluation method.

[0152] (Evaluation of linear characteristics above 1KHz) Next, the linear characteristics above 1KHz are evaluated using two-microphone intensity evaluation 1.

[0153] 48 is a graph showing the evaluation results of the difference in active intensity I by the two-microphone intensity evaluation 1. Lines L480, L481, L482, and L483 are plots of the differences between the measurement results when the numbers of damping materials 361-364 are 0, 1, 2, and 3, respectively, and the measurement results when the numbers are 4, which is a reference state.

[0154] 49 is a graph showing the evaluation results of the ratio of active intensity I by the two-microphone intensity evaluation 1. Lines L490, L491, L492, and L493 are plots of the ratios of the measurement results when the number of vibration-damping materials 361-364 is 0, 1, 2, and 3, respectively, to the measurement results in the reference state where the number is 4.

[0155] In the graphs of Figures 48 and 49, changes due to peeling of the damping material can be confirmed in the frequency bands of 2000 to 2200 Hz and 3400 to 3600 Hz. Specifically, the evaluation results for a single microphone are omitted, but the characteristic changes in the frequency band near 3500 Hz, where changes are difficult to confirm in the evaluation of a single microphone, can be evaluated in two-microphone intensity evaluation 1 as shown in the graphs of Figures 48 and 49. Furthermore, the change in the frequency band near 2000 Hz is a negative change, which can be considered to be due to an increase in vibration radiation sound caused by peeling of the damping material.

[0156] (auxiliary structural state analysis) Next, we will show the linear characteristic evaluation by auxiliary structural state analysis. Here, only the evaluation results by single microphone frequency characteristic evaluation 1 are shown in Figure 50 and Figure 51. The acoustic excitation volume was changed in the order of +0dB, +3dB, +6dB, and +9dB. A second microphone (mic A) was used for the acoustic measurement.

[0157] 50 is a graph showing the evaluation results of the differential transfer characteristic in single-microphone frequency characteristic evaluation 1. Line L500 and line L501 are plots of the differences between the measurement results at +6 dB, +9 dB and the measurement result at +3 dB, respectively.

[0158] 51 is a graph showing the evaluation results of the ratio of active intensity I in single-microphone frequency characteristic evaluation 1. Line L510 and line L511 are plots of the ratios of the measurement results at +6 dB and +9 dB to the measurement results at +3 dB, respectively.

[0159] When the vibration volume is increased to 3dB and 6dB, the graph in Figure 50 confirms that the sound pressure picked up by the microphone also increases, and the graph in Figure 51 confirms that the active intensity (which is energy, so the change is the square of the amplitude change) has doubled and quadrupled, respectively, confirming that there is no problem with the measurement environment. If there is a deviation from these changes, there is a problem with the measurement environment, and measures such as applying sound-absorbing treatment within the measurement environment are necessary.

[0160] (Evaluation of nonlinear characteristics above 1KHz) Next, we will show the evaluation of nonlinear characteristics (first-order distortion characteristics) above 1 kHz. Here, only the evaluation results of two-microphone intensity evaluation 1 are shown in Figures 52 and 53.

[0161] 52 is a graph showing the evaluation results of the difference in active intensity I by the two-microphone intensity evaluation 1. Lines L520, L521, L522, and L523 are plots of the differences between the measurement results when the numbers of damping materials 361-364 are 0, 1, 2, and 3, respectively, and the measurement results in a reference state with 4 damping materials.

[0162] 53 is a graph showing the evaluation results of the difference in reactive intensity Q by the two-microphone intensity evaluation 1. Lines L530, L531, L532, and L533 are plots of the differences between the measurement results when the numbers of damping materials 361-364 are 0, 1, 2, and 3, respectively, and the measurement results in a reference state with 4 damping materials.

[0163] In the graphs of Figures 52 and 53, changes in distortion characteristics due to peeling of the damping material can be confirmed in the frequency band of 3KHz to 3.4KHz. Since changes in distortion characteristics correspond to changes in nonlinear vibration radiation sound, when "chatter vibration" increases, the active intensity decreases (because the positive direction of intensity measurement is the direction toward the diagnosis target 90). By adopting a Logss signal as the acoustic excitation signal, it becomes possible to evaluate such distortion characteristics, and changes in characteristics other than linear characteristics such as changes in sound absorption coefficient and linear vibration radiation sound can also be treated as signs of deterioration.

[0164] In addition, as in this measurement, there are cases where the change in reactive intensity is more noticeable than the active intensity, so it is effective to monitor both the active and reactive intensity. This frequency band is also a frequency band where changes can be confirmed in LDV measurements (which are linear measurements), although the level is low.

[0165] (auxiliary structural state analysis) Next, we will show the evaluation of nonlinear characteristics (first-order distortion characteristics) above 1KHz using a supplementary structural state analysis. Here, only the evaluation results from two-microphone intensity evaluation 1 are shown in Figures 54 and 55. The acoustic excitation volume was changed in the order of +0dB, +3dB, +6dB, and +9dB. In single-microphone frequency characteristic evaluation 1, a second microphone (mic A) was used for acoustic measurement.

[0166] 54 is a graph showing the evaluation results of the ratio of active intensity I at a sound pressure ratio of 6 dB / 3 dB in two-microphone intensity evaluation 1. Lines L540, L541, L542, L543, and L544 are plots of measurement results when the numbers of vibration-damping materials 361-364 are 0, 1, 2, 3, and 4, respectively.

[0167] 55 is a graph showing the evaluation results of the ratio of active intensity I at a sound pressure ratio of 9 dB / 3 dB according to two-microphone intensity evaluation 1. Lines L550, L551, L552, L553, and L554 are plots of the measurement results when the numbers of vibration-damping materials 361-364 are 0, 1, 2, 3, and 4, respectively.

[0168] Since this is a distortion characteristic, it naturally does not change linearly. However, since changes occur in the measurement conditions in the frequency band from 3KHz to 3.4KHz, it can be said that it is possible to diagnose changes in distortion characteristics by monitoring changes in the intensity ratio caused by volume changes.

[0169] (Diagnostic processing based on a different analysis method) Next, we will explain the diagnostic processing executed by the diagnostic processing unit 30 based on another analysis method different from the four types of analysis methods described above. In the diagnostic processing based on this other analysis method, the structural condition analysis unit 32 calculates the sound pressure, intensity, and sound absorption coefficient of the sound waves arriving from the direction of the diagnostic object, and the structural condition diagnosis unit 33 evaluates the changes in these acoustic characteristics and judges the deterioration of the structure.

[0170] First, an outline of another analysis method will be described. Using two omnidirectional microphones 21, 22, sound waves arriving from the rear (incident side) and front (reflecting side) of each microphone 21, 22 are separated, and in particular, sound waves arriving from the front (direction of the object to be diagnosed) are analyzed. Furthermore, the intensity of the separated front and rear are calculated, and an approximate sound absorption coefficient is calculated and used for deterioration evaluation. The separation method achieves separation by shifting two impulse responses and subtracting them from each other. With microphones installed close to each other, there is no need to use correlation processing, and by shifting the impulse response forward or backward based on the propagation time of the microphone distance, separation is possible, although frequency weighting is applied. The frequency weighting is corrected later.

[0171] Next, the positional relationship between the speaker 11, the first and second microphones 21 and 22, and the diagnosis object 90 will be described with reference to Fig. 56. Fig. 56 is a diagram showing the positional relationship between the speaker 11, the first and second microphones 21 and 22, and the diagnosis object 90.

[0172] The first and second microphones 21 and 22 are both omnidirectional microphones. The first microphone 21 and the second microphone 22 are located on the speaker axis 13 of the speaker 11 with an inter-microphone distance d between them. The speaker axis 13 is perpendicular to the plane of the diagnosis object 90. The positive direction of the measurement axis m12 passing through the first microphone 21 and the second microphone 22 is the direction toward the diagnosis object 90.

[0173] Next, a diagnostic process based on another analysis method different from the analysis methods shown in Figures 8 to 11 will be described with reference to Figure 57. Figure 57 is a flowchart showing the procedure of the diagnostic process based on the other analysis method.

[0174] In step S61, the impulse response calculation unit 31 receives the received sound signals from each of the first microphone 21 and the second microphone 22, and calculates the impulse responses of each of the first microphone 21 and the second microphone 22. Here, it is assumed that the speaker 11 is acoustically excited by continuous input of a TSP signal such as a Logss signal.

[0175] In step S62, the structural condition analysis unit 32 extracts waveforms of the linear characteristic section and each distortion characteristic section from the impulse response. Subsequent processing, except for the final structural condition diagnosis, is performed by the structural condition analysis unit 32. In this analysis method, in addition to the transfer characteristic and intensity, the sound absorption coefficient is calculated. Here, since a LOGSS signal is used as the acoustic excitation signal, the impulse response extraction process in step S62 is performed. However, if a TSP signal other than a LOGSS signal is used as the acoustic excitation signal, the impulse response extraction process in step S62 is omitted. Furthermore, the sound absorption coefficient is evaluated only for the linear characteristic section, which is physically meaningful. As in the past, when a LOGSS signal is used, the transfer characteristic and intensity can be evaluated for each distortion characteristic section in addition to the linear characteristic section.

[0176] In step S63, the shift time and tap corresponding to the microphone distance d between the first microphone 21 and the second microphone 22 are calculated according to the following equation (13). In equation (13), c is the speed of sound, f s is the sampling frequency.

[0177]

number

[0178] In step S64, the following process is performed on the impulse response G1(t) of the first microphone 21 and the impulse response G2(t) of the second microphone 22. The response G is the response G delayed by tap from the impulse response G1(t). 1D Generate (t). Response G obtained by advancing the impulse response G1(t) by tap 1S Generate (t). The response G obtained by delaying the impulse response G2(t) by tap 2D Generate (t). Response G obtained by advancing the impulse response G2(t) by tap 2S Generate (t).

[0179] In step S65, the impulse response shift difference G 1P (t), G 1Q (t) is calculated by the following process: Here, the subscript P represents the direction from the first microphone 21 to the second microphone 22, and the subscript Q represents the direction from the second microphone 22 to the first microphone 21. Impulse response G1(t) to G 2D Divide (t) and G 1P Calculate (t). Impulse response G1(t) to G 2S Divide (t) and G 1Q Calculate (t).

[0180] In step S66, the impulse response shift difference G 2Q (t), G 2P (t) is calculated by the following process. Impulse response G2(t) to G 1D Divide (t) and G 2Q Calculate (t). Impulse response G2(t) to G 1S Divide (t) and G 2P Calculate (t).

[0181] In step S67, impulse response correction (frequency domain) is performed according to the following equation (10).

[0182]

number

[0183] Here, "→" means that the transfer characteristic on the left (before the arrow) becomes the new transfer characteristic on the right (after the arrow). The process of step S67 is a process for obtaining accurate intensity values ​​and sound absorption coefficient values. However, the main purpose of this embodiment is not to obtain accurate intensity values ​​and sound absorption coefficient values, but to evaluate the difference from the reference state. For this reason, the process of step S67 may be omitted.

[0184] Next, in step S68, the following process is carried out. G 1P (ω) and G 2P (ω) Active Intensity I P (ω), reactive intensity Q P Calculate (ω). G 1Q (ω) and G 2Q (ω) Active Intensity I Q (ω), reactive intensity Q Q Calculate (ω).

[0185] In step S69, active intensity I P (ω), Active Intensity I Q From (ω), the sound absorption coefficient α(ω) is α(ω)=1-|I Q (ω) / I P It is calculated using |(ω)|.

[0186] This completes the analysis process by the structural state analysis unit 32.

[0187] Finally, in step S70, the structural condition diagnosis unit 33 evaluates the change in acoustic characteristics and judges the deterioration of the structure. P (ω), reactive intensity Q P (ω), Active Intensity I Q (ω), reactive intensity Q Q The changes in α(ω) and α(ω) are evaluated to determine the deterioration of the structure.

[0188] The evaluation results obtained by applying this analysis method under the conditions of the embodiment described above are shown below. First, the evaluation results of the transmission characteristics of the sound waves arriving from the diagnosis target 90 obtained by using the first microphone 21 are shown in Figs. 58, 59, 60, and 61.

[0189] 58 is a graph showing the evaluation results of the transfer characteristics in a frequency band of 1 KHz or less. Lines L580, L581, L582, L583, and L584 are plots of the measurement results when the numbers of vibration-damping materials 361-364 are 0, 1, 2, 3, and 4, respectively.

[0190] 59 is a graph showing the evaluation results of the differential transfer characteristics in the frequency band of 1 KHz or less. Lines L590, L591, L592, and L593 are plots of the differences between the measurement results when the number of vibration-damping materials 361 to 364 is 0, 1, 2, and 3, respectively, and the measurement results when the number is 4 as a reference.

[0191] 60 is a graph showing the evaluation results of the transfer characteristics in a frequency band of 1 KHz or more. Lines L600, L601, L602, L603, and L604 are plots of the measurement results when the numbers of vibration-damping materials 361-364 are 0, 1, 2, 3, and 4, respectively.

[0192] 61 is a graph showing the evaluation results of the differential transfer characteristics in a frequency band of 1 KHz or more. Lines L610, L611, L612, and L613 are plots of the differences between the measurement results when the number of vibration-damping materials 361 to 364 is 0, 1, 2, and 3, respectively, and the measurement results when the number of vibration-damping materials 361 to 364 is 4, as a reference.

[0193] From the evaluation results of the differential transfer characteristics in Figures 59 and 61, it can be seen that the effect of peeling of the damping material can be accurately captured in the frequency bands of 400-450Hz, 650Hz-750Hz, 1300-1500Hz, 2000-2200Hz, and 3400-3600Hz. In particular, it is possible to capture the changes around 1500Hz that were not detected by the analysis method described above.

[0194] The evaluation of the characteristics of the sound waves coming from the diagnostic object 90 obtained using the second microphone 22 will be similar to the evaluation of the characteristics of the sound waves coming from the diagnostic object 90 obtained using the first microphone 21.

[0195] Next, the characteristics of the intensity coming from the diagnostic object 90 are shown in FIGS. 62, 63, 64, and 65. FIG.

[0196] Figure 62 shows the active intensity I in the frequency band below 1KHz. Q 6 is a graph showing the evaluation results of 1. Lines L620, L621, L622, L623, and L624 are plots of the measurement results when the numbers of vibration damping materials 361 to 364 are 0, 1, 2, 3, and 4, respectively.

[0197] Figure 63 shows the active intensity I in the frequency band below 1KHz. Q 6 is a graph showing the evaluation results of the difference between the measurement results when the number of vibration-damping materials 361 to 364 is 0, 1, 2, and 3, respectively, and the measurement results when the number of vibration-damping materials 361 to 364 is 4 as a reference.

[0198] Figure 64 shows the active intensity I in the frequency band above 1KHz. Q 6 is a graph showing the evaluation results of the above. Lines L640, L641, L642, L643, and L644 are plots of the measurement results when the numbers of vibration damping materials 361 to 364 are 0, 1, 2, 3, and 4, respectively.

[0199] Figure 65 shows the active intensity I in the frequency band above 1KHz. Q 6 is a graph showing the evaluation results of the difference between the measurement results when the number of vibration-damping materials 361 to 364 is 0, 1, 2, and 3, respectively, and the measurement results when the number of vibration-damping materials 361 to 364 is 4 as a reference.

[0200] Active Intensity I in Figures 63 and 65 QFrom the evaluation results of the difference, similar to the evaluation results of the difference between active intensity I in Figures 45 and 48, it can be seen that the effect of peeling of the vibration damping material can be accurately captured in the frequency bands of 400 to 450 Hz, 650 to 700 Hz, 2000 to 2200 Hz, and 3400 to 3600 Hz.

[0201] Finally, the characteristic evaluation of sound absorption coefficient, which is a feature of this analysis method, is shown in Figures 66, 67, 68, and 69.

[0202] 66 is a graph showing the evaluation results of the sound absorption coefficient α in the frequency band of 1 KHz or less. Lines L660, L661, L662, L663, and L664 are plots of the measurement results when the number of vibration-damping materials 361 to 364 is 0, 1, 2, 3, and 4, respectively.

[0203] Fig. 67 is a graph showing the evaluation results of the difference in sound absorption coefficient α in the frequency band of 1 KHz or less. Lines L670, L671, L672, and L673 are plots of the differences between the measurement results when the number of vibration-damping materials 361 to 364 is 0, 1, 2, and 3, respectively, and the measurement results when there are 4 reference materials.

[0204] 68 is a graph showing the evaluation results of the sound absorption coefficient α in the frequency band of 1 KHz or more. Lines L680, L681, L682, L683, and L684 are plots of the measurement results when the number of vibration-damping materials 361 to 364 is 0, 1, 2, 3, and 4, respectively.

[0205] Fig. 69 is a graph showing the evaluation results of the difference in sound absorption coefficient α in the frequency band of 1 KHz or more. Lines L690, L691, L692, and L693 are plots of the differences between the measurement results when the number of vibration-damping materials 361-364 is 0, 1, 2, and 3, respectively, and the measurement results when there are 4 reference materials.

[0206] In the graphs of Figures 67 and 69, the effects of exfoliation of the damping material appear in the frequency bands of 400-450Hz, 650-700Hz, 2000-2200Hz, and 3400-3600Hz. In other words, it can be confirmed that exfoliation of the damping material can be appropriately evaluated from the evaluation of the sound absorption coefficient α. The sound absorption coefficient α is an acoustic characteristic with a value of 0 to 1, and is characterized by the fact that it is easier to create a baseline of deterioration in the structural condition diagnosis unit compared to other acoustic characteristic indicators such as intensity and sound pressure.

[0207] It is also effective for monitoring purposes to measure the distance between the microphones 21 and 22 and the diagnosis target 90 in several cases.

[0208] According to these embodiments or examples, it is possible to provide an acoustic diagnostic device that performs a non-contact diagnosis by acoustically exciting an object to be diagnosed. In the embodiments and examples, a diagnosis object having a flat surface has been described as an example, but the acoustic diagnostic device according to the embodiments and examples can also be applied to a diagnosis object having a curved shape such as a cylinder.

[0209] Although some embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and spirit of the invention, and are included in the scope of the invention and its equivalents described in the claims. [Explanation of symbols]

[0210] 1...acoustic diagnosis device, 10...acoustic excitation unit, 11...speaker, 11a...speaker center, 12...front, 13...speaker axis, 15...single speaker, 16...acoustic tube, 18...movement mechanism, 20...sound receiving unit, 20A...sound receiving unit, 20B...sound receiving unit, 21, 22...microphone, 25...single microphone, 30...diagnosis processing unit, 31...impulse response calculation unit, 32...structural condition analysis unit, 33...structural condition diagnosis unit, 34...acoustic Vibration signal generating unit, 42...CPU, 43...control device, 44...arithmetic unit, 45...storage device, 46...ROM, 47...main storage device, 48...auxiliary storage device, 50...display, 90...diagnosis target, 91...flat surface, 351...steel can, 351a...bottom plate, 352...plastic cap, 353...stand, 354...base, 355...base, 361-364...vibration damping material, P31...flat surface, T31...orbit, m12...measurement axis.

Claims

1. an acoustic excitation unit that acoustically excites an object to be diagnosed; an acoustic excitation signal generating unit that generates an acoustic excitation signal and continuously inputs the acoustic excitation signal to the acoustic excitation unit; a sound receiving unit that receives an evaluation target sound including a sound wave reflected from the diagnosis object and a vibration radiation sound from the diagnosis object and outputs a received sound signal; an impulse response calculation unit that calculates an impulse response based on the received sound signal; a structural condition analysis unit that calculates acoustic characteristics using the impulse response and captures changes in the received sound signal to analyze a condition of the diagnosis object; a structural condition diagnosis unit that diagnoses a condition of the diagnosis object based on an analysis result of the structural condition analysis unit; The acoustic excitation signal generation unit continuously inputs a Logss signal capable of separating nonlinear characteristics to the acoustic excitation unit, The structural state analysis unit is In a first step, a waveform of a linear characteristic section and each distortion characteristic section are extracted from the impulse response calculated by the impulse response calculation unit; In the second step, single microphone frequency characteristic evaluation 1, single microphone frequency characteristic evaluation 2, two microphone intensity evaluation 1, and two microphone intensity evaluation 2 are performed. Acoustic diagnostic equipment.

2. The acoustic excitation unit has any one of a single speaker, a directional single sound source in which a single speaker is attached with an acoustic tube to enhance directivity, a speaker group in which a plurality of speakers are arranged on a circumference and driven in phase, a speaker group in which a plurality of speakers are arranged on a grid and output a plane wave in a simulated manner, and a general-purpose flat speaker. The acoustic diagnostic device according to claim 1 .

3. the sound receiving unit has two microphones, each of the two microphones being either an omnidirectional microphone, a directional microphone, a gun microphone, a line array microphone, or a circle array microphone, and both of the two microphones being either an omnidirectional microphone or a directional microphone; The acoustic diagnostic device according to claim 1 .

4. The acoustic excitation unit is installed so that a front surface for emitting sound waves faces the diagnosis object, and the sound receiving unit has two microphones, and the two microphones are installed side by side on a line connecting the acoustic excitation unit and the diagnosis object. The acoustic diagnostic device according to claim 1 .

5. In the single microphone frequency characteristic evaluation 1, the structural state analysis unit As a first step, zeros are inserted at the end of the extracted impulse response of a single microphone so that the signal length is equal to that before extraction, and an FFT is performed on the impulse response after the insertion. In the second step, frequency characteristic smoothing is performed on the gain and phase characteristics. The third step is to display the comparison of the transfer characteristics with the reference condition. The acoustic diagnostic device according to claim 1 .

6. In the single microphone frequency characteristic evaluation 2, the structural state analysis unit In the first step, the difference between the reference measurement cut-out impulse response measured under the reference condition and the cut-out impulse response of a single microphone is calculated. In the second step, zeros are inserted into the extracted differential impulse response so that the signal length is equal to that before the extraction, and an FFT is performed on the differential impulse response after the insertion. In the third step, frequency characteristic smoothing is performed on the gain and phase characteristics. As a fourth step, the differential transfer characteristic is displayed. The acoustic diagnostic device according to claim 1 .

7. In the dual microphone intensity evaluation 1, the structural state analysis unit In the first step, zeros are inserted into the end of each of the extracted impulse responses of the two microphones so that the signal length is equal to that before extraction, and an FFT is performed on the impulse responses after the insertion. In the second step, frequency characteristic smoothing is performed on the gain and phase characteristics, and the smoothed FFT values ​​are used to calculate the active intensity and reactive intensity. The third step is to display the intensity characteristics in comparison with the reference condition. The acoustic diagnostic device according to claim 1 .

8. In the dual microphone intensity evaluation 2, the structural state analysis unit In the first step, the difference between the reference measurement cut-out impulse response measured under the reference condition and each of the cut-out impulse responses of the two microphones is calculated. In the second step, zeros are inserted into the end of each of the extracted differential impulse responses of the two microphones so that the signal length is equal to that before extraction, and an FFT is performed on each of the differential impulse responses of the two microphones after the insertion. In the third step, frequency characteristic smoothing is performed on the gain and phase characteristics, and the smoothed FFT values ​​are used to calculate the active intensity and reactive intensity. The fourth step is to display the active and reactive intensity. The acoustic diagnostic device according to claim 1 .

9. The structural condition analysis unit performs measurements at a number of volume patterns of multiple acoustic excitations as an auxiliary structural condition analysis, and displays the difference characteristic of single microphone frequency characteristic evaluation 1 or the ratio characteristic of two microphone intensity evaluation 1 at each volume, with acoustic excitation volume +0 dB as the reference state. In the evaluation of the linear characteristic section, a linear change is confirmed, and if there is a deviation, it is determined that there is a problem with the measurement environment. In the nonlinear characteristic section (distortion characteristic), since there is no linear change, the change characteristic change in each state is monitored to assist in the diagnosis of deterioration. The acoustic diagnostic device according to claim 1 .

10. The acoustic excitation signal generation unit continuously inputs a TSP signal to the acoustic excitation unit, The structural state analysis unit performs single-microphone frequency characteristic evaluation 1, single-microphone frequency characteristic evaluation 2, two-microphone intensity evaluation 1, and two-microphone intensity evaluation 2 on the impulse response calculated by the impulse response calculation unit. The acoustic diagnostic device according to claim 1 .

11. the structural condition diagnosis unit compares the measurement analysis data obtained by the structural condition analysis unit with a baseline of an allowable range that is determined in advance by measuring when a failure mode occurs, and determines that an abnormality has occurred when the measurement analysis data exceeds the baseline. The acoustic diagnostic device according to claim 1 .

12. The structural condition diagnosis unit grasps whether the measurement analysis data obtained by the structural condition analysis unit is on an increasing or decreasing trend through time-series change monitoring, and diagnoses the progress of deterioration due to aging. The acoustic diagnostic device according to claim 1 .

13. The structural condition diagnosis unit diagnoses that a vibration-damping material attached to the diagnosis object has peeled off when an intensity with a positive direction toward the diagnosis object increases. The acoustic diagnostic device according to claim 1 .

14. A computer having a processor and a memory device, 2. A method for executing the functions of the acoustic excitation signal generating unit, the impulse response calculating unit, the structural condition analyzing unit, and the structural condition diagnosing unit according to claim 1 , Acoustic diagnostic program.

15. an acoustic excitation unit that acoustically excites an object to be diagnosed; an acoustic excitation signal generating unit that generates an acoustic excitation signal and continuously inputs the acoustic excitation signal to the acoustic excitation unit; a sound receiving unit that receives an evaluation target sound including a sound wave reflected from the diagnosis object and a vibration radiation sound from the diagnosis object and outputs a received sound signal; an impulse response calculation unit that calculates an impulse response based on the received sound signal; a structural condition analysis unit that calculates acoustic characteristics using the impulse response and captures changes in the received sound signal to analyze a condition of the diagnosis object; a structural condition diagnosis unit that diagnoses a condition of the diagnosis object based on an analysis result of the structural condition analysis unit; The acoustic excitation signal generation unit continuously inputs a Logss signal capable of separating nonlinear characteristics to the acoustic excitation unit, The structural state analysis unit is In a first step, a waveform of a linear characteristic section and each distortion characteristic section are extracted from the impulse response calculated by the impulse response calculation unit; In the second step, using each extracted waveform, single microphone frequency characteristic evaluation 1, single microphone frequency characteristic evaluation 2, two microphone intensity evaluation 1, and two microphone intensity evaluation 2 are performed. Acoustic diagnostic equipment.

16. an acoustic excitation unit that acoustically excites an object to be diagnosed; an acoustic excitation signal generating unit that generates an acoustic excitation signal and continuously inputs the acoustic excitation signal to the acoustic excitation unit; a sound receiving unit that receives an evaluation target sound including a sound wave reflected from the diagnosis object and a vibration radiation sound from the diagnosis object and outputs a received sound signal; an impulse response calculation unit that calculates an impulse response based on the received sound signal; a structural condition analysis unit that calculates acoustic characteristics using the impulse response and captures changes in the received sound signal to analyze a condition of the diagnosis object; a structural condition diagnosis unit that diagnoses a condition of the diagnosis object based on an analysis result of the structural condition analysis unit; the sound receiving unit has a first microphone positioned between the acoustic excitation unit and the diagnosis object, and a second microphone positioned between the first microphone and the diagnosis object, The acoustic excitation signal is a Logss signal capable of separating nonlinear characteristics, The structural state analysis unit is In a first step, a waveform of a linear characteristic section and each distortion characteristic section are extracted from the impulse response calculated by the impulse response calculation unit; As a second step, a shift time and a tap corresponding to a microphone distance between the first and second microphones are calculated; As a third step, for the impulse response G 1 (t) of the first microphone and the impulse response G 2 (t) of the second microphone, A response G 1D (t) is generated by delaying the impulse response G 1 (t) by tap. A response G 1S (t) is generated by advancing the impulse response G 1 (t) by tap. A response G 2D (t) is generated by delaying the impulse response G 2 (t) by tap; A response G 2S (t) is generated by advancing the impulse response G 2 (t) by taps, In a fourth step, impulse response shift differences G 1P (t), G 1Q (t), G 2Q (t), and G 2P (t) are calculated by the following process: G 2D (t) is divided by the impulse response G 1 (t) to calculate G 1P (t); G 2S (t) is divided by the impulse response G 1 (t) to calculate G 1Q (t); G 1D (t) is divided by the impulse response G 2 (t) to calculate G 2Q (t); G 1S (t) is divided by the impulse response G 2 (t) to calculate G 2P (t); The fifth step is: Active intensity I P (ω) and reactive intensity Q P (ω) are calculated from G 1P (ω) and G 2P (ω), Active intensity I Q (ω) and reactive intensity Q Q (ω) are calculated from G 1Q (ω) and G 2Q (ω), In a sixth step, the sound absorption coefficient α(ω) is calculated from the active intensity I P (ω) and the active intensity I Q (ω) by α(ω)=1-|I Q (ω) / I P (ω)|. Acoustic diagnostic equipment.

17. Following the fourth step and before the fifth step, an impulse response correction (frequency domain) is performed according to the following equation (1): [0010] In formula (1), "→" means that the transfer characteristic on the left (before the arrow) becomes the transfer characteristic on the right (after the arrow). The acoustic diagnostic device according to claim 16.

18. the structural condition diagnosis unit compares the measurement analysis data obtained by the structural condition analysis unit with a baseline of an allowable range that is determined in advance by measuring when a failure mode occurs, and determines that an abnormality has occurred when the measurement analysis data exceeds the baseline. The acoustic diagnostic device according to claim 16.

19. The structural condition diagnosis unit grasps whether the measurement analysis data obtained by the structural condition analysis unit is on an increasing or decreasing trend through time-series change monitoring, and diagnoses the progress of deterioration due to aging. The acoustic diagnostic device according to claim 16.

20. continuously inputting an acoustic excitation signal to an acoustic excitation unit to acoustically vibrate an object to be diagnosed; calculating an impulse response based on a received signal output from a sound receiving unit that receives an evaluation target sound including a sound wave reflected from the diagnosis object and a vibration radiated sound from the diagnosis object; calculating an acoustic characteristic using the impulse response, capturing a change in the received sound signal, and analyzing a state of the diagnosis object; Diagnosing the state of the diagnostic object based on the analysis result; The acoustic excitation of the diagnosis target object includes continuously inputting a Logss signal capable of separating nonlinear characteristics to the acoustic excitation unit; Analyzing the condition of the diagnostic subject includes: In the first step, the waveforms of the linear characteristic section and each distortion characteristic section are extracted from the impulse response. In the second step, single microphone frequency characteristic evaluation 1, single microphone frequency characteristic evaluation 2, two microphone intensity evaluation 1, and two microphone intensity evaluation 2 are performed. Acoustic diagnostic methods.

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