Composite material impact positioning method based on optical fiber sensor, medium and equipment

Abstract

The invention relates to the technical field of structural health detection, and particularly discloses a composite material impact positioning method based on an optical fiber sensor, a medium and equipment. According to the method, the optical fiber sensor is embedded into a composite material, an impact response signal in the material is monitored in real time, and corresponding signals of all FBG sensors serve as reference data; and then preprocessing is carried out, Fourier transform is utilized to obtain a frequency domain signal, the characteristic quantity of related energy is calculated according to the frequency domain signal, and accurate positioning of an impact position is realized according to a weighted centroid algorithm. According to the method, the sampling frequency is far lower than that of a time positioning method, and the data size is far smaller than that of an artificial neural grid method, so that the impact position can be accurately positioned under low-frequency and small-data samples, the test period is effectively shortened, the positioning accuracy is improved, and the method has universality.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of structural health monitoring, in particular to a composite material impact positioning method based on an optical fiber sensor, a medium and equipment. BACKGROUND

[0002] Composite materials are widely used in aerospace, civil engineering, and rail transportation due to their excellent properties such as light weight, high strength, fatigue resistance, and corrosion resistance. However, the reliability of composite materials faces many challenges. The damage forms of composite materials are complex and diverse, including delamination, matrix cracking, fiber breakage, and interfacial debonding. These damage forms are coupled with each other, making damage analysis extremely complex. In addition, the damage of composite materials often has strong concealment. Even if the strength has decreased sharply, visual inspection is difficult to find serious delamination and other damages inside the structure, until the structure appears rapid and large-scale damage. This concealment makes it difficult to find potential damage in daily maintenance and inspection, which may lead to sudden structural failure, causing huge economic losses and safety hazards. At the same time, composite materials have anisotropic performance characteristics, and their mechanical properties, thermal expansion coefficients, etc. differ in different directions, which makes it difficult to accurately assess the damage when traditional detection methods are applied to composite materials. Because these methods are usually based on the assumption of isotropic materials, they cannot effectively consider the anisotropic properties of composite materials, resulting in inaccurate or biased detection results. The detection results of composite materials need to be improved, and traditional detection methods often need more accurate models and algorithms to adapt to the complex material properties of anisotropic composite materials.

[0003] Therefore, it is urgent to develop a method that can accurately detect and efficiently evaluate the damage of composite materials to solve the problems existing in the prior art. SUMMARY

[0004] The technical problem to be solved by the present application is to overcome the deficiencies existing in the prior art and provide an accurate and efficient composite material impact positioning method based on an optical fiber sensor, a medium and equipment.

[0005] To solve the above technical problems, the present application adopts the following technical solutions: The composite material impact positioning method based on the optical fiber sensor comprises: Obtaining the wavelength signals of a plurality of FBG sensors in the composite material before and during impact, and preprocessing the wavelength signals to obtain the time domain signals of each FBG sensor before and during impact; Performing Fourier transform on the time domain signals before and during impact to obtain the frequency domain signals before and during impact; By integrating the energy density spectrum curves of the frequency domain signals before and during the impact, the total energy of the frequency domain signals before and during the impact of each FBG sensor is obtained. Calculate the difference between the total energy of the frequency domain signal before impact and the total energy of the frequency domain signal during impact for each FBG sensor, and use the difference as a feature value; The impact location is obtained by weighted averaging of each feature value with the coordinates of its corresponding FBG sensor.

[0006] As a further improvement to the above technical solution: The Fourier transform of the time-domain signals before and during the impact satisfies the following relationship: ; in: It is a frequency domain signal. It is a time-domain signal. It's frequency. It is an imaginary unit, and t represents time.

[0007] As a further improvement to the above technical solution: After performing Fourier transforms on the time-domain signals before and during the impact to obtain the frequency-domain signals before and during the impact, the method further includes: Based on the amplitude and phase information of different frequency components of the frequency domain signal before and during the impact, the corresponding frequency domain signal diagrams are plotted.

[0008] As a further improvement to the above technical solution: After performing Fourier transforms on the time-domain signals before and during the impact to obtain the frequency-domain signals before and during the impact, the method further includes: The frequency domain signals before and during the impact are normalized. Specifically, the normalization process involves: Divide the amplitude of the frequency domain signal at the time of impact by the amplitude of the frequency domain signal before impact, or scale the amplitude of the frequency domain signal before and during impact to the range of [0,1].

[0009] As a further improvement to the above technical solution: Integrating the energy density spectrum curves of the frequency domain signals before and during impact yields the total energy of the frequency domain signal before impact and the total energy of the frequency domain signal during impact for each FBG sensor, including: The total energy of the signal before the impact is obtained from the energy density spectrum curve of the frequency domain signal before the impact. The expression is as follows: ; in: This represents the power spectral density of the signal in the frequency domain before the impact. and These are the starting and ending frequencies for frequency domain analysis, respectively. Based on the energy density spectrum curve of the impact time-frequency domain signal, the total energy of the impact signal is obtained. The expression is as follows: .

[0010] As a further improvement to the above technical solution: The calculation involves determining the difference between the total energy of the frequency domain signal before impact and the total energy of the frequency domain signal during impact for each FBG sensor. It satisfies the following relationship: .

[0011] As a further improvement to the above technical solution: The impact location is calculated by weighted averaging of each feature value and its corresponding FBG sensor coordinates, satisfying the following relationship: ; in: For the impact position, Let i be the coordinates of the i-th FBG sensor. is the energy value of the i-th FBG sensor, and n is the number of FBG sensors.

[0012] As a further improvement to the above technical solution: After calculating the impact location by weighted averaging of each feature value and its corresponding FBG sensor coordinates, the method further includes: A grid is divided on the composite material, and the strain value of each grid is calculated using strain data measured by an FBG sensor. Then, a two-dimensional cloud map of the impact location is drawn based on the magnitude and distribution of the strain values.

[0013] The present invention also provides a readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the composite material impact positioning method based on fiber optic sensors as described above.

[0014] The present invention also provides an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the composite material impact positioning method based on fiber optic sensors as described above.

[0015] Compared with the prior art, the advantages of the present invention are as follows: A composite material impact location method based on fiber optic sensors is disclosed. This method embeds fiber optic sensors into the composite material to monitor the impact response signals inside the material in real time. The corresponding signals from each FBG sensor are used as reference data, preprocessed, and then Fourier transform is used to obtain the frequency domain signal. Based on the frequency domain signal, the relevant energy characteristics are calculated, and then the impact location is accurately located using a weighted centroid algorithm. This method not only has a much lower sampling frequency than time-based location methods but also requires significantly less data than artificial neural network methods. Therefore, it can achieve accurate impact location under low frequency and small data sample conditions, effectively shortening the test cycle, improving location accuracy, and possessing universality. Attached Figure Description

[0016] Figure 1 This is a flowchart of the composite material impact positioning method based on fiber optic sensors according to an embodiment of the present invention; Figure 2 This is a schematic diagram showing the arrangement of the FBG sensor in the composite material in the embodiment; Figure 3 This is a schematic diagram of the impact location selected during the impact in the embodiment; Figure 4(a) is a time-domain information diagram before the impact in the embodiment, and Figure 4(b) is a time-domain information diagram during the impact; Figure 5(a) is a frequency domain information diagram before the impact in the embodiment, and Figure 5(b) is a frequency domain information diagram during the impact; Figure 6 This is a graph showing the generation of feature values ​​in the embodiment; Figures 7(a), 7(b), and 7(c) are two-dimensional cloud maps of the impact locations selected in the embodiments.

[0017] In the diagram: 1. FBG sensor; 2. Alkali-free woven fabric; 3. Fiberglass. Detailed Implementation

[0018] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] like Figure 1 As shown, this embodiment provides a composite material impact positioning method based on fiber optic sensors, including: Step 1: Obtain the wavelength signals of multiple FBG sensors (fiber Bragg grating sensors) in the composite material before and during impact, and preprocess the wavelength signals to obtain the time domain signals of each FBG sensor before and during impact. Preferred, such as Figure 2As shown, the impact testing system was constructed in this embodiment by means of the following method when preparing the composite material: three FBG sensors 1 were fixed on top of an alkali-free woven square cloth 2, with three layers of glass fiber 3 on the top and bottom, each measuring 320mm*400mm*5mm. The distance between each FBG sensor 1 was 80mm, and the distance between each grid point was 100mm. The composite material was fixed at the four corners on a fixed platform composed of four aluminum materials. Three FBG sensors 1 are deployed in parallel to each other. Each FBG sensor 1 has three grating points, and a rectangular coordinate system is established to determine the coordinates of each grating. The final impact testing system consists of alkali-free woven fabric 2 (1 layer), glass fiber 3 (6 layers), FBG sensors (3 pieces), spring impact hammer (1J), and fiber optic demodulator (frequency 100Hz).

[0020] Preferably, before acquiring data before and during the impact, a pre-experimental repeatability assessment is conducted to evaluate the consistency of the sensor response signal and determine the reference path loss value of the sensor signal.

[0021] Specifically, such as Figure 3 As shown, in this embodiment, three impact positions (0.21, 0.18), (0.16, 0.18), and (0.15, 0.14) were selected on the composite material. Two impacts were repeated for each position, and data recorded by nine grating points of three FBGs were collected in each test. The collected data was then preprocessed to obtain the time-domain signals of each FBG sensor before and during the impact test. Time-domain diagrams were plotted according to the time-domain signals, as shown in Figure 4(a) and Figure 4(b). The horizontal axis in the figure represents time, and the vertical axis represents the amplitude of the signal.

[0022] Before impact, the raw time-domain signal received by the FBG sensor was relatively stable with small fluctuations, indicating that the composite material was in a stable state before impact. During impact, the time-domain signal received by the FBG sensor showed significant fluctuations and changes, indicating the dynamic response inside the composite material during impact.

[0023] Step 2: Perform Fourier transform on the time-domain signals before and during the impact to obtain the frequency-domain signals before and during the impact. Specifically, the preprocessed time-domain signal is analyzed in the frequency domain using Fourier transform to obtain the power spectral density of the time-domain signal at different frequencies. The expression for the frequency domain analysis is as follows: ; in: It is a frequency domain signal. It is a time-domain signal. It's frequency. It is the imaginary unit, t represents time; After Fourier transform, the time-domain signal is decomposed into amplitude and phase information of different frequency components, so that the energy distribution of the signal at different frequencies can be observed more clearly. Preferably, after performing Fourier transform on the time-domain signals before and during the impact to obtain the frequency-domain signals before and during the impact, a corresponding frequency-domain signal graph is plotted based on the amplitude and phase information of different frequency components of the frequency-domain signals before and during the impact. The frequency-domain signals before and during the impact are then normalized to better observe and compare the intensity of different frequency components. Specifically, the amplitude of the frequency-domain signal during the impact is divided by the amplitude of the frequency-domain signal before the impact, or the amplitudes of the frequency-domain signals before and during the impact are scaled to the [0,1] interval. The frequency-domain signal graphs are shown in Figures 5(a) and 5(b), where the horizontal axis represents frequency and the vertical axis represents the amplitude (power spectral density) of the signal.

[0024] Before impact, the frequency domain signal received by the FBG sensor shows that the energy of the signal is mainly concentrated in the lower frequency range and the amplitude is relatively small, reflecting the background noise and small vibration characteristics of the composite material before impact. During impact, the frequency domain signal received by the FBG sensor shows obvious energy peaks in a specific frequency range, reflecting the vibration response at a specific frequency generated inside the composite material when the impact event occurs.

[0025] Step 3: Integrate the energy density spectrum curves of the frequency domain signals before and during the impact to obtain the total energy of the frequency domain signal before the impact and the total energy of the frequency domain signal during the impact for each FBG sensor, including: The total energy of the signal before the impact is obtained from the energy density spectrum curve of the frequency domain signal before the impact. The expression is as follows: ; in: This represents the power spectral density of the signal in the frequency domain before the impact. and These are the starting and ending frequencies for frequency domain analysis, respectively. Based on the energy density spectrum curve of the impact time-frequency domain signal, the total energy of the impact signal is obtained. The expression is as follows: .

[0026] Step 4: Calculate the difference between the total energy of the pre-impact frequency domain signal and the total energy of the impact frequency domain signal for each FBG sensor, and use this difference as a characteristic value, expressed as follows: .

[0027] The energy difference S obtained through the above steps can reflect the change in energy inside the composite material when an impact event occurs, and can be used as a characteristic value for impact localization.

[0028] like Figure 6 As shown in the image, the dashed line represents the energy density spectrum of the frequency domain signal before impact, reflecting the background energy distribution of the composite material when it is not impacted; the solid line represents the energy density spectrum of the frequency domain signal during impact, reflecting the energy response characteristics inside the composite material when the impact event occurs. The area formed by its energy density spectrum and the X and Y axes represents the total energy of the signal in the frequency domain. The area before impact reflects the background energy level of the composite material when it is not impacted, while the area during impact reflects the energy response inside the composite material after the impact event. The difference S between the two is the energy change caused by the impact, which can be used to assess the intensity and location of the impact. The shaded area is the energy map that overlaps before and during the impact, therefore it can be used... Figure 6 The energy difference S is calculated using the shadow areas S1, S2, and S3 of the non-shadowed areas, where S = S1 - S2 + S3.

[0029] S1, S2, and S3 are the differences in energy in the frequency domain of the signals collected during the impact and before the impact, respectively, within three different time periods throughout the entire impact cycle. S is the total energy difference between the impact and before the impact, and this total energy difference S is used as the characteristic value of the signal.

[0030] In this embodiment, the signals collected by the sensor yield nine corresponding feature values.

[0031] Step 5: Calculate the impact location by performing a weighted average of each feature value and its corresponding FBG sensor coordinates, as shown in the following expression: ; in: For the impact position, Let i be the coordinates of the i-th FBG sensor. is the energy value of the i-th FBG sensor, and n is the number of FBG sensors; The impact location is estimated by weighting the impact energy characteristic value received by each sensor. The sensor with the larger energy characteristic value has a greater influence on the impact location, thus obtaining the predicted impact location. Preferably, after calculating the impact location by weighted averaging of each feature value and its corresponding FBG sensor coordinates, the method further includes: dividing the composite material into grids, using strain data measured by the FBG sensor, calculating the strain value of each grid using interpolation algorithms and other methods, and then drawing a two-dimensional cloud map of the impact location based on the magnitude and distribution of the strain value to intuitively display the strain distribution characteristics of the impact area, as shown in Figures 7(a), 7(b) and 7(c), which are two-dimensional cloud maps of the three impact locations, respectively.

[0032] This embodiment presents a composite material impact location method based on fiber optic sensors. This method embeds fiber optic sensors into the composite material to monitor the impact response signals within the material in real time. The corresponding signals from each FBG sensor are used as reference data, preprocessed, and then Fourier transform is used to obtain the frequency domain signal. Based on the frequency domain signal, the relevant energy characteristics are calculated, and then the impact location is accurately located using a weighted centroid algorithm. This method not only has a much lower sampling frequency than time-based location methods but also requires significantly less data than artificial neural network methods. Therefore, it can achieve accurate impact location even with low frequencies and small data samples, effectively shortening the test cycle, improving location accuracy, and possessing universality. This technology has significant application value in aerospace, civil engineering, and rail transportation fields.

[0033] In the aerospace field, this method, with its lightweight, interference-resistant, and high-sensitivity characteristics, provides real-time and accurate data for aircraft structural health monitoring. In civil engineering, this technology can monitor minute deformations in high-rise buildings and predict potential structural problems. In the rail transit field, the composite material impact positioning method based on fiber optic sensors, with its lightweight, interference-resistant, and high-sensitivity characteristics, provides real-time and accurate data for train structural health monitoring, track safety assessment, and wheel-rail interaction analysis, while optimizing train operation efficiency and maintenance plans, ensuring the safety and reliability of rail transit systems. Overall, this fiber optic sensor-based method plays a crucial role in structural health monitoring due to its real-time monitoring, high-precision positioning, and interference resistance capabilities, ensuring the safety and reliability of critical structures in various industries and possessing broad application value.

[0034] This embodiment also includes a readable storage medium storing a computer program that, when executed by a processor, implements the composite material impact positioning method based on fiber optic sensors as described above.

[0035] For example, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units may be a series of computer program segments capable of performing a specific function, and these instruction segments describe the execution process of the computer program in the electronic device.

[0036] This embodiment also provides an electronic device, including: a processor, a memory, and a computer program stored in the memory and executable by the processor. When the processor executes the computer program, it implements the composite material impact positioning method based on fiber optic sensors as described above.

[0037] The electronic device can be a mobile phone, desktop computer, laptop, handheld computer, cloud server, or other computing device. The electronic device may include, but is not limited to, processors and memory. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0038] The above description is merely a preferred embodiment of the present invention, and the scope of protection of the present invention is not limited to the above embodiments. For those skilled in the art, improvements and modifications obtained without departing from the inventive concept should also be considered within the scope of protection of the present invention.

Claims

1. A composite material impact positioning method based on fiber optic sensors, characterized in that, include: The wavelength signals of multiple FBG sensors in the composite material before and during impact are acquired, and the wavelength signals are preprocessed to obtain the time domain signals of each FBG sensor before and during impact. Fourier transform is performed on the time-domain signals of each FBG sensor before and during impact to obtain the frequency-domain signals of each FBG sensor before and during impact. By integrating the energy density spectrum curves of the frequency domain signals before and during the impact, the total energy of the frequency domain signals before and during the impact of each FBG sensor is obtained. Calculate the difference between the total energy of the frequency domain signal before impact and the total energy of the frequency domain signal during impact for each FBG sensor, and use the difference as a feature value; The impact location is obtained by weighted averaging of each feature value with the coordinates of its corresponding FBG sensor.

2. The composite material impact positioning method based on fiber optic sensors according to claim 1, characterized in that, The Fourier transform of the time-domain signals before and during the impact satisfies the following relationship: ； in: It is a frequency domain signal. It is a time-domain signal. It's frequency. It is an imaginary unit, and t represents time.

3. The composite material impact positioning method based on fiber optic sensors according to claim 1, characterized in that, After performing Fourier transforms on the time-domain signals before and during the impact to obtain the frequency-domain signals before and during the impact, the method further includes: Based on the amplitude and phase information of different frequency components of the frequency domain signal before and during the impact, the corresponding frequency domain signal diagrams are plotted.

4. The composite material impact positioning method based on fiber optic sensors according to claim 1, characterized in that, After performing Fourier transforms on the time-domain signals before and during the impact to obtain the frequency-domain signals before and during the impact, the method further includes: The frequency domain signals before and during the impact are normalized. Specifically, the normalization process involves: Divide the amplitude of the frequency domain signal at the time of impact by the amplitude of the frequency domain signal before impact, or scale the amplitude of the frequency domain signal before and during impact to the range of [0,1].

5. The composite material impact positioning method based on fiber optic sensors according to any one of claims 1-4, characterized in that, Integrating the energy density spectrum curves of the frequency domain signals before and during impact yields the total energy of the frequency domain signal before impact and the total energy of the frequency domain signal during impact for each FBG sensor, including: The total energy of the signal before the impact is obtained from the energy density spectrum curve of the frequency domain signal before the impact. It satisfies the following expression: ； in: This represents the power spectral density of the signal in the frequency domain before the impact. and These are the starting and ending frequencies for frequency domain analysis, respectively. Based on the energy density spectrum curve of the impact time-frequency domain signal, the total energy of the impact signal is obtained. It satisfies the following expression: 。 6. The composite material impact positioning method based on fiber optic sensors according to claim 5, characterized in that, The calculation involves determining the difference between the total energy of the frequency domain signal before impact and the total energy of the frequency domain signal during impact for each FBG sensor. It satisfies the following relationship: 。 7. The composite material impact positioning method based on fiber optic sensors according to claim 6, characterized in that, The impact location is calculated by weighted averaging of each feature value and its corresponding FBG sensor coordinates, satisfying the following relationship: ； in: For the impact position, Let i be the coordinates of the i-th FBG sensor. is the energy value of the i-th FBG sensor, and n is the number of FBG sensors.

8. The composite material impact positioning method based on fiber optic sensors according to claim 7, characterized in that, After calculating the impact location by weighted averaging of each feature value and its corresponding FBG sensor coordinates, the method further includes: A grid is divided on the composite material, and the strain value of each grid is calculated using strain data measured by an FBG sensor. Then, a two-dimensional cloud map of the impact location is drawn based on the magnitude and distribution of the strain values.

9. A readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the composite material impact positioning method based on a fiber optic sensor as described in any one of claims 1-8.

10. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the composite material impact positioning method based on a fiber optic sensor as described in any one of claims 1-8.

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