Sampling positioning method for airborne impact synchronous monitoringTechnical Field
The invention belongs to the technical field of testing methods of structural components, in particular to an impact monitoring method of the structural components, and particularly relates to a sampling and positioning method for airborne impact synchronous monitoring.
Background
In recent years, as the global aviation passenger traffic increases year by year, the number of daily flights taking off and landing breaks through 10 ten thousand frames. With the serious problem of safety of the aircraft. With incomplete statistics, about 480 foreign object crashes occur daily worldwide, with about 2% of crashes causing serious damage to the aircraft structure, which in turn poses a threat to flight safety. Against the increasingly serious threat, boeing and air passenger companies have developed onboard SHM (structural health monitoring) equipment for bird strike recognition during take-off and landing phases, and third party equipment suppliers such as Honeywell corporation have also purposely introduced a HUMS (HEALTH AND Usage Monitoring System) system for health monitoring and life management of critical components of aircraft. Corresponding monitoring methods are also provided for the field of aircraft impact monitoring in China.
A multichannel sensor sampling device is proposed in a multi-channel flexible strain sensing system [ J ]. Sensor and microsystem with autonomous temperature compensation [ 2024,43 (02): 97-100.DOI:10.13873 ], wherein a similar front-end architecture of multi-channel matrix switch and ADC alternate sampling is adopted in an analog acquisition part of the multichannel sensor sampling device, and the architecture is convenient for expanding sensor channels so as to support the array of a huge number of sensors. However, such systems rely on multi-channel matrix switches to balance the contradiction between a large number of data channels and fewer ADC sampling channels, with the sampling time base being different between the multiple channels due to the switching time of the multi-channel matrix switch. For the impact event recognition system, determining a unified time base point is a basic guarantee for performing post-data processing and position recognition, and even if the waiting time of a T/H (sample/hold) stage can be reduced by a method of increasing the sampling rate of the ADC, the final sampling time error can be reduced to a subtle level only. In particular, for example, jin Lu, miao Saien, the FPGA-based multi-channel high-speed sampling system design [ J ]. Electronic technology, 2014,43 (02): 22-26), uses multiple ADCs to sample in parallel to improve the synchronous sampling time accuracy, but due to the existence of a front-end processing circuit of a sensor signal, the phase shift of the signal may occur due to the parameter mismatch of any discrete component, and only the sampling time error of the ADC can be adjusted by using a hardware method, so that the error caused by the analog signal in the transmission process cannot be eliminated. Especially, the deviation of the line length during the installation and layout of the sensor is considered, the actual sampling time error among the channels is difficult to eliminate, and the later identification and positioning of the impact source are seriously influenced.
In addition, the airborne structure health monitoring systems developed by the companies such as boeing and the like all use an active monitoring method, and the basic principle is that an active excitation source such as piezoelectric guided wave and acoustic emission is used for exciting a structural member, a sensor array receives signals, and potential damage in the structural member is detected by analyzing the signals. However, the method is only suitable for ground maintenance and cannot realize real-time monitoring. If foreign matter impact occurs in the flight process, a driver cannot acquire impact information in time, the flight safety is improved only by scanning a single structural member at a time, the whole structure cannot be monitored for a whole period, and the method has a large limit in practical application.
Disclosure of Invention
The invention provides a sampling and positioning method for synchronous monitoring of airborne impact, which aims to overcome the technical defects that the existing airborne impact monitoring system method has larger sampling time error and seriously affects the identification and positioning of an impact source in the later period, the existing airborne health monitoring system cannot monitor in real time, only can scan a single structural member and cannot monitor the whole structure in full time.
The invention provides a sampling and positioning method for airborne impact synchronous monitoring, which comprises the steps of constructing an airborne impact monitoring device of an aircraft, wherein the impact monitoring device comprises a measuring module, a signal conditioning module, an AD conversion module, an FPGA control module, an eMMC storage module, an RS422 communication module and a power module for integrally supplying power to the impact monitoring device; the measuring module comprises a plurality of piezoelectric sensors which are attached to the surfaces of a fuselage, wings and an aircraft engine and are used for detecting impact guided waves, after the corresponding structural member is impacted by an impact source, the surface of the structural member generates the impact guided waves, the piezoelectric sensors can convert stress signals transmitted by the impact guided waves on the structural member into charge signals based on piezoelectric effect, the charge signals output by the measuring module are sequentially transmitted to the FPGA control module through the signal conditioning module and the AD conversion module, the FPGA control module controls the AD conversion module to synchronously sample the piezoelectric sensors of the measuring module, data obtained through sampling are filtered and framed in the FPGA control module and then are sent to a FIFO buffer to be triggered, when the signal of one piezoelectric sensor reaches a preset trigger threshold, the FPGA control module intercepts complete signals which are 500ms in total before and after impact and is used as impact signals to be stored in the eMMC storage module, support is provided for subsequent impact position analysis and feature extraction, the FPGA control module analyzes and calculates the position of the impact source by using a positioning algorithm based on TDOA and RSSI, finally the FPGA control module carries out frame formation on the time and impact magnitude of occurrence and the calculated impact source position information obtained through RS422, and the RSSI is sent to the TDOA control module to the system based on the positioning algorithm:
S1, firstly, determining a coordinate system of a monitoring area and coordinates corresponding to the piezoelectric sensors according to the arrangement positions of the piezoelectric sensors on an aircraft, and assuming thatThe positions of the piezoelectric sensors are respectively,,...;
S2, extracting impact time and impact amplitude characteristics according to the 500ms impact signals acquired by the FPGA control module, and recording the sampling time when the amplitude of each piezoelectric sensor exceeds a trigger threshold for the first time as the time when the impact guided wave reaches the corresponding piezoelectric sensor, wherein the impact guided wave reachesThe time of each piezoelectric sensor is respectively、、...And recording the maximum value of the impact guided wave received by each piezoelectric sensor as the impact amplitudeThe impact amplitude of each piezoelectric sensor is respectively、、...,The maximum impact amplitude value in the impact amplitudes corresponding to the piezoelectric sensors is recorded asAssume that the propagation speed of the impact guided wave on the aircraft isThe position of the impact source is;
S3, the TDOA algorithm calculates the position of the impact source by measuring the time difference of the impact guided wave reaching different piezoelectric sensors and combining the position information of the piezoelectric sensors, so that the distance between the piezoelectric sensors is calculated firstlyThe method comprises the following steps:
;
Formula (VI)In the process, theIs the firstThe number of piezoelectric sensors is such that,Is the firstA piezoelectric sensor;
First, thePiezoelectric sensor and the firstThe ideal time difference between the piezoelectric sensors is:
;
The time difference between the actual impact guided wave reaching the ith piezoelectric sensor and the jth piezoelectric sensor is:
;
Formula (VI)In the process, theTo the first for the impact guided waveThe actual time of the individual piezoelectric sensors,Impact guided wave reaches the firstActual time of the individual piezoelectric sensors;
the error of the ideal time difference from the actual time difference is:
;
For the followingA piezoelectric sensor for circularly calculating the first stepPiezoelectric sensor and the firstThe error between the piezoelectric sensors, the sum of squares of the total error is obtained as:
;
S4, calculating the distance from the impact source to each piezoelectric sensor according to a plane distance formula:
;
Attenuation of the impact source occurs due to damping effect in the transmission process, and according to the RSSI algorithm, the signal amplitude is inversely proportional to the square of the distance, and then the error function is obtainedBased on the above relation, expressed as the firstDifference between model predicted signal strength and actual measured signal strength at individual piezoelectric sensors, error functionThe calculation formula of (2) is as follows:
;
Formula (VI)In the process, theIs the firstImpact amplitude of the individual piezoelectric sensors;, is the total number of piezoelectric sensors;
For the followingA piezoelectric sensor for circularly calculating its error function by using the above stepsThe total error sum of squares is obtained as:
;
s5, weighting and summing the error square sum obtained by the TDOA algorithm and the RSSI algorithm according to a certain proportion to obtain a total error sum:
;
Formula (VI)In the process, theThe weight of the sum of squares of errors obtained for the RSSI algorithm,The weight of the error square sum obtained by the TDOA algorithm;
S6, using a nonlinear least square method to sum total errorsPerforming iterative solution to finally obtain the optimal position of the impact source。
The method greatly improves the multi-channel synchronous sampling time precision, determines a uniform sampling time base for multi-sensor data, is convenient for analyzing the impact event, monitors and identifies the impact event in real time in the whole flight process of the aircraft, and can further accurately position the impact source position.
Preferably, the signal conditioning module comprises a signal acquisition filter processing circuit and a signal processing circuitCorresponding to the piezoelectric sensorsThe charge-voltage conversion unit, the signal acquisition filtering processing circuit comprises a filtering circuit, an amplifying circuit and a limiting circuit,Charge signal passing through corresponding piezoelectric sensorsThe charge-voltage conversion units are converted into voltage signals, the voltage signals pass through a filter circuit to remove low-frequency interference and high-frequency resonance signals, and the filtered signals are processed through an amplifying circuit and a limiting circuit to obtain the voltage signals meeting the input requirements of the AD conversion module.
Compared with the prior art, the method has the technical effects that the method realizes the collection and storage of the body acceleration signals, the identification report of abnormal impact events and the real-time positioning of the impact source position in the whole flight process by utilizing a high-precision synchronous sampling technology, an impact identification algorithm based on threshold value discrimination and an impact source positioning algorithm based on RSSI+TDOA.
Drawings
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.
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is an overall system block diagram of an impact monitoring device on-board an aircraft in accordance with an embodiment of the present invention;
fig. 2 is a schematic diagram of a phase difference after adjustment by the sampling positioning method for on-board impact synchronous monitoring according to an embodiment of the present invention.
Detailed Description
In order that the above objects, features and advantages of the invention will be more clearly understood, a further description of the invention will be made. It should be noted that, without conflict, the embodiments of the present invention and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced otherwise than as described herein, and it is apparent that the embodiments in the specification are only some, rather than all, of the embodiments of the present invention.
Specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
In one embodiment, as shown in FIG. 1, a sampling and positioning method for on-board impact synchronous monitoring is disclosed, firstly, an on-board impact monitoring device of an aircraft is built, the impact monitoring device comprises 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 integrally supplying power to the impact monitoring device, the measurement module comprises a plurality of piezoelectric sensors which are attached to the surfaces of a fuselage, wings and an aircraft engine and are used for detecting impact guided waves, after the corresponding structural member is impacted by an impact source, the impact guided waves are generated on the surface of the structural member, the piezoelectric sensors convert stress signals transmitted by the impact guided waves on the structural member into charge signals based on 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 signal conditioning module comprises a signal acquisition and filtering processing circuit and a signal processing module and an interfaceCorresponding to the piezoelectric sensorsThe charge-voltage conversion unit, the signal acquisition filtering processing circuit comprises a filtering circuit, an amplifying circuit and a limiting circuit,Charge signal passing through corresponding piezoelectric sensorsThe charge-voltage conversion units are converted into voltage signals, the voltage signals are filtered by the filter circuit to remove low-frequency interference and high-frequency resonance signals, the filtered signals are processed by the amplifying circuit and the limiting circuit to obtain voltage signals meeting the input requirements of the AD conversion module, the AD conversion module is formed by cascading a plurality of eight-channel analog-to-digital converters and peripheral circuits of the eight-channel analog-to-digital converters, and the AD conversion module is internally formed by an independent 16-bit resolution SAR type ADC and eight independently controlled T/H components. All eight T/H assemblies are controlled by a unified conversion starting signal CONVST, a T/H circuit under the framework samples and holds input signals at the same moment and then sequentially sends the input signals to an ADC for conversion, an FPGA controller is used as a core control module of the system and is responsible for managing the whole sampling, storage, analysis and sending processes, an AD conversion module is controlled by the FPGA control module to synchronously sample a plurality of piezoelectric sensors of a measuring module, sampled data are sent to a FIFO buffer to be triggered after being filtered and framed in the FPGA control module, when the charge signals of one piezoelectric sensor reach a preset trigger threshold, the FPGA control module intercepts complete signals which are 500ms before and after the impact and comprise pre-trigger data and are used as impact signals to be stored in an eMMC storage module to provide support for subsequent impact position analysis and feature extraction, the FPGA control module utilizes a positioning algorithm based on TDOA and RSSI to analyze and calculate the position of an impact source, finally the FPGA control module frames the time, magnitude and the calculated impact source position information of the impact occurrence, and sends the obtained impact source position information to an RSSI (signal) on an RS422 communication module to an RSSI (signal to an RSSI) control system, and the FPGA control module is based on the positioning algorithm:
S1, firstly, determining a coordinate system of a monitoring area and coordinates corresponding to the piezoelectric sensors according to the arrangement positions of the piezoelectric sensors on an aircraft, and assuming thatThe positions of the piezoelectric sensors are respectively,,...;
S2, extracting impact time and impact amplitude characteristics according to the 500ms impact signals acquired by the FPGA control module, and recording the sampling time when the amplitude of each piezoelectric sensor exceeds a trigger threshold for the first time as the time when the impact guided wave reaches the corresponding piezoelectric sensor, wherein the impact guided wave reachesThe time of each piezoelectric sensor is respectively、、...And recording the maximum value of the impact guided wave received by each piezoelectric sensor as the impact amplitudeThe impact amplitude of each piezoelectric sensor is respectively、、...,The maximum impact amplitude value in the impact amplitudes corresponding to the piezoelectric sensors is recorded asAssume that the propagation speed of the impact guided wave on the aircraft isThe position of the impact source is;
S3, the TDOA algorithm calculates the position of the impact source by measuring the time difference of the impact guided wave reaching different piezoelectric sensors and combining the position information of the piezoelectric sensors, so that the distance between the piezoelectric sensors is calculated firstlyThe method comprises the following steps:
;
Formula (VI)In the process, theIs the firstThe number of piezoelectric sensors is such that,Is the firstA piezoelectric sensor;
First, thePiezoelectric sensor and the firstThe ideal time difference between the piezoelectric sensors is:
;
The time difference between the actual impact guided wave reaching the ith piezoelectric sensor and the jth piezoelectric sensor is:
;
Formula (VI)In the process, theTo the first for the impact guided waveThe actual time of the individual piezoelectric sensors,Impact guided wave reaches the firstActual time of the individual piezoelectric sensors;
the error of the ideal time difference from the actual time difference is:
;
For the followingA piezoelectric sensor for circularly calculating the first stepPiezoelectric sensor and the firstThe error between the piezoelectric sensors, the sum of squares of the total error is obtained as:
;
S4, calculating the distance from the impact source to each piezoelectric sensor according to a plane distance formula:
;
Attenuation of the impact source occurs due to damping effect in the transmission process, and according to the RSSI algorithm, the signal amplitude is inversely proportional to the square of the distance, and then the error function is obtainedBased on the above relation, expressed as the firstDifference between model predicted signal strength and actual measured signal strength at individual piezoelectric sensors, error functionThe calculation formula of (2) is as follows:
;
Formula (VI)In the process, theIs the firstImpact amplitude of the individual piezoelectric sensors;, is the total number of piezoelectric sensors;
For the followingA piezoelectric sensor for circularly calculating its error function by using the above stepsThe total error sum of squares is obtained as:
;
s5, weighting and summing the error square sum obtained by the TDOA algorithm and the RSSI algorithm according to a certain proportion to obtain a total error sum:
;
Formula (VI)In the process, theThe weight of the sum of squares of errors obtained for the RSSI algorithm,The weight of the error square sum obtained by the TDOA algorithm;
S6, using a nonlinear least square method to sum total errorsPerforming iterative solution to finally obtain the optimal position of the impact source。
Specifically, in order to reduce sampling time errors among a plurality of AD conversion modules, the AD conversion modules and the main control FPGA are connected in parallel to use a trigger signal together, so that the length, the wiring mode and the impedance of a signal line are kept as consistent as possible, and the delay of the trigger signal reaching each device is ensured to be consistent. In addition, in order to solve the phase error caused by the length of the transmission cable and the front-end filter circuit, a delay correction module is added in the FPGA, and the sampling time difference between all channels is dynamically adjusted by using a programmable delay line based on the FIFO. The sampled data stream of each channel is written into an independent FIFO module by using a synchronous clock, then the data of each channel is respectively read by using a read pointer with an offset address, and is written into a new FIFO, so that the data offset correction process is completed, and the data offset correction process is shown in fig. 2 in detail. The offset address here is the number of samples of the delay required for each channel, typically determined by measuring the phase difference of the signals of the different channels. By setting the read pointer offset values for the channels in the delay correction module, it is possible to ensure that the signals of each channel are aligned on the time axis, thereby eliminating phase errors caused by hardware differences. The hardware design and software correction method greatly reduces sampling errors among multiple channels, and the sampling time errors of the multiple channels are only a few nanoseconds at the sampling rate of 800K, so that a foundation is laid for a later time-based impact positioning method.
Impact events are typically represented as high-amplitude, high-frequency signals for short periods of time, which pose a potential threat to the structural and system performance of the aircraft, and monitoring and recording impact events is critical to assessing aircraft health. In order to effectively identify an abnormal impact event occurring on the fuselage, the impact event is then located. The invention provides a new impact recognition algorithm based on threshold discrimination and an impact positioning algorithm based on TDOA+RSSI.
The key idea of the impact recognition algorithm based on threshold discrimination is that by setting a preset threshold value, when the signal of a certain piezoelectric sensor exceeds the threshold value, the system determines that an impact event occurs. In the running process of the aircraft, the data of the multi-channel piezoelectric sensor are collected in real time and subjected to preliminary processing, and are temporarily stored in the FIFO pre-trigger memory in a circulating storage mode. After each sampling, the system compares the data of each channel with the threshold value one by one, and if a certain channel signal exceeds the threshold value, the system triggers the judgment of the impact event.
After the analysis of the raw sample data is completed and the impact event is extracted, the next step is to estimate the location of the impact source. This process aims to calculate the specific location where the impact occurs by analyzing the propagation characteristics of the impact guided wave signal, in combination with the piezoelectric sensor layout and aircraft structural information. Therefore, a positioning algorithm combining TDOA and RSSI is created, and the impact source position is comprehensively calculated by analyzing the propagation time difference and attenuation characteristic of the impact guided wave signals among the sensors.
The method combines the error functions of the TDOA algorithm and the RSSI algorithm, gives different weights according to the characteristics of the monitored area (the TDOA weight is dominant when the monitored area is large and the RSSI weight is dominant when the monitored area is small and high-precision monitoring is required), and can realize more accurate positioning under different environments and distance conditions.
By adopting the technical measures, the method realizes high-precision synchronous sampling of the signals of the multi-channel piezoelectric sensor by a hardware and software correction method, and can comprehensively monitor and record the impact condition of the whole process from take-off to landing of the aircraft. The system collects impact data of key parts of the aircraft in real time, and frames and locally stores the collected data. In the data processing process, a threshold-based discrimination algorithm is adopted to identify the impact event. In order to further position the impact source, the TDOA algorithm and the RSSI algorithm are combined, the impact source position is accurately positioned through analysis of a plurality of sensor signals, and support is provided for safety monitoring and fault diagnosis of the aircraft.
The foregoing is only a specific embodiment of the invention to enable those skilled in the art to understand or practice the invention. Although the foregoing embodiments have been described in detail, those skilled in the art will appreciate that modifications may be made to the embodiments described above, or equivalents may be substituted for some or all of the features thereof, without departing from the spirit and scope of the embodiments, and it is intended to cover the scope of the claims.