Spacecraft aluminum alloy metal matrix structure damage real-time positioning method

Abstract

The application provides a spacecraft aluminum alloy metal-based structure damage real-time positioning method, which comprises the following steps: a sensor array deployed on a detected piece collects original signals of acoustic emission through multiple channels; frequency components of the original signals of the multiple channels are analyzed to determine a frequency component extraction interval; the original signals of acoustic emission are subjected to band-pass filtering and continuous wavelet transformation, and a time corresponding to a first peak value of a signal amplitude after the wavelet transformation is taken as a signal arrival time; a signal actual propagation distance of a simulated acoustic emission source at one end of the sensor array is obtained, and is subjected to linear fitting with the signal arrival time to obtain a signal propagation velocity; and finally, an acoustic emission source positioning equation is established, and a least square method is used to solve the acoustic emission source positioning equation to obtain an acoustic emission source positioning result. Therefore, the application can improve the accuracy of online positioning of a structure damage of a spacecraft.

Description

Technical Field

[0001] This invention relates to the field of spacecraft structure monitoring technology, and in particular to a method for real-time location of damage to aluminum alloy metal-based structures in spacecraft. Background Technology

[0002] In the aerospace field, accidents caused by structural failures occur frequently during spacecraft operation. Microscopic defects resulting from impacts and stress concentrations can also pose safety hazards to spacecraft during on-orbit service. Under extreme environments such as high temperature, high pressure, and heavy loads, structural microscopic defects need to be detected and repaired in a timely manner; otherwise, as service time increases, these microscopic defects will continue to expand, causing structural failure and leading to safety accidents. Therefore, monitoring and locating structural microscopic defects is crucial to ensuring the safe and stable operation of spacecraft throughout their normal service life.

[0003] Because structural damage generates elastic wave signals, which can be considered acoustic signals, acoustic emission (AE) technology is a passive non-destructive testing technique that monitors signals without human intervention. Compared to active non-destructive testing techniques such as visual inspection and ultrasonic testing, AE technology utilizes the elastic wave signals generated by the material structure itself during damage detection, thus offering significant advantages for long-term online monitoring.

[0004] The existing patent CN111474244B discloses an "Adaptive Threshold Cross-Correlation Positioning Method for Rigid Flat Plates in Spacecraft," which achieves the positioning of acoustic emission sources. It divides the surface of the test specimen into a grid, uses time difference information to calculate the collision probability of each grid node using a cross-correlation function, and takes the coordinates of the grid node with the highest collision probability as the positioning result. In this method, time difference information is extracted by setting a voltage threshold and extracting a fixed number of signals, calculating the time offset caused by the extraction. The accuracy of the signal arrival time information calculation is limited by the sampling rate and the voltage threshold, and background noise can affect the setting of the voltage threshold.

[0005] Existing patent CN116448882A discloses a "method and device for locating acoustic emission sources of projectile structures." This method divides the test area of ​​the specimen into a grid, uses an exhaustive search method to traverse and search the grid nodes, calculates the positioning error of each node based on the signal arrival time difference and the longitudinal wave velocity, and takes the coordinates of the node with the smallest positioning error as the positioning result. This method obtains the acoustic emission arrival time difference based on the trigger time of the acoustic emission signal and defines a target function for the relative error based on distance, assuming the signal propagation speed is the transverse wave propagation speed of the material. However, since acoustic emission signals are complex elastic waves containing transverse waves, longitudinal waves, Lyme waves, Rayleigh waves, etc., and the refraction and reflection caused by boundary effects make the components of the acoustic emission signal even more difficult to distinguish, the method of calculating the positioning error using the signal trigger time difference and the longitudinal wave velocity is unreliable.

[0006] Existing technology describes a "wavelet analysis-based acoustic emission source localization technique." This method, based on acoustic emission signal analysis, proposes a wavelet transform-based localization approach. Starting with the signal received by the sensor, it separates the time-varying pattern of a flexible wave signal at a specific frequency, and uses the time corresponding to the point of maximum amplitude of the separated signal as the arrival time of the flexible wave group velocity at that frequency. Then, based on this arrival time and the actually measured group velocity, a triangulation method is used to locate the acoustic emission source. However, this technique does not mention a method for selecting a specific frequency. Therefore, during application, the boundary reflected wave may superimpose with the original signal, resulting in a phenomenon where the subsequent superimposed waveform exceeds the maximum amplitude of the original signal.

[0007] In summary, the existing methods have many problems in practical use, so it is necessary to improve them. Summary of the Invention

[0008] To address the aforementioned deficiencies, the present invention aims to provide a method and apparatus for real-time location of damage to aluminum alloy metal-based structures of spacecraft, which can be used for online monitoring and location of acoustic emission sources after the metal structure of a spacecraft cabin has been damaged by impacts, collisions, crack propagation, etc.

[0009] To achieve the above objectives, this invention provides a method for real-time damage localization of aluminum alloy metal-based structures in spacecraft, comprising the following steps:

[0010] The raw acoustic emission signal of the device under test is acquired through a multi-channel sensor array deployed on the device under test; wherein the sensor array is composed of several sensing units linearly and equally spaced.

[0011] Spectral analysis is performed on the original signals from multiple channels to obtain the frequency domain variance curve;

[0012] A reference threshold is determined based on the variance peak value in the frequency domain variance curve, and a frequency range not exceeding the reference threshold is searched at preset frequency intervals as the bandpass filtering range of the original signal to obtain the corresponding filtered signal.

[0013] A continuous wavelet transform is performed on the filtered signal to obtain a time spectrum diagram. The median frequency of the bandpass filter frequency range is used as the target frequency, and the corresponding wavelet transform amplitude curve is plotted. The time corresponding to the peak value of the first wave packet in the wavelet transform amplitude curve is taken as the signal arrival time.

[0014] The actual propagation distance of the signal simulating an acoustic emission source at one end of the sensor array is obtained, the actual propagation distance is linearly fitted with the signal arrival time, and the signal propagation speed is obtained based on the fitting result.

[0015] An acoustic emission source localization matrix equation is established, and the equation is solved using the least squares method to obtain the signal source position coordinate expression.

[0016] Substitute the signal arrival time and the signal propagation speed into the expression for the signal source location coordinates to obtain the acoustic emission source localization result.

[0017] Furthermore, the step of performing spectral analysis on the original signal from multiple channels to obtain the frequency domain variance curve includes:

[0018] The spectrum of the original signal is obtained by Fourier transform analysis. The normalized amplitude of a single channel in the spectrum is used as a sample to calculate the variance of the spectral amplitude at each frequency, thus obtaining the frequency domain variance curve.

[0019] Furthermore, the step of determining a reference threshold based on the variance peak value in the frequency domain variance curve, and searching for frequency ranges not exceeding the reference threshold at preset frequency intervals as the bandpass filtering range of the original signal to obtain the corresponding filtered signal includes:

[0020] One-tenth of the peak value of the variance curve in the frequency domain is determined as the reference threshold, and the frequency range not exceeding the reference threshold is searched at 5kHz intervals as the bandpass filtering range of the original signal.

[0021] The filtered signal corresponding to the original signal is obtained based on the bandpass filtering range.

[0022] Furthermore, the step of searching for a frequency range not exceeding the reference threshold at preset frequency intervals as the bandpass filtering range of the original signal further includes:

[0023] Search for frequency ranges that do not exceed the reference threshold at preset frequency intervals;

[0024] The first frequency range found in the search is determined as the bandpass filtering range of the original signal.

[0025] Furthermore, the step of obtaining the actual propagation distance of the signal from the simulated acoustic emission source at one end of the sensor array, linearly fitting the actual propagation distance with the signal arrival time, and obtaining the signal propagation speed based on the fitting result includes:

[0026] At one end of the sensor array, a broken lead is used to simulate an acoustic emission source to obtain the corresponding actual signal propagation distance;

[0027] The actual propagation distance is linearly fitted to the signal arrival time, and the slope of the fitted line in the fitting result is taken as the signal propagation speed.

[0028] Furthermore, the step of establishing the acoustic emission source localization matrix equation and solving the acoustic emission source localization matrix equation using the least squares method to obtain the signal source position coordinate expression includes:

[0029] Establish the acoustic emission source localization equation, and use the original signal of one of the channels as a reference to establish the acoustic emission source localization matrix equation;

[0030] The acoustic emission source localization matrix equation is solved using the least squares method to obtain the signal source position coordinate expression.

[0031] Furthermore, N sensing units are provided, each located within the positioning region (x... i y i At (i = 1…N), respectively at the signal arrival time t i If the original signal generated at time t0 is received at time t0, the signal source is (x0, y0), and the signal propagation speed is c, then the acoustic emission source localization equation is:

[0032]

[0033] Furthermore, the step of establishing the acoustic emission source localization matrix equation using the original signal from one of the channels as a reference includes:

[0034] The acoustic emission source localization equation is squared, and the original signal of one of the channels is used as a reference to eliminate the quadratic terms of the acoustic emission source position parameters in the acoustic emission source localization equation, so as to form an acoustic emission source localization matrix equation in matrix form.

[0035] Furthermore, the step of solving the acoustic emission source localization matrix equation using the least squares method to obtain the signal source position coordinate expression includes:

[0036] The error function of the acoustic emission source localization matrix equation is set according to the least squares method;

[0037] The corresponding signal source position coordinate expression is calculated based on the error function.

[0038] Furthermore, several of the sensor units are linearly and equally spaced on the surface of the workpiece under test, and the sensor unit is a piezoelectric ceramic sheet.

[0039] The real-time damage localization method for spacecraft aluminum alloy metal-based structures described in this invention involves acquiring raw acoustic emission signals through a multi-channel sensor array deployed on the tested component; analyzing the frequency components of the multi-channel raw signals to determine the frequency component extraction intervals; performing bandpass filtering and continuous wavelet transform on the raw acoustic emission signals; and using the moment corresponding to the first peak value of the wavelet-transformed signal amplitude as the signal arrival time; obtaining the actual propagation distance of the signal simulating an acoustic emission source at one end of the sensor array and linearly fitting it with the signal arrival time to obtain the signal propagation speed; finally, solving the established acoustic emission source localization equation using the least squares method to obtain the acoustic emission source localization result. Thus, this invention can accurately locate structural damage in spacecraft online. Attached Figure Description

[0040] Figure 1 This is a flowchart illustrating the steps of the real-time damage localization method for the aluminum alloy metal matrix structure of a spacecraft according to an embodiment of the present invention.

[0041] Figure 2 This is a schematic diagram of the signal acquisition and analysis system used in the real-time damage localization method for the aluminum alloy metal matrix structure of a spacecraft according to an embodiment of the present invention.

[0042] Figure 3 A time-domain curve of the acoustic emission signal of the real-time damage localization method for the aluminum alloy metal matrix structure of a spacecraft provided in an embodiment of the present invention;

[0043] Figure 4 The frequency diagram of the acoustic emission signal of the real-time damage localization method for the aluminum alloy metal matrix structure of a spacecraft provided in an embodiment of the present invention;

[0044] Figure 5 This is a frequency domain normalized amplitude variance curve of the real-time damage localization method for the aluminum alloy metal matrix structure of a spacecraft provided in an embodiment of the present invention.

[0045] Figure 6 This is a signal bandpass filter curve of the real-time damage localization method for the aluminum alloy metal matrix structure of a spacecraft provided in an embodiment of the present invention;

[0046] Figure 7 The time-frequency domain amplitude characteristic diagram of the real-time damage localization method for the aluminum alloy metal matrix structure of a spacecraft provided in an embodiment of the present invention;

[0047] Figure 8 The target frequency wavelet transform curve of the real-time damage localization method for the aluminum alloy metal matrix structure of a spacecraft provided in an embodiment of the present invention is shown.

[0048] Figure 9This is a schematic diagram of the lead-broken simulated acoustic emission source of the real-time damage localization method for the aluminum alloy metal matrix structure of a spacecraft provided in an embodiment of the present invention;

[0049] Figure 10 This is a schematic diagram illustrating the linear fitting between the actual propagation distance and the signal arrival time in the real-time damage localization method for the aluminum alloy metal matrix structure of a spacecraft provided in an embodiment of the present invention. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0051] It should be noted that references to "an embodiment," "embodiment," "example embodiment," etc., in this specification refer to the described embodiment including specific features, structures, or characteristics, but not every embodiment must include these specific features, structures, or characteristics. Furthermore, such expressions do not refer to the same embodiment. Moreover, when describing specific features, structures, or characteristics in conjunction with embodiments, whether or not explicitly described, it is indicated that incorporating such features, structures, or characteristics into other embodiments is within the knowledge of those skilled in the art.

[0052] Furthermore, certain terms are used in the specification and subsequent claims to refer to specific components or parts. Those skilled in the art will understand that manufacturers may use different names or terms to refer to the same component or part. This specification and subsequent claims do not distinguish components or parts by differences in name, but rather by differences in function. The terms "comprising" and "including" used throughout the specification and subsequent claims are open-ended and should be interpreted as "including but not limited to." Additionally, the term "connection" here includes any direct and indirect electrical connection means. Indirect electrical connection means include connections made through other means.

[0053] Figure 1 This invention illustrates a real-time damage location method for spacecraft aluminum alloy metal-based structures according to an embodiment of the present invention. The method is applied to the online monitoring and location of acoustic emission sources after the aluminum alloy structure of a spacecraft cabin has suffered damage such as impact, collision, or crack propagation. The method preferably employs methods such as... Figure 2The signal acquisition and analysis system shown comprises several sensing units 1, signal amplifiers 2 connected to the sensing units 1, signal acquisition boards 3 connected to the signal amplifiers 2, and a host computer 4 connected to the output of the signal acquisition boards 3. The host computer 4 analyzes the received acquired signals to locate the damage position on the tested component. The method includes the following steps:

[0054] S101: The raw acoustic emission signal of the tested component is acquired through a multi-channel sensor array deployed on the tested component; wherein, the sensor array is composed of several sensing units 1 linearly and equally spaced. Specifically, when the tested component is subjected to internal or external forces and produces acoustic emission, the raw signal is sensed by the sensing units 1 attached to the surface of the tested component. The weak raw signal is amplified by the signal amplifier 2 with a specified gain. The signal acquisition board 3 synchronously acquires the multi-channel amplified raw signals and transmits the data to the host computer 4 for analysis and processing.

[0055] The time-domain curve of the original signal acquired in this embodiment is as follows: Figure 3 As shown, its signal frequency is as follows Figure 4 As shown. Furthermore, several of the sensor units 1 are linearly and equally spaced on the surface of the workpiece under test, and the sensor unit is a piezoelectric ceramic sheet; of course, in other embodiments, other sensors suitable for acoustic emission signal acquisition may also be used.

[0056] In an optional implementation, the workpiece under normal temperature conditions is a 6061 aluminum alloy plate with dimensions of 300mm × 300mm × 1.5mm. A grid is drawn on the plate in 50mm increments using a marker to facilitate the deployment of sensor unit 1 and the determination of the location of the simulated acoustic emission source. The sensor unit uses a PZT-5H piezoelectric ceramic sheet, which can be fixed to the workpiece using 501 instant adhesive. Specifically, four sensor units are arranged in a linear array, spaced 50mm apart along the length of the aluminum alloy plate. A lead break is then applied at one end of the linear array to serve as the acoustic emission source. The frequency range of the acquired signal is analyzed by a host computer.

[0057] S102: Perform spectral analysis on the original multi-channel signal to obtain the frequency domain variance curve. Optionally, step S102 includes: obtaining the spectrum of the original signal through Fourier transform analysis; using the normalized amplitude of a single channel in the spectrum as a sample, calculating the spectral amplitude variance at each frequency to obtain the frequency domain variance curve, such as... Figure 5As shown; in specific implementation, the acquired raw signal is subjected to Fourier transform to obtain the signal amplitude at different frequencies. The acoustic emission signal spectrum has multiple amplitude peaks, and the frequency ranges of the amplitude peaks do not completely overlap between different channels. The spectral amplitude of each channel is normalized to a uniform range. Using the normalized amplitude of a single channel in the spectrum as a sample, the spectral amplitude variance at each frequency is calculated to obtain the frequency domain variance curve. The smaller the variance, the closer the amplitude intensity proportion of the corresponding frequency in each channel is.

[0058] S103: Determine a reference threshold based on the peak variance in the frequency domain variance curve, and search for frequency ranges not exceeding the reference threshold at preset frequency intervals as the bandpass filtering range of the original signal to obtain the corresponding filtered signal. In an optional embodiment, step S103 specifically includes: determining one-tenth of the peak variance in the frequency domain variance curve as the reference threshold, and searching for frequency ranges not exceeding the reference threshold at 5kHz intervals as the bandpass filtering range of the original signal; obtaining the filtered signal corresponding to the original signal based on the bandpass filtering range.

[0059] The step of searching for frequency intervals not exceeding the reference threshold at preset frequency intervals as the bandpass filtering range of the original signal further includes: searching for frequency intervals not exceeding the reference threshold at preset frequency intervals; and determining the first searched frequency interval as the bandpass filtering range of the original signal. That is, in this embodiment, 1 / 10 of the peak variance value in the frequency domain variance curve is used as the reference threshold, and 5kHz is used as the frequency interval search interval. If the variance within the searched frequency interval is less than the reference interval, it is considered to meet the search condition, and the first frequency interval that meets the search condition is taken as the bandpass filtering range of the original signal.

[0060] Specifically, this example normalizes the signal spectra of the four channels, calculates the variance of the spectral amplitude at each frequency, uses 1 / 10 of the peak variance as a reference threshold, and sets a frequency range search interval of 5 kHz. If the variance within the searched frequency range is less than the reference interval, the search condition is considered met. The first frequency range that meets the search condition is taken as the bandpass filtering range of the original signal; its signal bandpass filtering curve is shown below. Figure 6 As shown.

[0061] S104: Perform continuous wavelet transform on the filtered signal to obtain a time spectrum; and use the median frequency of the bandpass filter frequency range as the target frequency to plot the corresponding wavelet transform amplitude curve, and take the time corresponding to the peak value of the first wave packet in the wavelet transform amplitude curve as the signal arrival time.

[0062] The time-frequency spectrum obtained by the transformation in this embodiment is shown in Figure 7, and the wavelet transform amplitude curve is shown in Figure 8. Figure 8 As shown.

[0063] S105: Obtain the actual propagation distance of the signal from the simulated acoustic emission source at one end of the sensor array, linearly fit the actual propagation distance with the signal arrival time, and obtain the signal propagation speed based on the fitting result. Preferably, four or more sensor units 1 are arranged linearly and equally spaced on the surface of the object being tested. A simulated acoustic emission source is used at one end of the sensor array. The signal arrival time of each channel is obtained through the signal time information extraction method described above. Since the location of the simulated acoustic emission source is known, the actual propagation distance of the signal in each channel can be obtained. The propagation distance data is linearly fitted with the signal arrival time of the corresponding channel, and the signal propagation speed is obtained based on the fitting result.

[0064] Further, step S105 specifically includes: simulating an acoustic emission source at one end of the sensor array by breaking a lead, and obtaining the corresponding actual signal propagation distance; linearly fitting the actual propagation distance with the signal arrival time, the result of which is as follows: Figure 10 As shown, the slope of the fitted straight line in the fitting result is taken as the signal propagation speed.

[0065] Specifically, a lead-breaking operation can be performed at any end of the sensor array to simulate an acoustic emission source; the lead-breaking operation is as follows: Figure 9 As shown.

[0066] When simulating acoustic emission from a broken lead on the surface of the tested component, signals are collected by piezoelectric ceramic plates deployed at four endpoints within a 200mm×200mm rectangular monitoring range. The host computer then analyzes the signal arrival time t corresponding to each channel to determine the signal arrival time t. i (i = 1, 2, 3, 4).

[0067] In step S105 of this embodiment, the signal propagation distance and signal arrival time are linearly fitted to calibrate the target frequency signal propagation speed through a simulated acoustic emission experiment; that is, the actual propagation speed of a specific frequency of the signal is obtained by using the calibration experiment.

[0068] S106: Establish the acoustic emission source positioning matrix equation and solve it using the least squares method to obtain the signal source position coordinate expression. The acoustic emission source positioning matrix equation is the acoustic emission source positioning coordinate equation. That is, in this embodiment, the acoustic emission source positioning coordinate equation is established, and the acoustic emission source position coordinate is solved based on the least squares idea.

[0069] Furthermore, step S106 specifically includes: establishing an acoustic emission source localization equation, and using the original signal of one of the channels as a reference, establishing an acoustic emission source localization matrix equation; solving the acoustic emission source localization matrix equation using the least squares method to obtain the signal source position coordinate expression.

[0070] In one example, there are N sensing units, each located in the positioning region (x... i y i At (i = 1…N), respectively at the signal arrival time t i If the original signal generated at time t0 is received at time t0, the signal source is (x0, y0), and the signal propagation speed is c, then the acoustic emission source localization equation is:

[0071] This formula represents the correspondence between location coordinates and signal arrival time.

[0072] Furthermore, the step of establishing the acoustic emission source localization matrix equation with the original signal of one of the channels as a reference includes: squaring the acoustic emission source localization equation, and using the original signal of one of the channels as a reference, eliminating the quadratic terms of the acoustic emission source position parameters in the acoustic emission source localization equation to form a matrix form of the acoustic emission source localization matrix equation.

[0073] Specifically, squaring the above formula yields the following formula:

[0074]

[0075] Preferably, the first equation in the above equation set is used as a reference (of course, other equations corresponding to other signals can also be used as a reference; this invention does not limit the channel used as a reference). The remaining equations are subtracted from the first equation to eliminate the quadratic terms of the acoustic emission source position parameters, resulting in the following formula:

[0076]

[0077] Furthermore, by rearranging the above formula into matrix form, we obtain the formula for the matrix equation of acoustic emission source localization:

[0078]

[0079] Furthermore, the step of solving the acoustic emission source positioning matrix equation using the least squares method to obtain the signal source position coordinate expression includes: setting an error function for the acoustic emission source positioning matrix equation according to the least squares method; and analyzing and calculating the corresponding signal source position coordinate expression based on the error function.

[0080] Since measured data can cause disturbances to the above formula, this embodiment sets an error function F(X) based on the least squares approach, as follows:

[0081] F(X) = (AX - B) T (AX-B);

[0082] in:

[0083]

[0084] Furthermore, when the error function F(X) reaches its minimum value, the target vector X = [x0, y0, t0]. T The closer the result is to the theoretical calculation, the better, as shown in the following formula:

[0085]

[0086] Therefore, the target vector X = [x0, y0, t0] can be obtained. T The expression is as follows:

[0087] X = 2(AA) T ) -1 2A T B;

[0088] S107: Substitute the signal arrival time and signal propagation speed into the signal source location coordinate expression to obtain the acoustic emission source location result.

[0089] Specifically, substituting the signal arrival time and signal propagation speed of each channel into the formula: X = 2(AA) T ) -1 2A T B, then the acoustic emission source localization result can be obtained. For example, based on the signal arrival times t of the four channels extracted above. i Substituting (i = 1, 2, 3, 4) and the signal propagation speed c based on linear fitting analysis into the formula, the corresponding acoustic emission source location result is obtained.

[0090] This embodiment provides a real-time damage localization method for spacecraft aluminum alloy metal-based structures. It analyzes the frequency components of multi-channel raw signals to determine the frequency component extraction interval, performs bandpass filtering and continuous wavelet transform on the acoustic emission signal, and uses the time corresponding to the first peak value of the wavelet-transformed signal amplitude as the signal arrival time. Then, it obtains the actual propagation speed of the signal at a specific frequency through calibration experiments. Based on the established acoustic emission source localization equation, it solves using the least squares method to obtain the experimental localization result. Compared to existing technologies, this invention analyzes from the perspective of the proportion of original signal frequency components, and provides a clear target frequency determination and an adaptive signal arrival time extraction method based on existing wavelet analysis-based acoustic emission source time difference localization methods. This enables accurate online localization of spacecraft structural damage.

[0091] In summary, the real-time damage localization method for spacecraft aluminum alloy metal-based structures described in this invention involves building a signal acquisition and analysis system, using a host computer to process and analyze the acquired multi-channel acoustic emission signals, using Fourier transform to analyze the frequency domain characteristics of the acquired signals, using the normalized amplitude of a single channel in the spectrum as a sample, calculating the spectral amplitude variance at each frequency to obtain the frequency domain variance curve, using 1 / 10 of the variance peak value as a reference threshold, searching for frequency intervals not exceeding the reference threshold at 5kHz intervals as the original signal bandpass filtering range, then performing continuous wavelet transform on the filtered signal to obtain the time spectrum, using the median frequency of the bandpass filtering frequency range as the target frequency, plotting the wavelet transform amplitude curve corresponding to the target frequency, and using the time corresponding to the peak value of the first wave packet of the curve as the signal arrival time. Multiple piezoelectric sensing units are then linearly and equally spaced on the surface of the object being tested. A broken lead is used to simulate an acoustic emission source at one end of the linear sensing array. The signal arrival time of each channel is obtained using the time information extraction method described in this invention. Given the actual signal propagation distance, the signal propagation distance and signal arrival time data are linearly fitted, and the slope of the fitted line is taken as the signal propagation speed. Finally, an acoustic emission source localization equation is established. Using the signal from one of the channels as a reference, an acoustic emission source localization matrix equation is established. The equation is solved using the least squares approach to obtain the signal source position coordinate expression. Substituting the signal arrival time and signal propagation speed into the signal source position coordinate expression, the acoustic emission source is located. This method can be applied to the online monitoring and localization of acoustic emission sources after damage such as impacts, collisions, and crack propagation to the metal structure of a spacecraft cabin.

[0092] Of course, the present invention may have other various embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art can make various corresponding changes and modifications according to the present invention, but these corresponding changes and modifications should all fall within the protection scope of the appended claims.

Claims

1. A method for real-time damage localization of aluminum alloy metal-based structures in spacecraft, characterized in that, Including the following steps: The raw acoustic emission signal of the device under test is acquired through a multi-channel sensor array deployed on the device under test; wherein the sensor array is composed of several sensing units linearly and equally spaced. Spectral analysis is performed on the original signals from multiple channels to obtain the frequency domain variance curve; A reference threshold is determined based on the variance peak value in the frequency domain variance curve, and a frequency range not exceeding the reference threshold is searched at preset frequency intervals as the bandpass filtering range of the original signal to obtain the corresponding filtered signal. The steps for obtaining the corresponding filtered signal include: One-tenth of the peak value of the variance curve in the frequency domain is determined as the reference threshold, and the frequency range not exceeding the reference threshold is searched at 5kHz intervals as the bandpass filtering range of the original signal. The filtered signal corresponding to the original signal is obtained according to the bandpass filtering range; A continuous wavelet transform is performed on the filtered signal to obtain a time spectrum diagram. The median frequency of the bandpass filter frequency range is used as the target frequency, and the corresponding wavelet transform amplitude curve is plotted. The time corresponding to the peak value of the first wave packet in the wavelet transform amplitude curve is taken as the signal arrival time. The actual propagation distance of the signal simulating an acoustic emission source at one end of the sensor array is obtained, the actual propagation distance of the signal is linearly fitted with the arrival time of the signal, and the signal propagation speed is obtained based on the fitting result. The steps for obtaining the signal propagation speed based on the fitting results include: At one end of the sensor array, a broken lead is used to simulate an acoustic emission source to obtain the corresponding actual signal propagation distance; The actual propagation distance of the signal is linearly fitted to the arrival time of the signal, and the slope of the fitted straight line in the fitting result is taken as the signal propagation speed. An acoustic emission source localization matrix equation is established, and the equation is solved using the least squares method to obtain the signal source position coordinate expression. Substitute the signal arrival time and the signal propagation speed into the expression for the signal source location coordinates to obtain the acoustic emission source localization result.

2. The method for real-time damage localization of spacecraft aluminum alloy metal matrix structures according to claim 1, characterized in that, The step of performing spectral analysis on the original signals from multiple channels to obtain the frequency domain variance curve includes: The spectrum of the original signal is obtained by Fourier transform analysis. The normalized amplitude of a single channel in the spectrum is used as a sample to calculate the variance of the spectral amplitude at each frequency, thus obtaining the frequency domain variance curve.

3. The method for real-time damage localization of spacecraft aluminum alloy metal matrix structures according to claim 1, characterized in that, The step of searching for a frequency range not exceeding the reference threshold at preset frequency intervals as the bandpass filtering range of the original signal further includes: Search for frequency ranges that do not exceed the reference threshold at preset frequency intervals; The first frequency range found in the search is determined as the bandpass filtering range of the original signal.

4. The method for real-time damage localization of spacecraft aluminum alloy metal matrix structures according to claim 1, characterized in that, The steps of establishing the acoustic emission source localization matrix equation and solving the acoustic emission source localization matrix equation using the least squares method to obtain the signal source position coordinate expression include: Establish the acoustic emission source localization equation, and use the original signal of one of the channels as a reference to establish the acoustic emission source localization matrix equation; The acoustic emission source localization matrix equation is solved using the least squares method to obtain the signal source position coordinate expression.

5. The method for real-time damage localization of spacecraft aluminum alloy metal matrix structures according to claim 4, characterized in that, There are N sensing units, each located in the positioning area. x i , y i ) i =1… N At the location, respectively at the signal arrival time t i Receive at all times t 0 The original signal generated at time t, the signal source is ( x 0 , y 0 If the signal propagation speed is c, then the acoustic emission source localization equation is: .

6. The method for real-time damage localization of spacecraft aluminum alloy metal matrix structures according to claim 5, characterized in that, The step of establishing the acoustic emission source localization matrix equation using the original signal from one of the channels as a reference includes: The acoustic emission source localization equation is squared, and the original signal of one of the channels is used as a reference to eliminate the quadratic terms of the acoustic emission source position parameters in the acoustic emission source localization equation, so as to form an acoustic emission source localization matrix equation in matrix form.

7. The method for real-time damage localization of spacecraft aluminum alloy metal matrix structures according to claim 4, characterized in that, The step of solving the acoustic emission source localization matrix equation using the least squares method to obtain the signal source position coordinate expression includes: The error function of the acoustic emission source localization matrix equation is set according to the least squares method; The corresponding signal source position coordinate expression is calculated based on the error function.

8. The method for real-time damage localization of spacecraft aluminum alloy metal matrix structures according to claim 1, characterized in that, A plurality of the aforementioned sensing units are linearly and equally spaced on the surface of the object being tested, and the sensing units are piezoelectric ceramic sheets.

Images