A sampling positioning method for airborne impact synchronous monitoring

Abstract

The present invention belongs to the technical field of impact monitoring of structural components, specifically a sampling and positioning method for synchronous monitoring of airborne impact, which solves the technical problems that the existing airborne impact monitoring system method has poor sampling time synchronization and cannot identify and locate the impact source; the existing health monitoring system can only scan a single structural member and cannot monitor the entire structure at all times. The method described in the present invention first builds an aircraft-mounted impact monitoring device, which includes a measurement module, a signal conditioning module, an AD conversion module, an FPGA control module, an eMMC storage module, an RS422 communication module and a power supply module for powering the entire device; secondly, based on the impact identification algorithm of threshold discrimination and the impact source positioning algorithm based on RSSI+TDOA, the propagation time difference and attenuation characteristics of the impact waveguide signal between each sensor are analyzed, and finally the optimal position of the impact source is obtained.

Description

Technical Field

[0001] The present invention belongs to the technical field of testing methods for structural components, and in particular relates to impact monitoring of structural components, in particular to a sampling and positioning method for airborne synchronous impact monitoring. Background Art

[0002] In recent years, with the annual growth of global air passenger traffic, the number of daily flight takeoffs and landings has exceeded 100,000. This has brought with it severe challenges to aircraft safety. According to incomplete statistics, approximately 480 foreign object strikes occur daily worldwide, of which approximately 2% cause serious damage to the aircraft structure, posing a threat to flight safety. In response to this growing threat, Boeing and Airbus have developed airborne SHM (structural health monitoring) equipment to identify bird strikes during takeoff and landing. Third-party equipment suppliers such as Honeywell have also launched HUMS (Health and Usage Monitoring System) for health monitoring and lifespan management of key aircraft components. Domestically, corresponding monitoring methods have also been proposed for aircraft impact monitoring.

[0003] Dai Yu, Zhang Jie. Multi-channel flexible strain sensing system with autonomous temperature compensation [J]. Sensors and Microsystems, 2024, 43(02):97-100. DOI:10.13873. A multi-channel sensor acquisition and storage device is proposed. Its analog acquisition part adopts a similar "multi-channel matrix switch + ADC alternating sampling" front-end architecture. This type of architecture facilitates the expansion of sensor channels to support a large number of sensor arrays. However, this type of system relies on a multi-channel matrix switch to balance the contradiction between a large number of data channels and a small number of ADC sampling channels. Due to the switching time of the multi-channel matrix switch, the sampling time bases of multiple channels are different. For the impact event recognition system, determining a unified time base is the basic guarantee for subsequent data processing and position recognition. Even if the waiting time of the T / H (sample / hold) stage can be reduced by increasing the ADC sampling rate, the final sampling time error can only be reduced to the microsecond level. In particular, the device described in "Jin Lu, Miao Sien. Design of a Multi-channel High-speed Sampling System Based on FPGA [J]. Electronic Technology, 2014, 43(02): 22-26" uses multiple ADCs for parallel sampling to improve the accuracy of synchronous sampling time. However, due to the presence of the sensor signal front-end processing circuit, any parameter mismatch of the discrete components may cause phase shift in the signal during transmission. Using hardware alone can only adjust the sampling time error of the ADC, but cannot eliminate the error caused by the analog signal during transmission. In particular, considering the deviation in line length during sensor installation and layout, the actual sampling time error between channels is difficult to eliminate, which seriously affects the identification and location of the impact source in the later stage.

[0004] In addition, airborne structural health monitoring systems developed by companies such as Boeing mentioned above all use active monitoring methods. The basic principle is to use active excitation sources such as piezoelectric guided waves and acoustic emission to stimulate structural components, receive signals from sensor arrays, and analyze the signals to detect potential damage in the structural components. However, this method is only suitable for ground maintenance and cannot achieve real-time monitoring. If a foreign object impact occurs during flight, the pilot will not be able to obtain the impact information in a timely manner, which has limited improvement in flight safety. Moreover, only a single structural component can be scanned at a time, and it is impossible to monitor the entire structure at all times, which has significant limitations in practical application. Summary of the Invention

[0005] In order to overcome the technical defects in existing airborne impact monitoring system methods, such as large sampling time errors, which seriously affect the subsequent identification and positioning of impact sources; existing airborne health monitoring systems are unable to perform real-time monitoring and can only scan single structural parts, and are unable to monitor the entire structure throughout the entire period, the present invention provides a sampling and positioning method for airborne impact synchronous monitoring.

[0006] The present invention provides a sampling and positioning method for synchronous monitoring of airborne impacts, and builds an impact monitoring device carried by an aircraft, wherein the impact monitoring device includes a measurement module, a signal conditioning module, an AD conversion module, an FPGA control module, an eMMC storage module, an RS422 communication module, and a power supply module for supplying power to the impact monitoring device as a whole; the measurement module includes a plurality of piezoelectric sensors attached to the surface of the fuselage, wings, and aircraft engine for detecting impact guided waves; when the corresponding structural parts are impacted by the impact source, impact guided waves are generated on the surface of the structural parts, and the piezoelectric sensors can convert the stress signals transmitted by the impact guided waves on the structural parts into charge signals based on the piezoelectric effect; the charge signals output by the measurement module are sequentially transmitted to the FPGA control module through the signal conditioning module and the AD conversion module, and the FPGA control module controls the AD conversion module to convert the measurement module into a charge signal; The multiple piezoelectric sensors in the block are sampled synchronously. The sampled data is filtered and framed inside the FPGA control module and then sent to the FIFO buffer to be triggered. When the signal of a piezoelectric sensor reaches the preset trigger threshold, the FPGA control module intercepts the complete signal of 500ms before and after the impact and stores it in the eMMC storage module as the impact signal to provide support for subsequent impact position analysis and feature extraction. The FPGA control module then uses the positioning algorithm based on TDOA and RSSI to analyze the stored impact signal and calculate the location of the impact source. Finally, the FPGA control module frames the impact time, impact magnitude, and calculated impact source location information and sends it to the onboard control system through the RS422 communication module. The steps of the positioning algorithm based on TDOA and RSSI are as follows:

[0007] S1. First, determine the monitoring area coordinate system and the corresponding coordinates of the piezoelectric sensor according to the placement position of the piezoelectric sensor on the aircraft. Assume The positions of the piezoelectric sensors are , , … ;

[0008] S2, according to the 500ms shock signal obtained by the FPGA control module, extract the shock time and shock amplitude characteristics, and record the sampling time when the amplitude of each piezoelectric sensor exceeds the trigger threshold for the first time as the time when the shock wave reaches the corresponding piezoelectric sensor. The time of each piezoelectric sensor is 、 、 … ; The maximum value of the impact wave received by each piezoelectric sensor is recorded as the impact amplitude, then The impact amplitudes of the piezoelectric sensors are 、 、 … , The maximum impact amplitude among the impact amplitudes corresponding to the piezoelectric sensors is recorded as ; Assume that the propagation speed of the shock wave on the aircraft is The location of the impact source is ;

[0009] S3, TDOA algorithm measures the time difference between the impact wave reaching different piezoelectric sensors, and then combines the position information of the piezoelectric sensor to infer the position of the impact source. Therefore, the distance between each piezoelectric sensor is calculated first. for:

[0010] ;

[0011] formula middle, For the A piezoelectric sensor, It is a piezoelectric sensor;

[0012] No. A piezoelectric sensor and The ideal time difference between the piezoelectric sensors is :

[0013] ;

[0014] The time difference between the actual impact guided wave reaching the i-th piezoelectric sensor and the j-th piezoelectric sensor is: :

[0015] ;

[0016] formula middle, For the shock wave to reach the The actual time of each piezoelectric sensor, The shock wave reaches the The actual time of each piezoelectric sensor;

[0017] The error between the ideal time difference and the actual time difference is:

[0018] ;

[0019] for piezoelectric sensor, and calculate the A piezoelectric sensor and The error between the piezoelectric sensors is calculated, and the total sum of square errors is:

[0020] ;

[0021] S4. Calculate the distance from the impact source to each piezoelectric sensor according to the plane distance formula:

[0022] ;

[0023] The impact source is attenuated due to the damping effect during transmission. According to the RSSI algorithm, the signal amplitude is inversely proportional to the square of the distance, so the error function Based on the above relationship, it is expressed as The difference between the signal strength predicted by the model and the actual measured signal strength at each piezoelectric sensor is the error function The calculation formula is:

[0024] ;

[0025] formula middle, For the The shock amplitude of each piezoelectric sensor; , is the total number of piezoelectric sensors;

[0026] for piezoelectric sensor, use the above steps to calculate its error function , the total sum of squared errors is:

[0027] ;

[0028] S5. Weight the sum of squares of the errors obtained by the TDOA algorithm and the RSSI algorithm according to a certain ratio to obtain the total error sum:

[0029] ;

[0030] formula middle, is the weight of the sum of squared errors obtained by the RSSI algorithm, is the weight of the sum of squared errors obtained by the TDOA algorithm;

[0031] S6. Use nonlinear least squares method to calculate the total error and Perform iterative solution and finally obtain the optimal position of the impact source .

[0032] The method described in the present invention greatly improves the time accuracy of multi-channel synchronous sampling, determines a unified sampling time base for multi-sensor data, and facilitates the analysis of impact events; it monitors and identifies impact events in real time during the entire flight of the aircraft, and can further accurately locate the position of the impact source.

[0033] Preferably, the signal conditioning module includes a signal acquisition and filtering circuit and a The piezoelectric sensor corresponds to A charge-voltage conversion unit, the signal acquisition and filtering processing circuit includes a filtering circuit, an amplifying circuit and a limiting circuit, The charge signal of each piezoelectric sensor is transmitted through the corresponding The charge-voltage conversion unit is converted into a voltage signal. The voltage signal passes through a filtering circuit to remove low-frequency interference and high-frequency resonance signals. The filtered signal is processed by an amplifying circuit and a limiting circuit to obtain a voltage signal that meets the input requirements of the AD conversion module.

[0034] Compared with the existing technology, the technical solution provided by the present invention has the following technical effects: the method described in the present invention utilizes high-precision synchronous sampling technology, an impact identification algorithm based on threshold discrimination, and an impact source positioning algorithm based on RSSI+TDOA to realize the acquisition and storage of aircraft acceleration signals, abnormal impact event identification and reporting, and real-time positioning of the impact source during the entire flight process. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] 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.

[0036] 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.

[0037] Figure 1 This is an overall system block diagram of an aircraft-mounted impact monitoring device according to an embodiment of the present invention;

[0038] Figure 2 Schematic diagram of the phase difference after adjustment by the sampling and positioning method for airborne impact synchronous monitoring in an embodiment of the present invention. DETAILED DESCRIPTION

[0039] 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.

[0040] 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.

[0041] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0042] In one embodiment, Figure 1 As shown, a sampling and positioning method for synchronous monitoring of airborne impact is disclosed. First, an impact monitoring device on an aircraft is built, and the impact monitoring device includes a measurement module, a signal conditioning module, an AD conversion module, an FPGA control module, an eMMC storage module, an RS422 communication module and a power supply module for supplying power to the impact monitoring device as a whole; the measurement module includes a plurality of piezoelectric sensors attached to the surface of the fuselage, wings and aircraft engine for detecting impact guided waves. When the corresponding structural parts are impacted by the impact source, impact guided waves are generated on the surface of the structural parts. The piezoelectric sensors can convert the stress signals transmitted by the impact guided waves on the structural parts into charge signals based on the piezoelectric effect; the charge signals output by the measurement module are sequentially transmitted to the FPGA control module through the signal conditioning module and the AD conversion module. The signal conditioning module includes a signal acquisition and filtering processing circuit and a circuit for detecting and controlling the impact guided waves. The piezoelectric sensor corresponds to A charge-voltage conversion unit, the signal acquisition and filtering processing circuit includes a filtering circuit, an amplifying circuit and a limiting circuit, The charge signal of each piezoelectric sensor is transmitted through the corresponding The charge-voltage conversion unit converts the charge into a voltage signal. The voltage signal passes through a filtering circuit to remove low-frequency interference and high-frequency resonant signals. The filtered signal is processed by an amplification circuit and a limiting circuit to obtain a voltage signal that meets the input requirements of the AD conversion module. The AD conversion module consists of multiple eight-channel analog-to-digital converters cascaded with their peripheral circuits. Its interior consists of an independent 16-bit resolution SAR ADC and eight individually controlled T / H components. All eight T / H components are controlled by a unified conversion start signal, CONVST. In this architecture, the T / H circuit samples and holds the input signal at the same time, then sequentially feeds it into the ADC for conversion. The FPGA controller, as the system's core control module, manages the entire sampling, storage, analysis, and transmission process. The FPGA control module controls the AD conversion module to synchronously sample the measurement module's multiple piezoelectric sensors. The sampled data is filtered and framed within the FPGA control module before being sent to the trigger-ready FIFO buffer. When the charge signal of a piezoelectric sensor reaches the preset trigger threshold, the FPGA control module intercepts the complete signal, including pre-trigger data, for 500 ms before and after the impact, and stores it as the impact signal in the eMMC storage module to support subsequent impact location analysis and feature extraction. The FPGA control module then uses a positioning algorithm based on TDOA and RSSI to analyze the stored impact signal and calculate the impact source location. Finally, the FPGA control module frames the impact time, impact magnitude, and calculated impact source location information and transmits it to the onboard control system via the RS422 communication module. The steps of the TDOA and RSSI-based positioning algorithm are as follows:

[0043] S1. First, determine the monitoring area coordinate system and the corresponding coordinates of the piezoelectric sensor according to the placement position of the piezoelectric sensor on the aircraft. Assume The positions of the piezoelectric sensors are , , … ;

[0044] S2, according to the 500ms shock signal obtained by the FPGA control module, extract the shock time and shock amplitude characteristics, and record the sampling time when the amplitude of each piezoelectric sensor exceeds the trigger threshold for the first time as the time when the shock wave reaches the corresponding piezoelectric sensor. The time of each piezoelectric sensor is 、 、 … ; The maximum value of the impact wave received by each piezoelectric sensor is recorded as the impact amplitude, then The impact amplitudes of the piezoelectric sensors are 、 、 … , The maximum impact amplitude among the impact amplitudes corresponding to the piezoelectric sensors is recorded as ; Assume that the propagation speed of the shock wave on the aircraft is The location of the impact source is ;

[0045] S3, TDOA algorithm measures the time difference between the impact wave reaching different piezoelectric sensors, and then combines the position information of the piezoelectric sensor to infer the position of the impact source. Therefore, the distance between each piezoelectric sensor is calculated first. for:

[0046] ;

[0047] formula middle, For the A piezoelectric sensor, It is a piezoelectric sensor;

[0048] No. A piezoelectric sensor and The ideal time difference between the piezoelectric sensors is :

[0049] ;

[0050] The time difference between the actual impact guided wave reaching the i-th piezoelectric sensor and the j-th piezoelectric sensor is: :

[0051] ;

[0052] formula middle, For the shock wave to reach the The actual time of each piezoelectric sensor, The shock wave reaches the The actual time of each piezoelectric sensor;

[0053] The error between the ideal time difference and the actual time difference is:

[0054] ;

[0055] for piezoelectric sensor, and calculate the A piezoelectric sensor and The error between the piezoelectric sensors is calculated, and the total sum of square errors is:

[0056] ;

[0057] S4. Calculate the distance from the impact source to each piezoelectric sensor according to the plane distance formula:

[0058] ;

[0059] The impact source is attenuated due to the damping effect during transmission. According to the RSSI algorithm, the signal amplitude is inversely proportional to the square of the distance, so the error function Based on the above relationship, it is expressed as The difference between the signal strength predicted by the model and the actual measured signal strength at each piezoelectric sensor is the error function The calculation formula is:

[0060] ;

[0061] formula middle, For the The shock amplitude of each piezoelectric sensor; , is the total number of piezoelectric sensors;

[0062] for piezoelectric sensor, use the above steps to calculate its error function , the total sum of squared errors is:

[0063] ;

[0064] S5. Weight the sum of squares of the errors obtained by the TDOA algorithm and the RSSI algorithm according to a certain ratio to obtain the total error sum:

[0065] ;

[0066] formula middle, is the weight of the sum of squared errors obtained by the RSSI algorithm, is the weight of the sum of squared errors obtained by the TDOA algorithm;

[0067] S6. Use nonlinear least squares method to calculate the total error and Perform iterative solution and finally obtain the optimal position of the impact source .

[0068] Specifically, in order to reduce the sampling time error between multiple AD conversion modules, the AD conversion module and the main control FPGA are connected in parallel to use a common trigger signal, and the signal line length, routing method and impedance are kept as consistent as possible to ensure that the delay of the trigger signal reaching each device is consistent. In addition, in order to solve the phase error caused by the transmission line length and the front-end filtering circuit, a delay correction module is added to the FPGA, and a programmable delay line based on FIFO is used to dynamically adjust the sampling time difference between each channel. The sampling data stream of each channel is written into an independent FIFO module using a synchronous clock, and then the data of each channel is read separately using a read pointer with an offset address, and written into the new FIFO to complete the data offset correction process. For details, see Figure 2 The offset address here is the number of samples required to delay each channel, which is usually determined by measuring the phase difference between signals in different channels. By setting the read pointer offset value of each channel in the delay correction module, it is possible to ensure that the signal of each channel is aligned on the time axis, thereby eliminating the phase error caused by hardware differences. The above hardware design + software correction method greatly reduces the sampling error between multiple channels. At an 800K sampling rate, the sampling time error of multiple channels is only a few nanoseconds, laying the foundation for the subsequent time-based impact location method.

[0069] Shock events typically manifest as short, high-amplitude, high-frequency signals, posing a potential threat to aircraft structures and system performance. Monitoring and recording shock events is crucial for assessing aircraft health. To effectively identify and locate abnormal shock events occurring on the aircraft, this invention innovatively proposes a shock identification algorithm based on threshold discrimination and a shock location algorithm based on TDOA and RSSI.

[0070] The core concept of the threshold-based shock recognition algorithm is to set a predetermined threshold. When the signal from a piezoelectric sensor exceeds this threshold, the system determines that a shock event has occurred. During aircraft operation, data from the multi-channel piezoelectric sensors is collected in real time, initially processed, and temporarily stored in a FIFO pre-trigger memory in a circular manner. After each sampling, the system compares the data from each channel against the threshold. If the signal from a channel exceeds the threshold, a shock event is detected.

[0071] After parsing the raw sampled data and extracting impact events, the next step is to estimate the impact source's location. This process aims to calculate the specific impact location by analyzing the propagation characteristics of the impact waveguide signal, combined with information about the piezoelectric sensor layout and the aircraft structure. To this end, this invention innovatively combines TDOA and RSSI positioning algorithms. By analyzing the propagation time differences and attenuation characteristics of the impact waveguide signal between sensors, the impact source location is comprehensively calculated.

[0072] The method described in the present invention combines the error functions of the TDOA algorithm and the RSSI algorithm, and assigns different weights according to the characteristics of the monitoring area (TDOA weight prevails when the monitoring area is large and the region is complex; RSSI weight prevails when the monitoring area is small and high-precision monitoring is required). This can achieve more accurate positioning under different environmental and distance conditions.

[0073] The method of the present invention, by taking the above-mentioned technical measures, realizes high-precision synchronous sampling of multi-channel piezoelectric sensor signals through a hardware + software correction method, and can comprehensively monitor and record the impact conditions of the aircraft from takeoff to landing. The system collects impact data from key parts of the aircraft in real time, frames the collected data and stores it locally. During the data processing process, a threshold-based discrimination algorithm is used to identify impact events. In order to further locate the impact source, the TDOA algorithm and the RSSI algorithm are combined to analyze multiple sensor signals to accurately locate the impact source, providing support for aircraft safety monitoring and fault diagnosis.

[0074] 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 sampling and positioning method for airborne impact synchronous monitoring, characterized in that: An aircraft-mounted impact monitoring device is constructed, which includes a measurement module, a signal conditioning module, an AD conversion module, an FPGA control module, an eMMC storage module, an RS422 communication module, and a power supply module for supplying power to the entire impact monitoring device; the measurement module includes multiple piezoelectric sensors attached to the surface of the fuselage, wings, and aircraft engine for detecting shock guided waves. When the corresponding structural parts are impacted by the impact source, shock guided waves are generated on the surface of the structural parts. The piezoelectric sensors can convert the stress signals transmitted by the shock guided waves on the structural parts into charge signals based on the piezoelectric effect; the charge signals output by the measurement module are sequentially transmitted to the FPGA control module through the signal conditioning module and the AD conversion module, and the FPGA control module controls the AD conversion module to synchronously sample the multiple piezoelectric sensors of the measurement module. Similarly, the sampled data is filtered and framed within the FPGA control module and then sent to the FIFO buffer to be triggered. When the charge signal of a piezoelectric sensor reaches the preset trigger threshold, the FPGA control module intercepts the complete signal of 500ms before and after the impact and stores it in the eMMC storage module as the impact signal to provide support for subsequent impact position analysis and feature extraction. The FPGA control module then uses the positioning algorithm based on TDOA and RSSI to analyze the stored impact signal and calculate the location of the impact source. Finally, the FPGA control module frames the impact time, impact magnitude, and calculated impact source location information and sends it to the onboard control system through the RS422 communication module. The steps of the positioning algorithm based on TDOA and RSSI are as follows: S1. First, determine the monitoring area coordinate system and the coordinates corresponding to the shock wave sensor according to the placement position of the shock wave sensor on the aircraft. Assume The locations of the shock wave sensors are , , … ; S2, according to the 500ms shock signal obtained by the FPGA control module, extract the shock time and shock amplitude characteristics, and record the sampling time when the amplitude of each piezoelectric sensor exceeds the trigger threshold for the first time as the time when the shock wave reaches the corresponding piezoelectric sensor. The time of each piezoelectric sensor is 、 、 … ; The maximum value of the impact wave received by each piezoelectric sensor is recorded as the impact amplitude, then The impact amplitudes of the piezoelectric sensors are 、 、 … , The maximum impact amplitude among the impact amplitudes corresponding to the piezoelectric sensors is recorded as ; Assume that the propagation speed of the shock wave on the aircraft is The location of the impact source is ; S3, TDOA algorithm measures the time difference between the impact wave reaching different piezoelectric sensors, and then combines the position information of the piezoelectric sensor to infer the position of the impact source. Therefore, the distance between each piezoelectric sensor is calculated first. for: ； formula middle, For the A piezoelectric sensor, It is a piezoelectric sensor; No. A piezoelectric sensor and The ideal time difference between the piezoelectric sensors is : ； The time difference between the actual impact guided wave reaching the i-th piezoelectric sensor and the j-th piezoelectric sensor is: : ； formula middle, For the shock wave to reach the The actual time of each piezoelectric sensor, The shock wave reaches the The actual time of each piezoelectric sensor; The error between the ideal time difference and the actual time difference is: ； for piezoelectric sensor, and calculate the A piezoelectric sensor and The error between the piezoelectric sensors is calculated, and the total sum of square errors is: ； S4. Calculate the distance from the impact source to each piezoelectric sensor according to the plane distance formula: ； The impact source is attenuated due to the damping effect during transmission. According to the RSSI algorithm, the signal amplitude is inversely proportional to the square of the distance, so the error function Based on the following relationship, it is expressed as The difference between the signal strength predicted by the model and the actual measured signal strength at each piezoelectric sensor is the error function The calculation formula is: ； formula middle, For the The shock amplitude of each piezoelectric sensor; , is the total number of piezoelectric sensors; for piezoelectric sensor, use the above steps to calculate its error function , the total sum of squared errors is: ； S5. Weight the sum of squares of the errors obtained by the TDOA algorithm and the RSSI algorithm according to a certain ratio to obtain the total error sum: ； formula middle, is the weight of the sum of squared errors obtained by the RSSI algorithm, is the weight of the sum of squared errors obtained by the TDOA algorithm; S6. Use nonlinear least squares method to calculate the total error and Perform iterative solution and finally obtain the optimal position of the impact source .

2. The sampling and positioning method for airborne impact synchronous monitoring according to claim 1, characterized in that: The signal conditioning module includes signal acquisition, filtering and processing circuits and The piezoelectric sensor corresponds to A charge-voltage conversion unit, the signal acquisition and filtering processing circuit includes a filtering circuit, an amplifying circuit and a limiting circuit, The charge signal of each piezoelectric sensor is transmitted through the corresponding The charge-voltage conversion unit is converted into a voltage signal. The voltage signal passes through a filtering circuit to remove low-frequency interference and high-frequency resonance signals. The filtered signal is processed by an amplifying circuit and a limiting circuit to obtain a voltage signal that meets the input requirements of the AD conversion module.

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