Method and system for automatic detection of aircraft control surfaces based on virtual instrument and matrix switching

Abstract

The application discloses a kind of aircraft rudder surface automatic detection method and system based on virtual instrument and matrix switching, it is related to rudder detection technical field.The aircraft rudder surface automatic detection method and system based on virtual instrument and matrix switching, comprising the following steps: S1, obtain rudder surface actuator response data, and pretreat rudder surface actuator response data;S2, drive relay to realize channel switching, and evaluate the stability degree before and after relay switching, screen stable sampling period;S3, identify the effective response starting point and response end point of each channel, calculate each component index in response section, and construct rudder surface actuator response characteristic vector;S4, evaluate the deviation degree between current response behavior and ideal state, identify abnormal response state, generate channel level response behavior label and form classification result by summarizing.Solve the problem that transient jump caused by relay switching is not isolated by time window, leading to displacement response curve initial section misjudgment.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of rudder detection, in particular to an airplane rudder surface automatic detection method and system based on a virtual instrument and a matrix switch. BACKGROUND

[0002] As an important electrically driven actuator in the flight control system, the rudder surface actuator is responsible for fine adjustment of the flight attitude, and its performance directly affects the response accuracy and system stability of the aircraft. In actual engineering, comprehensive testing and feature analysis of the response behavior of the rudder surface actuator are key links for system design verification and fault prediction. In order to improve the testing efficiency, a relay matrix signal switching structure based on a virtual instrument platform is usually used, combined with a high-frequency excitation signal output module, under the coordination of an FPGA control unit, to apply adjustable frequency sinusoidal control voltage to multiple actuator samples or test channels in turn, so as to realize dynamic response characteristic acquisition of a multi-channel rudder surface control system.

[0003] However, during the channel switching process, the relay contact is prone to produce a micro-arc effect at the moment of conduction, which causes the control voltage to be lifted or the waveform to be distorted for a short time, thereby causing the initial segment of the response data to jump, which is manifested as the displacement response starting too early or the response drifting and distorting. The existing test system generally lacks a time window isolation and data stability verification mechanism for such relay switching disturbance, and cannot eliminate or determine the unstable response when the excitation signal is just connected, which easily causes problems such as misidentification of the response starting point and misjudgment of the disturbance state.

[0004] In addition, the actuator has complex nonlinear dynamic response behavior during operation, including voltage and displacement hysteresis, feedback delay, driving current fluctuation and mechanical response overshoot, and these multi-dimensional coupling characteristics are more pronounced under high-frequency excitation conditions. The traditional method relies on manual experience point selection or static threshold analysis of a single physical quantity, lacks joint modeling capability for dynamic processes, and is difficult to achieve accurate identification and classification statistics of the response behavior.

[0005] Especially in the face of complex scenarios such as multi-frequency excitation, continuous switching and parallel channel collaborative testing, how to extract response features with stable reference value from multi-source dynamic data, construct a standard response segment, and accurately determine the response starting point and the response ending point is a technical bottleneck that the existing system cannot overcome. At the same time, abnormal response states usually show coordinated deviation of multi-dimensional signals, and without a unified evaluation model and feature vector construction method, it is difficult to realize automatic classification of abnormal states and generation of channel-level behavior labels, further limiting the data intelligent processing capability and efficient discrimination capability of the test system in the engineering application of the rudder surface control system.

[0006] Therefore, in view of the above problems, an airplane rudder surface automatic detection method and system based on a virtual instrument and a matrix switch are urgently needed. SUMMARY

[0007] PROBLEMS TO BE SOLVED

[0008] In view of the deficiencies in the prior art, the present application provides an aircraft control surface automatic detection method and system based on virtual instruments and matrix switching, which solves the problem of misjudgment of the initial displacement response curve caused by the transient jump of relay switching not being isolated by the time window.

[0009] TECHNICAL SCHEME

[0010] To achieve the above object, the present application is implemented by the following technical scheme: an aircraft control surface automatic detection method and system based on virtual instruments and matrix switching, comprising the following steps: S1, full-process dynamic acquisition of the control surface actuator operation is performed to obtain control surface actuator response data, and the control surface actuator response data is subjected to time axis repositioning, dynamic denoising, phase compensation and scale unification; S2, continuous control excitation signals are generated based on the pretreated control surface actuator response data, relays are driven to realize channel switching, and the stability before and after relay switching is evaluated to screen stable sampling periods and construct stable response data sets; S3, candidate response starting points are screened based on the stable response data sets, and effective response starting points and response ending points of each channel are identified, component indicators in the response section are calculated, and control surface actuator response feature vectors are constructed; S4, the response feature vectors are extracted, the deviation between the current response behavior and the ideal state is evaluated, abnormal response states are identified based on the evaluation results, channel-level response behavior labels are generated, and classification results are formed by summarizing.

[0011] Further, the specific steps of full-process dynamic acquisition of the control surface actuator operation, obtaining control surface actuator response data, and time axis repositioning, dynamic denoising, phase compensation and scale unification of the control surface actuator response data are as follows: full-process dynamic acquisition of the control surface actuator operation is performed to obtain control surface actuator response data, the control surface actuator response data including control excitation voltage, actuator feedback voltage, actuator mechanical displacement, actuator current, excitation frequency, control voltage phase angle, and feedback voltage phase angle; the control surface actuator response data is subjected to time axis repositioning by a dynamic window delay sampling method based on relay state synchronous marking, transient response drift and initial displacement misjudgment caused by micro-arc disturbance at the initial stage of relay switching are repaired; the control surface actuator response data is subjected to dynamic denoising by a sliding fitting method with response derivative constraint, high-frequency noise caused by starting stage and impact current is filtered out; phase errors caused by mechanical hysteresis and sampling offset are identified and compensated by a delay identification method based on control-response phase correlation; the control surface actuator response data is subjected to scale unification processing by amplitude normalization and response rate standard deviation scaling strategies.

[0012] Further, the specific steps of generating a continuous control excitation signal based on the pretreated control surface actuator response data and driving a relay to realize channel switching are as follows: based on the pretreated control surface actuator response data, a digital sine sequence is generated, and a continuous control excitation voltage is output through a digital-to-analog converter; the control excitation voltage is connected to the target channel after power amplification, the excitation frequency is set by a clock control circuit and is output synchronously with the control excitation voltage; a control signal is output through a decoding circuit to drive the relay to switch the channel; after the relay switching is completed, the control excitation voltage, the actuator feedback voltage and the actuator current in the continuous fixed period before and after the relay switching are extracted in the sampling period, and the average values before and after the switching are calculated respectively.

[0013] Further, the specific steps of evaluating the stability degree before and after the relay switching are as follows: based on the average values before and after the switching, the stability degree before and after the relay switching is evaluated: the absolute value of the difference between the average values of the control excitation voltage before and after the relay switching is calculated to obtain the control input variation term; the absolute value of the difference between the average values of the actuator feedback voltage before and after the relay switching is calculated to obtain the voltage response variation term; the absolute value of the difference between the average values of the actuator current before and after the relay switching is calculated to obtain the current response variation term; the control input variation term, the voltage response variation term and the current response variation term are summed to obtain the switching joint disturbance evaluation value.

[0014] Further, the specific steps of screening the stable sampling period and constructing the stable response data set are as follows: the switching joint disturbance evaluation value and the switching disturbance threshold value are compared in real time, if the switching joint disturbance evaluation value is greater than the switching disturbance threshold value, it is determined that there is still non-steady-state disturbance in the current channel, and the recording of the control surface actuator response data in the current sampling period is suspended, and the judgment is made again after the next sampling period is evaluated; if the switching joint disturbance evaluation value is less than or equal to the switching disturbance threshold value, it is determined that the current channel has stabilized, and the control surface actuator response data in a fixed number of sampling periods is recorded continuously from the current sampling period, and the stable response data set is constructed.

[0015] Further, the specific steps of screening the candidate response starting point based on the stable response data set and identifying the effective response starting point and the response ending point of each channel are as follows: based on the stable response data set, the maximum value of the actuator current is extracted; the first-order difference of the actuator mechanical displacement signal is calculated to obtain the displacement change rate, and the trend mutation point is identified, and the time corresponding to the trend mutation point is marked as the candidate response starting point; the control surface actuator response data of the continuous fixed sampling period starting from the candidate response starting point is extracted to construct a response starting evaluation value: the absolute value of the difference between the phase angle of the control excitation voltage and the phase angle of the actuator feedback voltage is calculated, and the absolute value is divided by The reverse opposite value is taken to obtain a phase response cooperativity term; the ratio of the actuator current to the maximum value of the actuator current is calculated to obtain a driving strength normalization term; the displacement rate of change, the phase response cooperativity term and the driving strength normalization term are multiplied in each sampling period, and the product result is weighted and accumulated in a continuous fixed sampling period and then averaged to obtain a response starting evaluation value; the response starting evaluation value is compared with a response starting threshold value in real time, if the response starting evaluation value is greater than the response starting threshold value, the current candidate point is confirmed as an effective response starting point, and the rudder surface actuator response data after the starting point is intercepted; if the response starting evaluation value is lower than the response starting threshold value, the candidate response starting point is slid backward, and the above calculation process is repeated until the first effective response starting point meeting the response starting threshold value condition is identified; after the effective response starting point is determined, the analysis sampling period is slid backward, the first-order differential absolute value of the actuator feedback voltage, the first-order differential absolute value of the actuator mechanical displacement and the standard deviation of the actuator current in the sliding window are calculated, if the three indicators are all lower than the lower limit of the feedback voltage change, the lower limit of the displacement rate and the current fluctuation stability threshold in the continuous fixed sampling period, the current sampling period is determined as the response ending point.

[0016] Further, the specific steps of calculating the component indicators in the response section and constructing the rudder surface actuator response feature vector are as follows: the rudder surface actuator response data in the continuous sampling period from the effective response starting point to the response ending point is intercepted, and the component indicators in the response section are calculated: the difference between the maximum value and the minimum value of the actuator feedback voltage in the response section is calculated to obtain a response voltage range; the first-order differential maximum value of the actuator mechanical displacement in the response section is counted to obtain a response displacement maximum rate; the maximum value of the difference between the control excitation voltage phase angle and the actuator feedback voltage phase angle in the response section is extracted to obtain a response phase shift peak value; the standard deviation of the actuator current in the response section is calculated, and the maximum value of the actuator current in the response section is extracted to obtain a response current standard deviation and a response current maximum value; the response voltage range, the response displacement maximum rate, the response phase shift peak value, the response current standard deviation and the response current maximum value are extracted to jointly construct the response feature vector.

[0017] Further, the specific steps of extracting the constructed response feature vector and evaluating the deviation degree between the current response behavior and the ideal state are as follows: the response feature vector is extracted to evaluate the deviation degree between the current response behavior and the ideal state: the response voltage range is divided by the absolute value of the response voltage range plus the response displacement maximum rate as an amplitude change term; the absolute value of the response phase shift peak value is divided by the response displacement maximum rate as a phase change term; the response current standard deviation is divided by the response current maximum value as a current change term; the amplitude change term, the phase change term and the current change term are combined to obtain a response behavior evaluation value; the response behavior evaluation value is compared with a response behavior threshold value in real time, if the response behavior evaluation value is greater than the response behavior threshold value, the current response behavior is confirmed as an ideal state, otherwise, the current response behavior is not an ideal state. the ratio of the standard deviation of the response current to the maximum value of the response current as a current fluctuation normalization term; multiplying the amplitude variation term, the phase difference amplification term, and the current fluctuation normalization term in sequence to obtain a response deviation evaluation value; comparing the response deviation evaluation value obtained by calculation with a response deviation threshold value; if the response deviation evaluation value is less than or equal to the response deviation threshold value, determining that the current response section is a normal response; if the response deviation evaluation value is greater than the response deviation threshold value, entering a local anomaly analysis link, and respectively performing feature threshold value judgment on the response voltage range, the response displacement maximum rate, the response phase offset peak value, and the response current standard deviation; if the voltage response range is greater than a voltage amplitude threshold value and the displacement maximum rate is lower than a displacement rate lower limit, identifying a response delay state; if the phase offset peak value is greater than a phase difference threshold value and the duration is not lower than a continuous sampling period lower limit, identifying a feedback lag state; if the displacement maximum rate is greater than a rate upper limit and the displacement change trend after the response section tends to be flat, identifying a displacement saturation state; if the current standard deviation proportion is higher than a current fluctuation ratio threshold value and the fluctuation times in a unit time exceed a current fluctuation threshold value, identifying a driving current disturbance state.

[0018] Further, based on the evaluation result, the abnormal response state is identified, the channel level response behavior label is generated, and the specific steps of forming the classification result are as follows: the identified response state is structurally bound with the current channel number and the sampling time information to generate the response behavior label; at the same time, the abnormal channel is set with a review flag, and the corresponding abnormal state is automatically labeled; after the detection task of all channels is completed, the response behavior labels of all channels are automatically summarized to generate a response state statistical atlas and an abnormal distribution overview, which provides support data for subsequent fault positioning and performance change trend analysis.

[0019] The second aspect of the present application provides an aircraft control surface automatic detection system based on virtual instrument and matrix switching, characterized by comprising: a control surface response data acquisition and preprocessing module, a control excitation and channel switching evaluation module, a response start and end determination and feature extraction module, and an abnormality identification and response behavior classification module.

[0020] Advantages

[0021] The present application has the following advantages:

[0022] (1) The aircraft control surface automatic detection method and system based on virtual instrument and matrix switching, which fuses displacement change rate, phase response cooperativity term and driving strength normalization term, realizes high-precision identification of the response starting point of the control surface actuator based on the weighted average strategy within the continuous fixed sampling period. It can effectively avoid the initial displacement misjudgment problem caused by micro-arc disturbance at the initial stage of relay switching, solve the response advance and displacement drift diagnosis error faced by the traditional system in the initial response segment, and improve the robustness and timing accuracy of response starting point identification.

[0023] (2) The aircraft control surface automatic detection method and system based on virtual instrument and matrix switching, by constructing a switching joint disturbance evaluation value index system, after the relay channel switching, respectively calculating the control input change term, the voltage response change term and the current response change term three indexes and summing, dynamically evaluating the stability of the sampling period before and after the relay switching, can accurately exclude the non-steady-state channel sampling period, ensure that the stable response data set only contains the true response behavior under the controlled excitation, and provide a reliable data basis for subsequent response feature extraction.

[0024] (3), the automatic detection method and system of aircraft control surface based on virtual instrument and matrix switching, by constructing response characteristic vector, extracting response voltage range, response displacement maximum rate, response phase offset peak, response current standard deviation and response current maximum five indexes, forming multi-dimensional, multi-channel response behavior characteristic expression, providing comprehensive, fine feature support for subsequent response state recognition and abnormal classification.

[0025] (4), the automatic detection method and system of aircraft control surface based on virtual instrument and matrix switching, by constructing response deviation evaluation value index system, evaluating the deviation degree of current response behavior and ideal state. If the response deviation evaluation value exceeds the response deviation threshold, further combined with each single index and feature threshold value judgment, identify including subdivision abnormal state, automatically generate channel level response behavior label, provide accurate basis for system level abnormal traceability. BRIEF DESCRIPTION OF DRAWINGS

[0026] Figure 1 The flow chart of the automatic detection method of aircraft control surface based on virtual instrument and matrix switching is shown in the figure.

[0027] Figure 2 The structure diagram of the automatic detection system of aircraft control surface based on virtual instrument and matrix switching is shown in the figure.

[0028] Figure 3 The principle diagram of excitation signal generation and response feedback is shown in the figure.

[0029] Figure 4 The structure composition block diagram of main control program and modular detection function is shown in the figure.

[0030] Figure 5 The hardware structure schematic diagram of the control surface actuator multi-channel detection device based on PC104 platform is shown in the figure. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0032] Please refer to Figures 1-5The embodiment of the application provides a technical scheme: an airplane control surface automatic detection method and system based on a virtual instrument and matrix switching, comprising the following steps: S1, full-process dynamic acquisition is performed on control surface actuator operation, control surface actuator response data is acquired, and time axis repositioning, dynamic denoising, phase compensation and scale unification are performed on the control surface actuator response data; S2, continuous control excitation signals are generated based on the pretreated control surface actuator response data, relays are driven to realize channel switching, and the stability degrees before and after relay switching are evaluated, a stable sampling period is screened, and a stable response data set is constructed; S3, candidate response starting points are screened based on the stable response data set, effective response starting points and response ending points of each channel are identified, component indicators in a response section are calculated, and a control surface actuator response feature vector is constructed; S4, the response feature vector is extracted, the deviation degree between the current response behavior and the ideal state is evaluated, an abnormal response state is identified based on the evaluation result, a channel-level response behavior label is generated, and a classification result is formed by summarizing.

[0033] Specifically, the specific steps of full-process dynamic acquisition on control surface actuator operation, acquisition of control surface actuator response data, time axis repositioning, dynamic denoising, phase compensation and scale unification on the control surface actuator response data are as follows: full-process dynamic acquisition is performed on control surface actuator operation, control surface actuator response data is acquired, the control surface actuator response data includes control excitation voltage, actuator feedback voltage, actuator mechanical displacement, actuator current, excitation frequency, control voltage phase angle and feedback voltage phase angle; a synchronization criterion based on signal sampling sequence stability is established in combination with dynamic correlation information of excitation frequency fluctuation characteristics and response starting delay behavior; time axis repositioning is performed on the control surface actuator response data through a dynamic window delay sampling method based on a relay state synchronization marker, transient response drift and initial displacement misjudgment caused by micro-arc disturbance at the initial stage of relay switching are repaired; dynamic denoising is performed on the control surface actuator response data through a response derivative constraint sliding fitting method, high-frequency noise caused by starting stage and impact current is filtered out; a low-pass filter and a differential amplification circuit are introduced in the acquisition link, high-frequency arc interference and common-mode noise can be effectively suppressed, and the measurement accuracy of actuator feedback voltage and current signals is improved; a morphological smoothing function of a continuous current slope change interval is introduced to enhance the response trend stability identification ability and assist in removing non-control source driving components; phase errors caused by mechanical hysteresis and sampling offset are identified and compensated through a delay identification method based on control-response phase correlation; scale unification is performed on the control surface actuator response data through an amplitude normalization and response rate standard deviation scaling strategy, so that the response sequences of all channels have uniform order of magnitude weights in subsequent calculation links and are conducive to comparison and analysis between feature indicators.

[0034] In this embodiment, by introducing dynamic window delay sampling, response derivative sliding fitting, phase correlation delay identification and scale normalization processing, the processing accuracy of control excitation voltage, actuator feedback voltage, actuator mechanical displacement and actuator current of multi-source rudder surface actuator response data in time synchronization, signal purity, phase consistency and dimension comparability is effectively improved, which provides data foundation guarantee for subsequent response starting point identification and feature extraction.

[0035] Specifically, the specific steps of generating a continuous control excitation signal based on the pretreated rudder surface actuator response data and driving the relay to realize channel switching are as follows: based on the pretreated rudder surface actuator response data, a digital sine sequence is generated, and a continuous control excitation voltage is output through a digital-to-analog converter, wherein the excitation signal amplitude, frequency and phase are referenced from the characteristic mean values of the historical stable segments in the stable response data set; the control excitation voltage is connected to the target channel after power amplification, the excitation frequency is set by a clock control circuit, and is output synchronously with the control excitation voltage to ensure the consistency of excitation rhythm and the alignment of response between channels; the frequency, phase and waveform of the control excitation signal are precisely controlled through an FPGA module, the frequency synthesis is completed by a digital phase-locked loop device to ensure that the output excitation and response acquisition are strictly aligned in time reference; a control signal is output through a decoding circuit to drive the relay to switch the channel, the duration of the relay control signal is set by a scheduling strategy to avoid the arc noise duration window; after the relay switching is completed, the control excitation voltage, actuator feedback voltage and actuator current in the continuous fixed period before and after the relay switching are extracted in the sampling period, the mean values before and after the switching are calculated respectively, and the synchronization relationship between the excitation frequency and the sampling period is recorded for subsequent response stability judgment.

[0036] As shown in Figure 3 , it is a schematic diagram of excitation signal generation and response feedback, which shows the complete process of excitation signal generation and response feedback in the rudder surface actuator response test. The integrated waveform generator is used to output a sine signal of the target frequency, which is converted into an analog voltage signal through a D / A converter, input to a power operational amplifier module for amplitude amplification to drive the actuator to run, and at the same time trigger the displacement sensor to detect the response displacement. The computer receives the feedback data for subsequent response feature extraction and behavior classification analysis. This structure embodies the continuity and high precision of excitation waveform control, signal amplitude adjustment, power output driving and feedback sensing, and provides a basis for the quantitative evaluation of rudder surface actuator dynamic response behavior.

[0037] In the embodiment, the continuous control excitation voltage is generated based on the pretreated rudder surface actuator response data, the excitation frequency and phase output are accurately set, the high-precision switching control of the relay is realized by combining the decoding circuit, and the mean values of the control excitation voltage, the actuator feedback voltage and the actuator current before and after switching are extracted, thereby providing a high-quality input basis with consistent rhythm, controllable response and clear switching for subsequent identification of channel stable state and construction of stable response data set.

[0038] Specifically, the specific steps for evaluating the stable degree before and after the switching of the relay are as follows: based on the mean values before and after the switching, the stable degree before and after the switching of the relay is evaluated: first, according to the sampling rhythm of the stable response data set, the absolute value of the difference between the mean values of the control excitation voltage before and after the switching of the relay is calculated to obtain the control input change item; then, the absolute value of the difference between the mean values of the actuator feedback voltage before and after the switching of the relay is calculated in combination with the response matching of the excitation signal output link and the feedback link to obtain the voltage response change item; subsequently, the absolute value of the difference between the mean values of the actuator current before and after the switching of the relay is calculated with reference to the actuator current driving characteristics to obtain the current response change item; the control input change item, the voltage response change item and the current response change item are summed to obtain the switching joint disturbance evaluation value.

[0039] The specific calculation formula of the switching joint disturbance evaluation value is as follows:

[0040]

[0041] In the formula, Q represents the switching joint disturbance evaluation value, represents the mean value of the control excitation voltage before the switching of the relay, represents the mean value of the control excitation voltage after the switching of the relay, represents the mean value of the actuator feedback voltage before the switching of the relay, represents the mean value of the actuator feedback voltage after the switching of the relay, represents the mean value of the actuator current before the switching of the relay, represents the mean value of the actuator current after the switching of the relay.

[0042] In the embodiment, by accurately extracting the change amplitudes of the control excitation voltage mean value, the actuator feedback voltage mean value and the actuator current mean value before and after the switching of the relay, the transient disturbance degree caused by the switching of the relay is effectively identified, and it is ensured that the data segment entering the subsequent sampling has sufficient voltage stability, current consistency and feedback response continuity, thereby laying a data foundation for accurate construction of the stable response data set.

[0043] Specifically, the specific steps of screening a stable sampling period and constructing a stable response data set are as follows: comparing a switching joint disturbance evaluation value and a switching disturbance threshold value in real time, the disturbance evaluation value is composed of a control input change item, a voltage response change item and a current response change item in turn, and can reflect the disturbance intensity of multiple sources in the relay switching process, if the switching joint disturbance evaluation value is greater than the switching disturbance threshold value, it is determined that there is still non-steady-state disturbance in the current channel, such disturbance is easy to cause the feedback voltage of the actuator to jump instantaneously, the actuator current to fluctuate intensively, and the mechanical displacement response to deviate, the recording of the response data of the control surface actuator in the current sampling period is suspended, and the judgment is made again after the next sampling period is re-evaluated; if the switching joint disturbance evaluation value is less than or equal to the switching disturbance threshold value, it is determined that the current channel has been stabilized, the current sampling period is started, whether the actuator feedback voltage trend returns to the steady-state track is observed, the actuator current enters the stable driving interval, and the response data of the control surface actuator in a fixed number of sampling periods is recorded continuously to construct a stable response data set.

[0044] In the embodiment, by comparing the switching joint disturbance evaluation value and the switching disturbance threshold value, the stability state of the channel after the relay switching is dynamically distinguished, the disturbance intensity is quantitatively evaluated by combining the multiple source change amounts of the control excitation voltage, the actuator feedback voltage and the actuator current, the transient interference influence in the non-steady-state stage can be effectively shielded, the sampling recording is started only under the condition that the disturbance is attenuated and the response is recovered to be stable, so that the stable response data set constructed subsequently has high reliability and consistency, and an accurate data basis is laid for the dynamic response analysis of the control surface actuator.

[0045] Specifically, the specific steps of screening a candidate response starting point based on the stable response data set and identifying the effective response starting point and the response ending point of each channel are as follows: based on the stable response data set, the maximum value of the actuator current is extracted; the first-order difference of the actuator mechanical displacement signal is performed to obtain the displacement change rate, and the trend mutation point of the displacement change is identified, and the time corresponding to the trend mutation point is marked as the candidate response starting point; the response data of the control surface actuator in the continuous fixed sampling period starting from the candidate response starting point is extracted to construct a response starting evaluation value: the absolute value of the difference between the phase angle of the control excitation voltage and the phase angle of the actuator feedback voltage is calculated, and the absolute value is divided by a phase response cooperativity term is obtained by taking the reverse opposite value of the phase response cooperativity term; a driving strength normalization term is obtained by calculating the ratio of the actuator current and the maximum value of the actuator current; the displacement rate of change, the phase response cooperativity term and the driving strength normalization term are multiplied in each sampling period, and the product result is weighted and accumulated in a continuous fixed sampling period and then averaged to obtain a response starting evaluation value; the response starting evaluation value is compared with a response starting threshold value in real time, if the response starting evaluation value is greater than the response starting threshold value, the current candidate point is confirmed as an effective response starting point, and the rudder surface actuator response data after the starting point is intercepted; if the response starting evaluation value is lower than the response starting threshold value, the candidate response starting point is slid backward, and the above calculation process is repeated until the first effective response starting point meeting the response starting threshold value condition is identified; after the effective response starting point is determined, the analysis sampling period is slid backward, the first order differential absolute value of the actuator feedback voltage, the first order differential absolute value of the actuator mechanical displacement and the standard deviation of the actuator current in the sliding window are calculated, if the three indicators are all lower than the lower limit of the feedback voltage change, the lower limit of the displacement rate and the current fluctuation stability threshold in a continuous fixed sampling period, the current sampling period is determined as the response ending point.

[0046] wherein the specific calculation formula of the response starting evaluation value is:

[0047] ;

[0048] In the formula, X represents the response starting evaluation value, T represents the number of fixed sampling periods, represents the candidate response starting point, S represents the actuator mechanical displacement, represents the displacement rate of change, represents the control excitation voltage phase angle, represents the actuator feedback voltage phase angle, I represents the actuator current, represents the maximum value of the actuator current.

[0049] In the embodiment, the response starting evaluation value is constructed by comprehensively utilizing the maximum value of the actuator current, the actuator mechanical displacement rate of change, the control excitation voltage phase angle and the actuator feedback voltage phase angle difference, and the effective response starting point is accurately determined through dynamic characteristic calculation in a continuous sampling period; on this basis, the endpoint judgment mechanism is constructed by combining the first order differential absolute value of the feedback voltage, the first order differential absolute value of the mechanical displacement and the standard deviation of the actuator current, so as to ensure the accuracy and stability of the response segment starting and ending determination, provide a precise interval basis for subsequent response feature extraction, and improve the accuracy and robustness of the overall response behavior recognition.

[0050] Specifically, the specific steps of calculating the component indicators in the response section to construct the response characteristic vector of the rudder surface actuator are as follows: intercepting the rudder surface actuator response data in the continuous sampling period from the start point of the effective response to the end point of the response, calculating the component indicators in the response section: calculating the difference between the maximum value and the minimum value of the actuator feedback voltage in the response section to obtain the response voltage range, which is used to reflect the fluctuation amplitude change characteristic of the feedback voltage signal in the response process; counting the maximum value of the first-order difference of the actuator mechanical displacement in the response section to obtain the response displacement maximum rate, which embodies the response sensitivity and mutation characteristics of the mechanical displacement; extracting the maximum value of the difference between the phase angle of the control excitation voltage and the phase angle of the actuator feedback voltage in the response section to obtain the response phase shift peak value, which is used to evaluate the synchronization error in the phase transmission process; calculating the standard deviation of the actuator current in the response section and extracting the maximum value of the actuator current in the response section to obtain the response current standard deviation and the response current maximum value, which are used to represent the stability degree and peak load capacity of the current driving process; extracting the response voltage range, the response displacement maximum rate, the response phase shift peak value, the response current standard deviation and the response current maximum value, and jointly constructing the response characteristic vector to provide multi-dimensional numerical support for subsequent anomaly identification and channel behavior analysis.

[0051] In the embodiment, by quantifying the rudder surface actuator response data between the start point of the effective response and the end point of the response, the system extracts the feedback voltage range, the mechanical displacement maximum rate, the phase angle shift peak value, the current standard deviation and the current maximum value, constructs the response characteristic vector covering four types of characteristics including amplitude fluctuation, displacement change, phase response and current driving, and effectively enhances the structured description ability of the response behavior of the rudder surface actuator, providing a high-resolution parameter basis for anomaly identification.

[0052] Specifically, the specific steps of extracting and constructing the response characteristic vector to evaluate the deviation degree between the current response behavior and the ideal state are as follows: extracting and constructing the response characteristic vector to evaluate the deviation degree between the current response behavior and the ideal state: dividing the response voltage range by the absolute value of the response voltage range plus the response displacement maximum rate as the amplitude change item; dividing the absolute value of the response phase shift peak value by the absolute value of the response phase shift peak value plus the response current standard deviation as the phase change item; dividing the absolute value of the response current maximum value by the absolute value of the response current maximum value plus the response current standard deviation as the current change item; and adding the amplitude change item, the phase change item and the current change item to obtain the deviation degree between the current response behavior and the ideal state. a ratio of the response current standard deviation to the response current maximum value as a current fluctuation normalization term; multiplying the amplitude variation term, the phase difference amplification term, and the current fluctuation normalization term in sequence to obtain a response deviation evaluation value; comparing the response deviation evaluation value obtained by calculation with a response deviation threshold value; if the response deviation evaluation value is less than or equal to the response deviation threshold value, determining that the current response section is a normal response; if the response deviation evaluation value is greater than the response deviation threshold value, entering a local anomaly analysis link, and respectively performing feature threshold value judgment on the response voltage range, the response displacement maximum rate, the response phase offset peak value, and the response current standard deviation; if the voltage response range is greater than a voltage amplitude threshold value and the displacement maximum rate is lower than a displacement rate lower limit, identifying a response lag state; if the phase offset peak value is greater than a phase difference threshold value and the duration is not lower than a continuous sampling period lower limit, identifying a feedback lag state; if the displacement maximum rate is greater than a rate upper limit and the displacement change after the response section tends to be gentle, identifying a displacement saturation state; and if the current standard deviation proportion is higher than a current fluctuation ratio threshold value and the fluctuation times in a unit time exceed a current fluctuation threshold value, identifying a driving current disturbance state.

[0053] wherein the specific calculation formula of the response deviation evaluation value is:

[0054]

[0055] In the formula, P represents the response deviation evaluation value, represents the response voltage range, represents the response displacement maximum rate, represents the response phase offset peak value, represents the response current standard deviation, represents the response current maximum value.

[0056] In the embodiment, the response voltage range, the response displacement maximum rate, the response phase offset peak value, the response current standard deviation, and the response current maximum value in the response feature vector are used to construct multiple normalized discrimination indexes, the deviation degree between the response behavior and the ideal state is quantified, and the response lag state, the feedback lag state, the displacement saturation state, and the driving current disturbance state are accurately identified in combination with the comparison result of the response deviation evaluation value and the preset threshold value, so that the grading identification ability of the response behavior anomaly of the control surface actuator is effectively improved.

[0057] Specifically, based on the evaluation results, the abnormal response state is identified, the channel-level response behavior label is generated, and the specific steps of forming the classification results are as follows: the identified response state is structurally bound with the current channel number and sampling time information, the response behavior label is generated, the label content includes the abnormal type, the response deviation evaluation value, the threshold determination result and the corresponding component index; at the same time, the recheck flag is set for the channel identified as abnormal, the abnormal duration, the start and end sampling period and the abnormal peak value are added in the flag, and the corresponding abnormal state is automatically labeled to track the consistency evolution of the subsequent control instruction and feedback behavior; after all channel detection tasks are completed, the response behavior labels of all channels are automatically summarized, the response state statistical atlas and abnormal distribution overview are generated, the channel distribution density and response characteristic index mean distribution of each type of abnormal state are presented in the statistical atlas, which provides quantitative support data and structured reference basis for subsequent fault positioning and rudder surface response performance change trend analysis based on time sequence evolution characteristics.

[0058] In the embodiment, by structurally binding and labeling the identified response state, not only the quantitative classification of response behavior and the accurate positioning of sampling time are realized, but also the tracking ability of abnormal response channel is improved by adding the response deviation evaluation value, abnormal duration, response segment start and end sampling period and abnormal peak value information, the identification efficiency and discrimination accuracy of abnormal response behavior characteristics in rudder surface control system detection are further enhanced, and finally the response state statistical atlas and abnormal distribution overview can be used as the basis for rudder surface response performance trend identification and fault positioning analysis, which enhances the comprehensive perception and classification decision ability of actuator dynamic behavior change.

[0059] As Figure 2As shown, the second aspect of the present application provides an aircraft control surface automatic detection system based on virtual instrument and matrix switching, characterized by: a control surface response data acquisition and preprocessing module, a control excitation and channel switching evaluation module, a response start and end determination and feature extraction module, and an abnormality identification and response behavior classification module. The control surface response data acquisition and preprocessing module is used to dynamically collect the whole process of the control surface actuator operation, obtain the control surface actuator response data, and perform time axis relocation, dynamic noise reduction, phase compensation, and scale unification on the control surface actuator response data. The control excitation and channel switching evaluation module is used to generate a continuous control excitation signal based on the preprocessed control surface actuator response data, drive a relay to realize channel switching, evaluate the stability before and after the relay switching, screen stable sampling periods, and construct a stable response data set. The response start and end determination and feature extraction module is used to screen candidate response starting points based on the stable response data set, identify the effective response starting points and response ending points of each channel, calculate the component indicators in the response segment, and construct a control surface actuator response feature vector. The abnormality identification and response behavior classification module is used to extract and construct the response feature vector, evaluate the deviation between the current response behavior and the ideal state, identify the abnormal response state based on the evaluation result, generate channel-level response behavior labels, and aggregate the classification results. In the integration process of the above functional modules, the main control program serves as the core scheduling unit of the detection platform, responsible for coordinating the tasks of control surface response data acquisition and preprocessing, excitation signal generation and channel switching control, response behavior analysis and result classification output, and providing unified management support for the data flow and control logic between system modules. In addition, the aircraft control surface automatic detection system based on virtual instrument and matrix switching is constructed based on a PC104 structure virtual instrument platform, has high integration and embedded processing capability, and is suitable for multi-channel, multi-frequency parallel test environment.

[0060] As Figure 4The diagram shows the structural composition of the main control program and modular testing functions, comprehensively demonstrating the functional layering and process logic of the aircraft control surface automatic testing system based on virtual instruments and matrix switching. The main control program, as the core scheduling unit of the system, coordinates four major modules: hardware control, test tasks, database operations, and result processing. Specifically, the hardware control module is responsible for initializing the system and configuring related equipment, and flexibly switching between multi-channel test paths through matrix switches; the test module supports test item selection, performance testing, and system self-checks, ensuring the integrity and accuracy of data acquisition; the core acquisition and excitation control functions rely on D / A and A / D chips for high-precision analog signal processing; the database module handles interrupted data transfer and structured storage of sampling results; and the result processing module enables real-time display and long-term archiving of test results, improving the traceability of the testing process and the utilization rate of results. The highly integrated and clearly defined overall architecture supports multi-channel concurrent detection and dynamic response behavior classification analysis, providing key technical support for the entire process of control surface actuator response feature extraction and anomaly identification.

[0061] like Figure 5 The diagram shows the hardware structure of a multi-channel detection device for control surface actuators based on the PC104 platform. The detection device is built on the PC104 embedded platform, and its core modules include a signal generator, A / D board, D / A board, and I / O board. It connects to the control surface control box and control surface actuators via a relay matrix switch. Peripherally, a mouse panel and an LCD display are provided for interaction and status visualization. The hardware structure of the PC104-based multi-channel detection device effectively supports the operation of functional modules in this implementation scheme, such as control surface actuator response data acquisition, excitation signal generation, relay channel switching, and feedback data processing, forming a complete closed-loop detection process.

[0062] This implementation plan integrates a continuous process including control surface response data acquisition and preprocessing, control excitation signal generation and relay channel switching, automatic response start and end identification and feature vector construction, and response behavior deviation assessment and classification labeling. This enables accurate acquisition, effective start and end interception, key feature extraction, and abnormal behavior identification of dynamic response data of the control surface actuator during multi-channel and multi-cycle operation. It significantly improves the automation level of response data processing and the accuracy of behavior classification, and constructs a response feature extraction and anomaly classification mechanism applicable to the entire process of control surface control system detection. This provides complete process support for control surface actuator performance stability analysis and rapid screening of response anomalies.

[0063] It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting; it is not intended to exclude myriad other embodiments of the present application that other presenters can develop. It is also possible, however, that only a single element can be present. It is further noted that such a term as "comprising" is intended to mean that the embodiments include the recited elements, but not excluding other elements. "Consisting essentially of when used herein in relation to a composition, means that the composition includes the recited elements, and can include additional elements, so long as the additional elements do not materially alter the basic and novel characteristics of the claimed composition. "Consisting of" when used herein in relation to a composition, means that the composition includes the recited elements, and no additional elements.

[0064] The preferred embodiments of the application disclosed above are only to help explain the principles of the present application. The preferred embodiments do not describe all the details of the present application, nor limit the present application to only the specific embodiments described. It is apparent that many modifications and variations can be made to the present application based on the content of the present disclosure. The present disclosure selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present application, so that those skilled in the art can well understand and utilize the present application. The present application is limited only by the claims and their full scope and equivalents.

Claims

1. An automatic detection method for aircraft control surfaces based on virtual instruments and matrix switching, characterized in that, Includes the following steps: S1, dynamically acquires the entire process of the control surface actuator operation, obtains the control surface actuator response data, and performs time axis repositioning, dynamic noise reduction, phase compensation and scale unification on the control surface actuator response data. S2, Based on the preprocessed control surface actuator response data, a continuous control excitation signal is generated to drive the relay to achieve channel switching, and the stability before and after the relay switching is evaluated, a stable sampling period is selected, and a stable response dataset is constructed. The specific steps for evaluating the stability of the relay before and after switching are as follows: Based on the average values ​​before and after each switching, the stability of the relay before and after switching is evaluated: the absolute value of the difference between the average values ​​of the control excitation voltage before and after the relay switching is calculated to obtain the control input change term; the absolute value of the difference between the average values ​​of the actuator feedback voltage before and after the relay switching is calculated to obtain the voltage response change term; the absolute value of the difference between the average values ​​of the actuator current before and after the relay switching is calculated to obtain the current response change term. The summation of the control input variation, voltage response variation, and current response variation is used to obtain the joint switching disturbance evaluation value. The specific steps for selecting stable sampling periods and constructing a stable response dataset are as follows: The system compares the combined switching disturbance assessment value and the switching disturbance threshold in real time. If the combined switching disturbance assessment value is greater than the switching disturbance threshold, it is determined that there is still an unsteady disturbance in the current channel. The recording of the control surface actuator response data in the current sampling period is paused, and the judgment is made again after reassessment in the next sampling period. If the combined switching disturbance assessment value is less than or equal to the switching disturbance threshold, it is determined that the current channel is stable. Starting from the current sampling period, the control surface actuator response data in a fixed number of sampling periods are continuously recorded to build a stable response dataset. S3. Based on the stable response dataset, candidate response starting points are selected, and the effective response starting points and response ending points of each channel are identified. The component indices within the response segment are calculated, and the response feature vector of the control surface actuator is constructed. S4. Extract and construct response feature vectors, evaluate the degree of deviation between the current response behavior and the ideal state, identify abnormal response states based on the evaluation results, generate channel-level response behavior labels, and summarize them to form classification results.

2. The automatic detection method for aircraft control surfaces based on virtual instruments and matrix switching according to claim 1, characterized in that: The specific steps for dynamically acquiring the entire process of the control surface actuator operation, obtaining the control surface actuator response data, and performing time axis repositioning, dynamic noise reduction, phase compensation, and scale unification on the control surface actuator response data are as follows: The entire process of the control surface actuator operation is dynamically acquired to obtain control surface actuator response data, which includes control excitation voltage, actuator feedback voltage, actuator mechanical displacement, actuator current, excitation frequency, control voltage phase angle, and feedback voltage phase angle. A dynamic window delay sampling method based on relay state synchronization marking is used to reposition the time axis of the control surface actuator response data, correcting the instantaneous response drift and initial displacement misjudgment caused by micro-arc disturbances in the early stage of relay switching. A sliding fitting method with response derivative constraints is used to dynamically denoise the control surface actuator response data, filtering out high-frequency noise caused by the start-up phase and inrush current. A delay identification method based on control-response phase correlation is used to identify and compensate for phase errors caused by mechanical hysteresis and sampling offset. A scaling strategy of amplitude normalization and response rate standard deviation scaling is used to unify the scale of the control surface actuator response data.

3. The automatic detection method for aircraft control surfaces based on virtual instruments and matrix switching according to claim 1, characterized in that: The specific steps for generating a continuous control excitation signal based on the preprocessed control surface actuator response data to drive the relay and achieve channel switching are as follows: Based on the preprocessed control surface actuator response data, a digital sine sequence is generated and a continuous control excitation voltage is output via a digital-to-analog converter. The control excitation voltage is then amplified and connected to the target channel. The excitation frequency is set by a clock control circuit and output synchronously with the control excitation voltage. The control signal is output through the decoding circuit to drive the relay to switch channels. After the relay is switched, the control excitation voltage, actuator feedback voltage and actuator current are extracted in a continuous fixed period before and after the relay switching, and the average values ​​before and after the switching are calculated respectively.

4. The automatic detection method for aircraft control surfaces based on virtual instruments and matrix switching according to claim 1, characterized in that: The specific steps for filtering candidate response starting points based on the stable response dataset and identifying the effective response starting and ending points of each channel are as follows: Based on the stable response dataset, the maximum value of the actuator current is extracted; the first-order difference of the actuator mechanical displacement signal is performed to obtain the displacement change rate, identify the abrupt change point of the displacement change trend, and mark the time corresponding to the abrupt change point as the candidate response start point. Extract the control surface actuator response data for a continuous fixed sampling period starting from the candidate response start point, and construct the response start evaluation value: calculate the absolute value of the difference between the control excitation voltage phase angle and the actuator feedback voltage phase angle, and divide this absolute value by... Then, take its reverse relative value to obtain the phase response coordination term; calculate the ratio of actuator current to the maximum value of actuator current to obtain the driving strength normalization term; multiply the displacement change rate, phase response coordination term and driving strength normalization term in each sampling period, and then average the product results in a continuous fixed sampling period to obtain the initial response evaluation value. The response start evaluation value and the response start threshold are compared in real time. If the response start evaluation value is greater than the response start threshold, the current candidate point is confirmed as a valid response start point, and the control surface actuator response data after the start point is captured. If the response start evaluation value is lower than the response start threshold, the candidate response start point is slid backward, and the above calculation process is repeated until the first valid response start point that meets the response start threshold condition is identified. After the effective response start point is determined, the sampling period is analyzed backward. The absolute value of the first difference of the actuator feedback voltage, the absolute value of the first difference of the actuator mechanical displacement, and the standard deviation of the actuator current within the sliding window are calculated. If all three indicators are lower than the lower limit of the feedback voltage change, the lower limit of the displacement rate, and the current fluctuation stability threshold within a continuous fixed sampling period, the current sampling period is determined to be the response end point.

5. The automatic detection method for aircraft control surfaces based on virtual instruments and matrix switching according to claim 1, characterized in that: The specific steps for constructing the eigenvector of the control surface actuator response by calculating the component indices within the response segment are as follows: Extract the control surface actuator response data within a continuous sampling period from the effective response start point to the response end point, and calculate the component indices within the response segment: calculate the difference between the maximum and minimum values ​​of the actuator feedback voltage within the response segment to obtain the response voltage range; statistically analyze the maximum value of the first-order difference of the actuator mechanical displacement within the response segment to obtain the maximum response displacement rate; extract the maximum value of the difference between the phase angle of the control excitation voltage and the phase angle of the actuator feedback voltage within the response segment to obtain the response phase offset peak value; calculate the standard deviation of the actuator current within the response segment, and extract the maximum value of the actuator current within the response segment to obtain the standard deviation and maximum value of the response current. Extract the response voltage range, response displacement maximum rate, response phase shift peak value, response current standard deviation, and response current maximum value, and jointly construct the response feature vector.

6. The automatic detection method for aircraft control surfaces based on virtual instruments and matrix switching according to claim 1, characterized in that: The specific steps for extracting and constructing the response feature vector and evaluating the deviation of the current response behavior from the ideal state are as follows: Extract and construct the response feature vector to evaluate the degree of deviation between the current response behavior and the ideal state: divide the response voltage range by the absolute value of the response voltage range plus the maximum response displacement rate, and use it as the amplitude change term; The absolute value of the peak value of the response phase shift is compared with The ratio is increased by 1 to form the phase difference amplification term; the ratio of the standard deviation of the response current to the maximum value of the response current is used as the current fluctuation normalization term; the amplitude change term, the phase difference amplification term, and the current fluctuation normalization term are multiplied in sequence to obtain the response deviation evaluation value. The calculated response deviation assessment value is compared with the response deviation threshold: if the response deviation assessment value is less than or equal to the response deviation threshold, the current response segment is determined to be a normal response. If the response deviation assessment value is greater than the response deviation threshold, the local anomaly analysis stage is entered, and the characteristic thresholds of the four indicators, namely the response voltage range, the maximum response displacement rate, the peak response phase shift, and the standard deviation of the response current, are judged respectively: if the voltage response range is greater than the voltage amplitude threshold and the maximum displacement rate is lower than the lower limit of the displacement rate, it is identified as a response hysteresis state. If the peak phase offset is greater than the phase difference threshold and the duration is not less than the lower limit of the continuous sampling period, it is identified as a feedback lag state; if the maximum displacement rate is greater than the upper limit of the rate and the subsequent displacement change in the response segment tends to be gradual, it is identified as a displacement saturation state. If the current standard deviation ratio is higher than the current fluctuation ratio threshold, and the number of fluctuations per unit time exceeds the current fluctuation threshold, it is identified as a driving current disturbance state.

7. The automatic detection method for aircraft control surfaces based on virtual instruments and matrix switching according to claim 1, characterized in that: The specific steps for identifying abnormal response states based on evaluation results, generating channel-level response behavior labels, and summarizing them to form classification results are as follows: The identified response status is structurally bound to the current channel number and sampling time information to generate response behavior labels; at the same time, a re-inspection flag is set for channels identified as abnormal, and the corresponding abnormal status is automatically marked. After all channel detection tasks are completed, the response behavior labels of all channels are automatically summarized, and a response status statistical map and anomaly distribution overview are generated to provide supporting data for subsequent fault location and performance change trend analysis.

8. An automatic aircraft control surface detection system based on virtual instruments and matrix switching, employing the automatic aircraft control surface detection method based on virtual instruments and matrix switching as described in any one of claims 1-7, characterized in that: include: The system comprises a control surface response data acquisition and preprocessing module, a control excitation and channel switching evaluation module, a response start / end determination and feature extraction module, and an anomaly identification and response behavior classification module, among which: The control surface response data acquisition and preprocessing module is used to dynamically acquire the control surface actuator's operation throughout the entire process, obtain the control surface actuator response data, and perform time axis repositioning, dynamic noise reduction, phase compensation, and scale unification on the control surface actuator response data. The control excitation and channel switching evaluation module is used to generate a continuous control excitation signal based on the preprocessed control surface actuator response data, drive the relay to realize channel switching, evaluate the stability before and after the relay switching, select stable sampling periods, and construct a stable response dataset. The response start and end determination and feature extraction module is used to filter candidate response start points based on the stable response dataset, identify the effective response start and end points of each channel, calculate the component indexes within the response segment, and construct the control surface actuator response feature vector. The anomaly identification and response behavior classification module is used to extract and construct response feature vectors, evaluate the degree of deviation between the current response behavior and the ideal state, identify abnormal response states based on the evaluation results, generate channel-level response behavior labels, and summarize them to form classification results.

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