Abnormal vibration monitoring method for aircraft

Abstract

The present invention belongs to the technical field of vibration testing of structural components, and specifically relates to a method for monitoring abnormal vibration of an aircraft, which solves the technical problems of low sampling accuracy and inability to achieve real-time online monitoring in existing methods. The method comprises building a sensor signal acquisition system, which includes a vibration measurement module, a multi-channel switching matrix, a noise generator, an ADC sampling chip, an FPGA controller, a USB controller, an eMMC memory, an RS422 transceiver, and a power management and power distribution unit; the FPGA controller compares the sensor data with a set threshold value, and if the threshold value is exceeded, it is considered that an abnormal vibration event has occurred at the corresponding position. At this time, a total of 500ms of data before and after the vibration occurs is stored in the eMMC memory, the FPGA controller analyzes the abnormal vibration data, calculates the position of the vibration source, and frames the vibration source position and sends it to a host computer.

Description

Technical Field

[0001] The present invention relates to the technical field of vibration testing of structural components, and in particular to an abnormal vibration monitoring method for an aircraft. Background Art

[0002] Monitoring abnormal vibration during flight is a key area of ​​research for aircraft status monitoring. Vibration signals directly reflect the structural health of an aircraft. Analysis of these signals can effectively identify potential faults and anomalies. During normal flight, the vibration acceleration on an aircraft typically ranges from 0.1g to 2g. Any acceleration outside this range, especially exceeding 2g, is considered an abnormal vibration event. By installing vibration sensors and a vibration monitoring system, vibration levels can be monitored in real time, helping to identify potential structural issues in the aircraft, ensuring flight safety, and providing data support for subsequent aircraft design and optimization, significantly improving aircraft safety and reliability.

[0003] China has proposed corresponding monitoring methods for abnormal vibration monitoring of aircraft: Patent 202311027173.8 proposes a distributed multi-parameter test system suitable for aircraft. The system uses multiple types of sensor devices to form an array and uses a single-chip ADC to collect and analyze the array signals. This sampling method can realize the sampling of multi-channel signals on a single ADC, saving a lot of board-level space and cost. However, due to the existence of channel switching delay, the system needs to use a high-sampling rate ADC to reduce the waiting time of the T / H (sample / hold) stage. However, for ADCs, there is an inherent contradiction between high sampling rate and high sampling resolution. The sampling resolution of common high-speed ADCs on the market is slightly insufficient for sensor data that requires precise sampling, which seriously affects the recording accuracy of the sensor sampling system and also brings limitations to subsequent data processing and analysis.

[0004] "Han Ze. Design and Implementation of an Ultrasonic Guided Wave Active Structural Health Monitoring System [D]. Shandong University, 2023" and "Guo Fangyu. Research on Guided Wave Monitoring Methods for Aircraft Structural Corrosion [D]. Nanjing University of Aeronautics and Astronautics, 2018" propose two structural health monitoring systems suitable for aircraft and other equipment. Both use active monitoring methods. The basic principle is to use a piezoelectric guided wave active excitation source to apply excitation to structural components, and a sensor array receives the signal. The signal is analyzed to detect potential damage in the structural components. However, this method requires a large amount of data and models to calibrate and optimize the algorithm, and the computational complexity is very large. It is only suitable for ground maintenance and cannot achieve real-time monitoring. In addition, the structural health monitoring system is only for post-maintenance and lacks effective means to record abnormal events that occur during flight. Some abnormal vibrations that occur during flight cannot be detected, recorded, or analyzed, making real-time online monitoring impossible. Summary of the Invention

[0005] In order to overcome the technical defects of the existing methods, such as low sampling accuracy and inability to achieve real-time online monitoring, the present invention provides a method for monitoring abnormal vibration of an aircraft.

[0006] The present invention provides a method for monitoring abnormal vibration of an aircraft, comprising building a sensor signal acquisition system, wherein the sensor signal acquisition system comprises a vibration measurement module, a multi-channel switching matrix, a noise generator, an ADC sampling chip, an FPGA controller, a USB controller, an eMMC memory, an RS422 transceiver, and a power management and power distribution unit, wherein the power management and power distribution unit supplies power to the sensor signal acquisition system as a whole; the vibration measurement module comprises a plurality of normal temperature uniaxial acceleration sensors, a plurality of normal temperature triaxial acceleration sensors, and a plurality of high temperature acceleration sensors, wherein the normal temperature uniaxial acceleration sensors and the normal temperature triaxial acceleration sensors are respectively arranged in a matrix form. Installed on the wing skin and keel, high-temperature acceleration sensors are installed on the surface of the left engine and the right engine. The output signal of the high-temperature acceleration sensor is processed by the sensor signal transmitter and transmitted to the multi-channel switching matrix. The output signals of the normal temperature uniaxial acceleration sensor and the normal temperature triaxial acceleration sensor are directly transmitted to the input end of the multi-channel switching matrix. The multi-channel switching matrix includes a group of analog switch arrays controlled by the FPGA controller. Under the control of the FPGA controller, the signal of any input channel of the multi-channel switching matrix can be transmitted to the output channel of the multi-channel switching matrix. The output signal of the multi-channel switching matrix is ​​sent to the ADC sampling chip. The output end of the noise generator is connected to the A The input end of the DC sampling chip is connected to the noise generator, which includes a resistor, an operational amplifier and a low-pass filter. The random white noise generated by the thermal disturbance of the resistor is amplified by the operational amplifier and processed by the low-pass filter to generate a narrow-band disturbance signal. The original analog input signal obtained by superimposing the narrow-band disturbance signal and the output signal of the multi-channel switching matrix is ​​input into the ADC sampling chip for sampling; the FPGA controller processes the sampling result output by the ADC sampling chip through the FIR high-pass filter to filter out the narrow-band disturbance signal added in the early stage. The final data is the sampling result after the disturbance processing. The output signal of the ADC sampling chip is filtered and framed by the FPGA controller. The FPGA controller compares the multi-channel sensor data obtained by each sampling of the ADC sampling chip with the set threshold value. If the sensor data of a certain channel exceeds the threshold, it is considered that an abnormal vibration event has occurred at the corresponding position. When an abnormal vibration event is detected, the 500ms data before and after the abnormal vibration occurs is stored in the eMMC memory as abnormal vibration data. The FPGA controller uses a positioning method based on the RSSI algorithm to analyze the abnormal vibration data, calculate the location of the abnormal vibration source, and frame the calculated vibration source location. It is sent to the host computer through the RS422 transceiver.

[0007] The steps of the positioning method based on the RSSI algorithm are:

[0008] S1. Assume that the amplitude decay of abnormal vibration data conforms to the exponential decay model:

[0009] ,

[0010] formula middle, Indicates the The amplitude of the signal received by each sensor; Indicates the signal amplitude of the vibration source; Indicates the vibration source to the The distance between the sensors; represents the attenuation coefficient, Determined through testing;

[0011] S2, known The placement of the sensors is ( ), by analyzing the amplitude of the signals received by multiple sensors and establishing a set of equations, the position and amplitude of the vibration source can be solved; assuming that the position of the vibration source is ( ), according to the amplitude attenuation model in step S1, the vibration source to the The distance between the sensors is expressed as:

[0012] ,

[0013] S3, using triangulation method, for the sensors, the position of the vibration source satisfies the formula :

[0014] ,

[0015] Expand the formula The nonlinear equation in and convert it into a linear equation:

[0016] ,

[0017] Use the vibration source relative to the The position formula of the first sensor minus the position formula of the vibration source relative to the first sensor eliminates and After simplifying, we get:

[0018] ,

[0019] Then, for sensors, we can get Linear equations, these equations are written in matrix form:

[0020] ,

[0021] formula middle, is the coefficient matrix; where:

[0022] ,

[0023] ,

[0024] ,

[0025] Finally, the least squares method is used to solve:

[0026] ,

[0027] formula middle, yes The transposed matrix of yes The inverse matrix of the solution vector p is the vibration source position ( ).

[0028] The core function of this method is to monitor the vibration status of the aircraft in real time during flight and to identify and locate the vibration source in real time when abnormal vibration events occur. The vibration measurement module can sense the vibration of the aircraft body and convert the vibration signal of the structure into an electrical signal. The sensor signal transmitter is used to convert the charge signal output by the accelerometer into a voltage signal suitable for back-end acquisition and analysis. The multi-channel switching matrix includes multiple input channels and one output channel, and is internally composed of a set of analog switch arrays controlled by external signals.

[0029] A noise generator is used to generate random disturbance signals. Resistor thermal noise is caused by the thermal agitation of charge carriers within the resistor. This irregular electron motion produces tiny voltage fluctuations across the resistor. Because these voltage fluctuations are random, they are white noise, with a near-Gaussian distribution. The resistor thermal noise voltage (rms value) can be calculated using the following formula:

[0030] , in the formula is the Boltzmann constant, usually taken as =1.38×10 -23 J / K; is the temperature (in Kelvin, K); is the resistance value (in ohms, Ω); is the noise bandwidth (in Hertz, Hz), which is the frequency range of the measurement. and Changes in the square root of the noise factor affect the noise, so the amplified resistor-derived noise source is stable. Therefore, the present invention uses a simple large resistor combined with an operational amplifier to generate Gaussian white noise, which is easy to operate and low-cost. The low-pass filter cutoff frequency in the noise generator is approximately one-tenth of the sampling frequency, which is much lower than the input signal bandwidth. At this time, the narrowband disturbance signal and the input signal are independent in the frequency domain, making it easier to filter out the disturbance signal in the sampling results later.

[0031] The ADC sampling chip is responsible for sampling sensor signals from the multi-channel switching matrix and converting the analog signals into digital signals. The FPGA controller serves as the main control module of the entire system, controlling the entire sampling, storage, analysis, and transmission process. During the sampling process of the output signal of the multi-channel switching matrix, the ADC sampling chip will cause harmonic spurious due to problems with coherent sampling and channel switching, resulting in distortion of the ADC sampling chip and increasing the sampling error. In order to minimize this error as much as possible, the present invention proposes a method of injecting out-of-band disturbances to reduce the sampling error of the ADC sampling chip. The sampling error is mainly reflected in the deterioration of the dynamic performance of the ADC sampling chip, among which SFDR (spurious-free dynamic range) is one of the important indicators of the dynamic performance of the ADC sampling chip.

[0032] During the sampling and quantization process, ADC sampling chips often exhibit inherent imperfections (such as DNL error, which refers to the difference between the actual codeword and the ideal codeword) that can lead to variations in quality and quantization results. This is particularly true when the sampling dynamic range and the amount of sampled data are large. The resulting "bad codewords" can be periodic and repetitive, leading to harmonic growth and deteriorating the signal's spurious-free dynamic range (SFDR). The main principle behind out-of-band dithering is that the dithering signal, a random signal with no correlation with the input signal, is superimposed on the input signal at the ADC sampling chip input. This disrupts the periodicity of the ADC sampling chip's quantization error, averages the DNL error, and normalizes the DNL dispersion, making the ADC sampling chip's quantization process more linear. Ultimately, this approach reduces coherent spurious signals to within the noise floor. While this method increases the ADC sampling chip's noise floor and slightly reduces the SNR, it improves the quality of the effective signal, significantly improving the SFDR of the ADC sampling chip and significantly enhancing the sampling accuracy of the ADC sampling chip. High-precision signal sampling provides reliable data support for the subsequent vibration positioning method based on amplitude changes.

[0033] In the present invention, a USB controller is used to transmit sampled data to a host computer and receive configuration files from the host computer, enabling bidirectional communication between the FPGA controller and the host computer via the USB controller. The eMMC memory is used to store data collected by the device from different sensors, including normal data and abnormal data corresponding to abnormal vibration events. The RS422 transceiver is used to provide feedback on vibration position identification and positioning results. The FPGA controller controls bidirectional data communication between it and the USB controller via its internal USB transmission control module. The FPGA controller controls the eMMC memory via its internal eMMC read / write control module, completing data read and write functions. The task management and storage control module within the FPGA controller is used to control storage task management, USB data transmission, and eMMC memory read and write scheduling functions. After system startup, the FPGA controller first reads device information from the eMMC memory via the task management and storage control module and initializes the device. After initialization is complete, the FPGA controller enters a waiting state. In the waiting state, when the FPGA controller receives a successful enumeration instruction from the USB controller, it enters a data transmission state, waiting for the host computer to send a read data instruction or a write data instruction. When the FPGA controller receives a read data instruction, the task management and storage control module of the FPGA controller controls the eMMC read-write control module inside the FPGA controller to read the stored data from the eMMC memory, and then send the data to the host computer through the USB controller; if the FPGA controller receives a write data instruction, the data received by the USB controller is written to the corresponding storage location of the eMMC memory as a new configuration file.

[0034] Positioning algorithms based on the RSSI (Received Signal Strength Indicator) algorithm primarily estimate position by analyzing the attenuation characteristics of signal strength. In practical applications, RSSI-based positioning algorithms have low requirements for time synchronization and rely primarily on accurate measurement of signal amplitude. Using this positioning algorithm to calculate the vibration source location provides data support for subsequent aircraft maintenance and optimization, improving flight safety and reliability.

[0035] Preferably, the sensor signal transmitter includes a charge-to-voltage conversion circuit, a filtering circuit, and an amplification and limiting circuit. The input charge signal is first converted into a voltage signal by the charge-to-voltage conversion circuit. The voltage signal is then filtered out by the filtering circuit to remove low-frequency interference signals and high-frequency resonant signals. Finally, the filtered voltage signal is amplified and limited by the amplification and limiting circuit to adapt to the input voltage range of the ADC sampling chip. The amplification and limiting circuit includes a signal amplification circuit and a signal limiting circuit.

[0036] Preferably, the ADC sampling chip includes a 6-bit first-stage ADC module, a 7-bit second-stage ADC module, a DAC module and an amplifier component. The original analog input signal is first converted into a digital signal by the first-stage ADC module and then converted into a new analog signal by the DAC module. The new analog signal is subtracted from the original analog input signal to obtain a residual signal after the first-stage conversion. The residual signal is gain-adjusted by the amplifier component and then enters the second-stage ADC module for conversion to obtain a digital signal. Finally, the digital signal converted by the first-stage ADC module and the digital signal converted by the second-stage ADC module are added to obtain a final conversion result.

[0037] Preferably, the threshold value set in the FPGA controller is a vibration acceleration value of 2g.

[0038] Compared with the prior art, the technical solution provided by the present invention has the following technical effects: the present invention utilizes a disturbance technology method to improve the sampling accuracy of the ADC sampling chip, and an abnormal vibration identification algorithm based on threshold discrimination and a positioning algorithm based on the RSSI algorithm, thereby realizing the real-time collection and storage of vibration signals, the identification of abnormal vibration events, and the real-time positioning of the abnormal vibration source during the aircraft's flight mission, thereby solving the problems existing in other monitoring methods under the prior art conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0041] Figure 1 This is a flow chart of a sensor signal acquisition system according to an embodiment of the present invention;

[0042] Figure 2 This is a signal processing diagram after an out-of-band disturbance is injected into an analog input signal in an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to more clearly understand the above-mentioned objectives, features and advantages of the present invention, the scheme of the present invention will be further described below. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features therein can be combined with each other.

[0044] In this description, it should be noted that the terms "mounted," "connected," and "connected" should be interpreted broadly. For example, they can refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediary; and internal communication between two components. Those skilled in the art will understand the specific meanings of these terms based on specific circumstances.

[0045] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present invention, rather than all the embodiments.

[0046] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0047] In one embodiment, Figure 1As shown, a method for monitoring abnormal vibration of an aircraft is disclosed, including building a sensor signal acquisition system, the sensor signal acquisition system including a vibration measurement module, a multi-channel switching matrix, a noise generator, an ADC sampling chip, an FPGA controller, a USB controller, an eMMC memory, an RS422 transceiver and a power management and power distribution unit, the power management and power distribution unit supplies power to the sensor signal acquisition system as a whole; the vibration measurement module includes a plurality of normal temperature single-axis acceleration sensors, a plurality of normal temperature three-axis acceleration sensors and a plurality of high-temperature acceleration sensors, the normal temperature single-axis acceleration sensors and the normal temperature three-axis acceleration sensors are respectively installed on the wing skin and the keel in a matrix form, the high-temperature acceleration sensor is installed on the surface of the left engine and the right engine, the output signal of the high-temperature acceleration sensor is processed by the sensor signal transmitter and transmitted to the multi-channel switching matrix, the output signal of the normal temperature single-axis acceleration sensor and the normal temperature three-axis acceleration sensor is transmitted to At the input end of the multi-channel switching matrix, the sensor signal transmitter includes a charge-voltage conversion circuit, a filtering circuit, an amplification and limiting circuit. The input charge signal is first converted into a voltage signal by the charge-voltage conversion circuit, and the voltage signal is then filtered out of low-frequency interference signals and high-frequency resonance signals by the filtering circuit. Finally, the filtered voltage signal is amplified and limited by the amplification and limiting circuit to adapt to the input voltage range of the ADC sampling chip; the multi-channel switching matrix includes a group of analog switch arrays controlled by an FPGA controller. Under the control of the FPGA controller, the signal of any input channel can be transmitted to the output channel of the multi-channel switching matrix. The output signal of the multi-channel switching matrix is ​​sent to the ADC sampling chip. The output end of the noise generator is connected to the input end of the ADC sampling chip. The noise generator includes a resistor, an operational amplifier and a low-pass filter. The random white noise generated by the thermal disturbance of the resistor is amplified by the operational amplifier and processed by the low-pass filter to generate a narrowband disturbance signal, such as Figure 2As shown in the figure, the original analog input signal obtained by superimposing the narrowband disturbance signal and the output signal of the multi-channel switching matrix is ​​input into the ADC sampling chip for sampling; the ADC sampling chip includes a 6-bit first-stage ADC module, a 7-bit second-stage ADC module, a DAC module and an amplifier component. The original analog input signal is first converted into a digital signal by the first-stage ADC module and then converted into a new analog signal by the DAC module. The new analog signal is subtracted from the original analog input signal, that is, the residual signal after the first-stage conversion is obtained. The residual signal is gain-adjusted by the amplifier component and then enters the second-stage ADC module for conversion to obtain a digital signal. Finally, the digital signal converted by the first-stage ADC module and the digital signal converted by the second-stage ADC module are added to obtain the final conversion result; the FPGA controller uses an FIR high-pass filter to filter the sampling result output by the ADC sampling chip. The result is processed and the narrowband disturbance signal added in the early stage is filtered out. The final data obtained is the sampling result after the disturbance processing. The output signal of the ADC sampling chip is filtered and framed by the FPGA controller and then enters the FIFO pre-trigger memory of the FPGA controller. For the multi-channel sensor data obtained by the ADC sampling chip each time, the FPGA controller compares it with the set threshold value. If the sensor data of a certain channel exceeds the threshold, it is considered that an abnormal vibration event has occurred at the corresponding position. When an abnormal vibration event is detected, a total of 500ms of data before and after the abnormal vibration occurs is stored in the eMMC memory as abnormal vibration data. The FPGA controller uses a positioning method based on the RSSI algorithm to analyze the abnormal vibration data, calculate the position of the abnormal vibration source, and frame the calculated vibration source position, and send it to the host computer through the RS422 transceiver.

[0048] The steps of the positioning method based on the RSSI algorithm are:

[0049] S1. Assume that the amplitude decay of abnormal vibration data conforms to the exponential decay model:

[0050] ,

[0051] formula middle, Indicates the The amplitude of the signal received by each sensor; Indicates the signal amplitude of the vibration source; Indicates the vibration source to the The distance between the sensors; represents the attenuation coefficient, Determined through testing;

[0052] S2, known The placement of the sensors is ( ), by analyzing the amplitude of the signals received by multiple sensors and establishing a set of equations, the position and amplitude of the vibration source can be solved; assuming that the position of the vibration source is ( ), according to the amplitude attenuation model in step S1, the vibration source to the The distance between the sensors is expressed as:

[0053] ,

[0054] S3, using triangulation method, for the sensors, the position of the vibration source satisfies the formula :

[0055] ,

[0056] Expand the formula The nonlinear equation in and convert it into a linear equation:

[0057] ,

[0058] Use the vibration source relative to the The position formula of the first sensor minus the position formula of the vibration source relative to the first sensor eliminates and After simplifying, we get:

[0059] ,

[0060] Then, for sensors, we can get Linear equations, these equations are written in matrix form:

[0061] ,

[0062] formula middle, is the coefficient matrix; where:

[0063] ,

[0064] ,

[0065] ,

[0066] Finally, the least squares method is used to solve:

[0067] ,

[0068] formula middle, yes The transposed matrix of yes The inverse matrix of the solution vector p is the vibration source position ( ).

[0069] The core function of the method described in this invention is to monitor the vibration status of an aircraft in real time during flight and to identify and locate the source of abnormal vibration events in real time. The vibration measurement module senses the vibration of the aircraft body and converts the structural vibration signal into an electrical signal. The sensor signal transmitter converts the charge signal output by the accelerometer into a voltage signal suitable for back-end data collection and analysis. The multi-channel switching matrix includes multiple input channels and one output channel, and is internally composed of an array of analog switches controlled by external signals.

[0070] A noise generator is used to generate random disturbance signals. Resistor thermal noise is caused by the thermal agitation of charge carriers within the resistor. This irregular electron motion produces tiny voltage fluctuations across the resistor. Because these voltage fluctuations are random, they are white noise, with a near-Gaussian distribution. The resistor thermal noise voltage (rms value) can be calculated using the following formula:

[0071] , in the formula is the Boltzmann constant, usually taken as =1.38×10 -23 J / K; is the temperature (in Kelvin, K); is the resistance value (in ohms, Ω); is the noise bandwidth (in Hertz, Hz), which is the frequency range of the measurement. and Changes in the square root of the noise factor affect the noise, so the amplified resistor-derived noise source is stable. Therefore, the present invention uses a simple large resistor combined with an operational amplifier to generate Gaussian white noise, which is easy to operate and low-cost. The low-pass filter cutoff frequency in the noise generator is approximately one-tenth of the sampling frequency, which is much lower than the input signal bandwidth. At this time, the narrowband disturbance signal and the input signal are independent in the frequency domain, making it easier to filter out the disturbance signal in the sampling results later.

[0072] The ADC sampling chip is responsible for sampling sensor signals from the multi-channel switching matrix and converting the analog signals into digital signals. The FPGA controller serves as the main control module of the entire system, controlling the entire sampling, storage, analysis, and transmission process. During the sampling process of the output signal of the multi-channel switching matrix, the ADC sampling chip will cause harmonic spurious due to problems with coherent sampling and channel switching, resulting in distortion of the ADC sampling chip and increasing the sampling error. In order to minimize this error as much as possible, the present invention proposes a method of injecting out-of-band disturbances to reduce the sampling error of the ADC sampling chip. The sampling error is mainly reflected in the deterioration of the dynamic performance of the ADC sampling chip, among which SFDR (spurious-free dynamic range) is one of the important indicators of the dynamic performance of the ADC sampling chip.

[0073] During the sampling and quantization process, ADC sampling chips often exhibit inherent imperfections (such as DNL error, which refers to the difference between the actual codeword and the ideal codeword) that can lead to variations in quality and quantization results. This is particularly true when the sampling dynamic range and the amount of sampled data are large. The resulting "bad codewords" can be periodic and repetitive, leading to harmonic growth and deteriorating the signal's spurious-free dynamic range (SFDR). The main principle behind out-of-band dithering is that the dithering signal, a random signal with no correlation with the input signal, is superimposed on the input signal at the ADC sampling chip input. This disrupts the periodicity of the ADC sampling chip's quantization error, averages the DNL error, and normalizes the DNL dispersion, making the ADC sampling chip's quantization process more linear. Ultimately, this approach reduces coherent spurious signals to within the noise floor. While this method increases the ADC sampling chip's noise floor and slightly reduces the SNR, it improves the quality of the effective signal, significantly improving the SFDR of the ADC sampling chip and significantly enhancing the sampling accuracy of the ADC sampling chip. High-precision signal sampling provides reliable data support for the subsequent vibration positioning method based on amplitude changes.

[0074] In the present invention, a USB controller is used to transmit sampled data to a host computer and receive configuration files from the host computer, enabling bidirectional communication between the FPGA controller and the host computer via the USB controller. The eMMC memory is used to store data collected by the device from different sensors, including normal data and abnormal data corresponding to abnormal vibration events. The RS422 transceiver is used to provide feedback on vibration position identification and positioning results. The FPGA controller controls bidirectional data communication between it and the USB controller via its internal USB transmission control module. The FPGA controller controls the eMMC memory via its internal eMMC read / write control module, completing data read and write functions. The task management and storage control module within the FPGA controller is used to control storage task management, USB data transmission, and eMMC memory read and write scheduling functions. After system startup, the FPGA controller first reads device information from the eMMC memory via the task management and storage control module and initializes the device. After initialization is complete, the FPGA controller enters a waiting state. In the waiting state, when the FPGA controller receives a successful enumeration instruction from the USB controller, it enters a data transmission state, waiting for the host computer to send a read data instruction or a write data instruction. When the FPGA controller receives a read data instruction, the task management and storage control module of the FPGA controller controls the eMMC read-write control module inside the FPGA controller to read the stored data from the eMMC memory, and then send the data to the host computer through the USB controller; if the FPGA controller receives a write data instruction, the data received by the USB controller is written to the corresponding storage location of the eMMC memory as a new configuration file.

[0075] Positioning algorithms based on the RSSI (Received Signal Strength Indicator) algorithm primarily estimate position by analyzing the attenuation characteristics of signal strength. In practical applications, RSSI-based positioning algorithms have low requirements for time synchronization and rely primarily on accurate measurement of signal amplitude. Using this positioning algorithm to calculate the vibration source location provides data support for subsequent aircraft maintenance and optimization, improving flight safety and reliability.

[0076] The above description is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Although detailed descriptions have been made with reference to the aforementioned embodiments, those skilled in the art should understand that they may still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents; and such modifications or replacements do not deviate from the essence of the corresponding technical solutions within the scope of the technical solutions of the embodiments, and they should all be included in the scope of protection of the claims.

Claims

1. A method for monitoring abnormal vibration of an aircraft, characterized in that: The invention comprises building a sensor signal acquisition system, which includes a vibration measurement module, a multi-channel switching matrix, a noise generator, an ADC sampling chip, an FPGA controller, a USB controller, an eMMC memory, an RS422 transceiver, and a power management and power distribution unit. The power management and power distribution unit supplies power to the sensor signal acquisition system as a whole. The vibration measurement module includes a plurality of normal temperature single-axis acceleration sensors, a plurality of normal temperature three-axis acceleration sensors, and a plurality of high-temperature acceleration sensors. The normal temperature single-axis acceleration sensors and the normal temperature three-axis acceleration sensors are respectively installed on the wing skin and the keel in a matrix form. The high-temperature acceleration sensor is installed on the surface of the left engine and the right engine. The output signal of the high-temperature acceleration sensor is processed by the sensor signal transmitter and transmitted to the multi-channel switching matrix. The output signals of the room-temperature uniaxial acceleration sensor and the room-temperature triaxial acceleration sensor are directly transmitted to the input end of the multi-channel switching matrix. The multi-channel switching matrix includes a group of analog switch arrays controlled by an FPGA controller. Under the control of the FPGA controller, the signal of any input channel of the multi-channel switching matrix can be transmitted to the output channel of the multi-channel switching matrix. The output signal of the multi-channel switching matrix is ​​sent to the ADC sampling chip. The output end of the noise generator is connected to the input end of the ADC sampling chip. The noise generator includes a resistor, an operational amplifier and a low-pass filter. The random white noise generated by the thermal disturbance of the resistor is amplified by the operational amplifier and processed by the low-pass filter to generate a narrow-band disturbance signal. The original analog input signal obtained by superimposing the narrow-band disturbance signal and the output signal of the multi-channel switching matrix is ​​input into the ADC sampling chip for sampling. The FPGA controller processes the sampling results output by the ADC sampling chip through an FIR high-pass filter to filter out the narrowband disturbance signal added in the early stage. The final data obtained is the sampling result after disturbance processing. The output signal of the ADC sampling chip enters the FIFO pre-trigger memory of the FPGA controller after filtering and framing by the FPGA controller. For the multi-channel sensor data obtained by the ADC sampling chip each time, the FPGA controller compares it with the set threshold value. If the sensor data of a certain channel exceeds the threshold, it is considered that an abnormal vibration event has occurred at the corresponding position. When an abnormal vibration event is detected, a total of 500ms of data before and after the abnormal vibration occurs is stored in the eMMC memory as abnormal vibration data. The FPGA controller uses a positioning method based on the RSSI algorithm to analyze the abnormal vibration data, calculate the position of the abnormal vibration source, and frame the calculated vibration source position, and send it to the host computer through the RS422 transceiver. The steps of the positioning method based on the RSSI algorithm are: S1. Assume that the amplitude decay of abnormal vibration data conforms to the exponential decay model: ， formula middle, Indicates the The amplitude of the signal received by each sensor; Indicates the signal amplitude of the vibration source; Indicates the vibration source to the The distance between the sensors; represents the attenuation coefficient, Determined through testing; S2, known The placement of the sensors is ( ), by analyzing the amplitude of the signals received by multiple sensors and establishing a set of equations, the position and amplitude of the vibration source can be solved; assuming that the position of the vibration source is ( ), according to the amplitude attenuation model in step S1, the vibration source to the The distance between the sensors is expressed as: ， S3, using triangulation method, for the sensors, the position of the vibration source satisfies the formula : ， Expand the formula The nonlinear equation in and convert it into a linear equation: ， Use the vibration source relative to the The position formula of the first sensor minus the position formula of the vibration source relative to the first sensor eliminates and After simplifying, we get: ， Then, for sensors, we can get Linear equations, these equations are written in matrix form: ， formula middle, is the coefficient matrix; where: ， ， ， Finally, the least squares method is used to solve: ， formula middle, yes The transposed matrix of yes The inverse matrix of the solution vector p is the vibration source position ( ).

2. The abnormal vibration monitoring method for an aircraft according to claim 1, characterized in that: The sensor signal transmitter includes a charge-voltage conversion circuit, a filtering circuit, and an amplification and limiting circuit. The input charge signal is first converted into a voltage signal by the charge-voltage conversion circuit. The voltage signal then passes through the filtering circuit to filter out low-frequency interference signals and high-frequency resonant signals. Finally, the filtered voltage signal is amplified and limited by the amplification and limiting circuit to adapt to the input voltage range of the ADC sampling chip.

3. The abnormal vibration monitoring method for an aircraft according to claim 1, characterized in that: The ADC sampling chip includes a 6-bit first-stage ADC module, a 7-bit second-stage ADC module, a DAC module, and an amplifier component. The original analog input signal is first converted into a digital signal by the first-stage ADC module and then converted into a new analog signal by the DAC module. The new analog signal is subtracted from the original analog input signal to obtain the residual signal after the first-stage conversion. The residual signal is gain-adjusted by the amplifier component and then enters the second-stage ADC module for conversion to a digital signal. Finally, the digital signal converted by the first-stage ADC module and the digital signal converted by the second-stage ADC module are added to obtain the final conversion result.

4. The abnormal vibration monitoring method for an aircraft according to claim 1, characterized in that: The threshold value set in the FPGA controller is a vibration acceleration value of 2g.

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