Automatic evaluation system for vibration monitoring signals of aerospace products

Abstract

This invention provides an automated evaluation system for vibration monitoring signals of aerospace products, comprising: a raw signal parsing module, a data preprocessing module, a signal parameter configuration module, a signal interpretation and evaluation module, and an evaluation conclusion output module. The raw signal parsing module parses unreadable raw data packets into a program-readable data format; the data preprocessing module eliminates signal start-time errors and performs filtering; the signal parameter configuration module configures parameters for single and related signals, forming a parameter configuration library; the signal interpretation and evaluation module evaluates the waveform similarity of single signals based on a cross-correlation normalization algorithm and interprets the time sequence relationship of related signals; the evaluation conclusion output module displays the evaluation results on a software interface. This invention achieves automated evaluation of vibration monitoring signals of aerospace products, replacing manual interpretation, improving evaluation efficiency and reliability, and possessing good versatility and scalability.

Description

Technical Field

[0001] This invention relates to the field of aerospace product testing technology, specifically to an automated evaluation system for vibration monitoring signals of aerospace products, and more particularly to an automated evaluation system for determining the correctness of test signal curves collected and monitored from the missile during vibration testing of aerospace products. Background Technology

[0002] During vibration testing of aerospace products, onboard telemetry equipment or ground testing equipment generates a large number of monitoring signals. These signals are generally response signals and command signals issued by the aerospace product according to flight control instructions within a specified testing time. Therefore, the monitoring signals are generally output according to predetermined parameter requirements. The accuracy of the collected signal curves directly reflects the operational performance of the aerospace product. Therefore, the evaluation of vibration monitoring signals of aerospace products is an important means of assessing their various electrical performance characteristics during vibration.

[0003] The current evaluation of vibration monitoring signals for aerospace products mainly relies on manual interpretation. Designers evaluate the monitoring signal curves one by one based on design documents or personal experience. There are generally hundreds of vibration monitoring signals for each type of aerospace product. As the number of models and products increases, this manual evaluation method not only consumes a lot of human resources, but is also inefficient, prone to errors, and seriously restricts the production efficiency and reliability of mass-produced models.

[0004] Therefore, there is an urgent need for an easy-to-use automated evaluation system for vibration monitoring signals of aerospace products to improve the evaluation efficiency and reliability of vibration monitoring signals and increase production efficiency. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the purpose of this invention is to provide an automated evaluation system for vibration monitoring signals of aerospace products.

[0006] An automated evaluation system for vibration monitoring signals of aerospace products, provided by the present invention, includes: The raw signal parsing module is used to parse unreadable raw data packets into data packets that can be read by the program. The data preprocessing module is used to filter the parsed measured signal data and eliminate start time errors; The signal parameter configuration module includes configurations for single signal characteristic parameters and associated signal parameters, forming a parameter configuration library. The signal interpretation and evaluation module is used to evaluate the preprocessed signal curves one by one according to the preset parameter requirements in the parameter configuration library, including single signal feature evaluation and associated signal evaluation. The evaluation conclusion output module is used to interpret the results output by the signal interpretation module, give an evaluation conclusion for the evaluated signal, and display it on the evaluation system software interface.

[0007] Preferably, the original data format parsed by the original signal parsing module is a binary data stream format, including .DAT or TDMS files, and the parsed data is a readable .txt file.

[0008] Preferably, the data preprocessing module aligns all signal data to the same time starting point and removes glitches or interference signals.

[0009] Preferably, in the signal parameter configuration module, the signal type corresponding to a single signal characteristic parameter includes pulse signal, step signal, and periodic signal.

[0010] Preferably, the parameters that need to be set for the pulse signal include: pulse start time, level amplitude, pulse width, pulse interval time, signal sampling rate, and sampling time; The parameters that need to be set for the step signal include: signal generation time, trigger slope, initial voltage, trigger voltage, signal sampling rate, and sampling time. The parameters that need to be set for the periodic signal include: waveform type, waveform amplitude, period or frequency, starting phase, signal sampling rate, and sampling time.

[0011] Preferably, in the signal parameter configuration module, the associated signal parameters are used to set the interpretation feature points, timing relationships, and allowable errors between associated signals.

[0012] Preferably, the signal interpretation and evaluation module performs interpretation and evaluation of a single signal including: Based on the parameter name and parameter type, the parameters in the parameter configuration library are called, and a reference signal is generated based on the parameter characteristics. The measured signal and the reference signal are cross-correlated, and the normalized result is obtained based on the mean removal and normalization process to reflect the similarity between the measured signal and the reference signal.

[0013] Preferably, the cross-correlation operation is performed using the following formula:

[0014] in, For the cross-correlation output results, The signal being measured, The reference signal is n, the time axis translation position is n, and the signal sampling length is N. The mean removal and normalization processes are performed using the following formula:

[0015] in The mean of the input signal, The mean of the reference signal, The output is a cross-correlation normalized result.

[0016] Preferably, the signal interpretation and evaluation module performs interpretation and evaluation of the associated signal, including: Each associated signal to be evaluated is evaluated individually to confirm that all associated signals are not distorted; At the set associated signal interpretation point, read the occurrence time of the associated signal at the interpretation point and compare it. If it meets the set timing requirements and error requirements, the timing of the associated signal is correct; otherwise, the timing is abnormal.

[0017] Preferably, the evaluation conclusion output module displays the aerospace product test signal name, single test signal curve feature evaluation conclusion, and associated test signal curve evaluation conclusion on the software evaluation interface. When all signal curves are evaluated correctly, the module gives the conclusions "signal normal" and "association correct". When there is an abnormal signal evaluation, the module gives the conclusions "signal abnormal" and "association abnormal".

[0018] Compared with the prior art, the present invention has the following beneficial effects: 1. The automated evaluation system provided by this invention realizes the fully automated processing of vibration monitoring signals of aerospace products from data input to evaluation conclusion output, completely replacing the traditional manual interpretation method, significantly improving the efficiency and reliability of signal evaluation, and is especially suitable for large-scale test data processing of mass-produced products.

[0019] 2. This invention adopts a single signal evaluation method based on cross-correlation normalization algorithm. By calculating the waveform similarity between the signal under test and the reference signal generated in the parameter configuration library, it realizes the quantitative evaluation of the quality of various types of signals such as pulse signals, step signals, and periodic signals. The evaluation results are objective and consistent, avoiding misjudgment caused by factors such as experience differences or fatigue in manual interpretation.

[0020] 3. Based on single signal evaluation, this invention further introduces a related signal evaluation mechanism. By performing time sequence analysis on a set of related signals with causal relationships, it can effectively verify the logical timing relationship between signals, ensure the correctness of system-level functions, and make up for the insufficiency of single signal evaluation in covering the system interaction logic. Attached Figure Description

[0021] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a schematic diagram of the structure of the present invention; Figure 2 This is a schematic diagram of the data preprocessing module workflow; Figure 3 Flowchart for setting parameters for a single signal curve; Figure 4 Flowchart for setting parameters of associated signal curves; Figure 5 A flowchart for evaluating vibration monitoring signals of aerospace products; Figure 6 A schematic diagram of the software interface for a vibration monitoring signal evaluation system for aerospace products; Figure 7 This is a flowchart illustrating the operation of an automated evaluation system for vibration monitoring signals of aerospace products. Detailed Implementation

[0022] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0023] An automated evaluation system for vibration monitoring signals of aerospace products, such as Figure 1 As shown, it specifically includes five modules: raw signal analysis, data preprocessing, signal parameter configuration, signal interpretation and evaluation, and evaluation conclusion output.

[0024] The raw signal parsing module is used to parse unreadable raw data packets into program-readable data packets. Aerospace product test data includes test data generated by onboard telemetry equipment or ground-based test equipment, typically in DAT or TDMS format. Both of these formats are unreadable. Specific parsing tools are used to parse the data packets into readable TXT format data and extract the "test signal name" and its corresponding one-dimensional array data. All test signal data forms a two-dimensional matrix array.

[0025] The data preprocessing module aligns all signal data to the same starting time and removes glitches or interference. During aerospace product testing, differences in software startup times can cause time discrepancies in each test acquisition. A specific signal (e.g., the "bounce" signal) is taken as the reference signal. Simultaneously, the same signal model (e.g., the "bounce" signal) is extracted from the parameter configuration library. The time difference between the first step occurrence of the acquired ("bounce") signal and the first step occurrence of the reference ("bounce") signal is the time error value. All acquired signals are shifted along the time axis according to this time error to eliminate all signal acquisition startup time deviations. The obtained data is then filtered to remove glitches or interference before being used for evaluation.

[0026] The signal parameter configuration module is used to configure parameters for all signals to be evaluated according to preset curve requirements. Test signal types mainly include: pulse signals, step signals, and periodic signals. The evaluation of test signal curves is performed in conjunction with signal characteristics and timing. Evaluation includes single test signal and associated test signal curve evaluation.

[0027] like Figure 3 As shown, the parameter settings for a single test signal curve are as follows: (1) Pulse signal, the parameters that need to be set are: pulse start time, level amplitude, pulse width, pulse interval time, signal sampling rate, and sampling time.

[0028] (2) Step signal, the parameters that need to be set are: signal generation time, trigger slope (rising edge or falling edge), initial voltage, trigger voltage, signal sampling rate, and sampling time.

[0029] (3) Waveform signal, waveform type (sine wave, sawtooth wave, etc.), waveform amplitude, period (or frequency), starting phase, signal sampling rate, sampling time.

[0030] (4) Set the name of the test signal for aerospace products, determine the signal type, and set the evaluation parameters for each test signal curve.

[0031] (5) Import the set aerospace product test signal parameters into the parameter configuration library.

[0032] like Figure 4 The following is a flowchart showing the parameter setting process for the associated test signal curve: (1) Determine the set of related signals. Based on the system principle, select the set of related signals with causal relationship, such as A occurs → after a delay → B and C occur, [A, B, C] is the set of related signals.

[0033] (2) Determine the correlation mode between the associated signals [A, B, C], and set the judgment feature points, timing relationship and allowable error of the associated signals.

[0034] (3) The set test signal parameters of the associated aerospace products are imported into the parameter configuration library according to the associated signal set.

[0035] The signal interpretation and evaluation module evaluates each signal curve according to preset signal curve parameters, including single signal curve evaluation and related signal curve evaluation. The evaluation process is as follows: Figure 5As shown: The test signal name set and test signal data array are extracted from the two-dimensional matrix array of the collected signals. The collected signal data and parameter configuration library data are extracted according to the test signal name index. The test signals of aerospace products are evaluated one by one. First, the individual signal curves are interpreted and evaluated. Then, according to the association mode of the associated signals, the timing relationship between the associated signals is evaluated to see if it meets the requirements.

[0036] Single signal evaluation includes the following steps: Step S1: Based on the parameter name and parameter type, call the parameters in the parameter configuration library and generate a reference signal based on the parameter characteristics.

[0037] Step S2: Perform cross-correlation operation between the measured signal and the reference signal (see Formula 1). The cross-correlation output result can reflect the degree of similarity between the measured signal and the reference signal.

[0038] (1) Furthermore, mean removal and normalization are performed on the original cross-correlation (see Formula 2 for the normalization formula), and the normalization result is between -1 and 1.

[0039] (2) in, The input signal is the signal being measured; N is the signal sampling length. The reference signal is denoted as n, which is the time axis translation position. The time error of the measured signal has been eliminated by the data preprocessing, so n=0 here. The mean of the input signal; The mean of the reference signal; Output the cross-correlation results; The output is a cross-correlation normalized result.

[0040] when When the value is 1, the waveform of the measured signal is completely consistent with that of the reference signal, and the signal is completely correct.

[0041] when When the value is greater than or equal to 0.9 and less than 1, the waveform of the measured signal is very similar to that of the reference signal, and the signal is good.

[0042] when When the value is greater than or equal to 0.8 and less than 0.9, the waveform of the measured signal is highly similar to that of the reference signal, and the signal is slightly distorted.

[0043] when When the value is less than 0.8 and greater than 0, the waveform of the measured signal is not very similar to that of the reference signal, and the signal is distorted.

[0044] when When the value is 0, the measured signal and the reference signal waveform are completely uncorrelated, and the signal is completely distorted.

[0045] Correlation signal evaluation includes the following steps: Step A1: Evaluate each associated signal individually, ensuring that all associated signals are undistorted.

[0046] Step A2: At the set associated signal interpretation point, read the occurrence time of the associated signal and compare it. If the time meets the set error requirement, the timing of the associated signal is correct; otherwise, the timing is abnormal.

[0047] The evaluation conclusion output module is used to output the evaluation conclusions through the software interface, such as... Figure 6 As shown, the software evaluation interface displays the name of the aerospace product test signal, the evaluation conclusion of the single test signal curve feature, and the evaluation conclusion of the associated test signal curve. If all signal curves are evaluated correctly, the conclusions "signal normal" and "association correct" are given. If any signal is evaluated abnormally, the conclusions "signal abnormal" and "association abnormal" are given.

[0048] Figure 7 This is a flowchart illustrating the operation of the automated evaluation system for vibration monitoring signals of aerospace products provided by this invention. Figure 7 As shown, the method of using the above-mentioned automated evaluation system for vibration monitoring signals of aerospace products includes the following steps; Step B1: Open and run the "Automatic Evaluation System for Vibration Monitoring Signals of Aerospace Products" software. The software interface is shown in the figure.

[0049] Step B2 leads to the "Parameter Settings" interface. This is the first time a certain type of aerospace product has used the vibration monitoring signal automated evaluation system to configure the signal curve parameters. After configuration, this step is not required for subsequent use.

[0050] Step B3: Click the "Open" button and select the raw data packet of the aerospace product test signal to be evaluated. The software will automatically parse and preprocess the signal data packet.

[0051] Step B4: Click the "Analysis and Evaluation" button. The system will automatically extract the test signal data to be evaluated and the signal model in the parameter configuration library, and perform automatic analysis and evaluation, outputting the evaluation conclusion.

[0052] Step B5: If you need to save the evaluation information, click the "Save" button.

[0053] Step B6: Click the "Stop" button to stop the system.

[0054] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. An automated assessment system for space product vibration monitoring signals, characterized in that, Comprise: The original signal analysis module is used for parsing unreadable original data packet into program readable data packet; The data preprocessing module is used for filtering and eliminating the starting time error of the measured signal data after analysis; The signal parameter configuration module contains single signal characteristic parameter and associated signal parameter configuration, forming parameter configuration library; The signal interpretation evaluation module is used for evaluating the preprocessed signal curve according to the preset parameter requirements in the parameter configuration library, which includes single signal characteristic evaluation and associated signal evaluation; The evaluation conclusion output module is used for giving the evaluation conclusion of the evaluated signal according to the output result of the signal interpretation evaluation module, and displaying on the evaluation system software interface.

2. The automated assessment system of a space product vibration monitoring signal according to claim 1, characterized in that, The original signal analysis module parses the original data format as binary data stream format, including.DAT or TDMS file, and the parsed data is readable.txt file.

3. The automated space product vibration monitoring signal evaluation system of claim 1, wherein, The data preprocessing module aligns all signal data at the same time starting point and removes burrs or interference signals.

4. The automated space product vibration monitoring signal evaluation system of claim 1, wherein, In the signal parameter configuration module, the signal type corresponding to the single signal characteristic parameter includes pulse signal, step signal and periodic signal.

5. The space product vibration monitoring signal automatic evaluation system of claim 4, wherein The parameters required to be set for the pulse signal include pulse starting time, level amplitude, pulse width, pulse interval time, signal sampling rate and sampling time; The parameters required to be set for the step signal include signal occurrence time, trigger slope, initial voltage, trigger voltage, signal sampling rate and sampling time; The parameters required to be set for the periodic signal include waveform type, waveform amplitude, period or frequency, starting phase, signal sampling rate and sampling time.

6. The automated space product vibration monitoring signal evaluation system of claim 1, wherein, In the signal parameter configuration module, the associated signal parameter is used for setting the interpretation characteristic point, timing relationship and allowable error between the associated signals.

7. The automated space product vibration monitoring signal evaluation system of claim 1, wherein, The signal interpretation evaluation module includes: According to the parameter name and parameter type, the parameters in the parameter configuration library are called, and the reference signal is generated according to the parameter characteristics; The measured signal and the reference signal are correlated, and the normalized result is obtained based on the de-meaning and normalization processing, so as to reflect the similarity between the measured signal and the reference signal.

8. The automated space product vibration monitoring signal evaluation system of claim 7, wherein, The cross-correlation operation adopts the formula: wherein, is the cross-correlation output result, is the measured signal, is the reference signal, n is the time axis shift position, and N is the signal sample length. The de-meaning and normalization processing adopts the formula: wherein is the input signal mean, is the reference signal mean, is the cross-correlation normalized output result.

9. The automated space product vibration monitoring signal evaluation system of claim 1, wherein, The signal interpretation evaluation module includes: The associated signals to be evaluated are evaluated one by one, and it is confirmed that all the associated signals are not distorted; At the set interpretation point of the associated signal, the occurrence time of the interpretation point associated signal is read and compared, if the set timing requirement and error requirement are met, the timing of the associated signal is correct, otherwise the timing is abnormal.

10. The automated assessment of space product vibration monitoring signals system of claim 1, wherein, The evaluation conclusion output module displays the space product test signal name, single test signal curve characteristic evaluation conclusion and associated test signal curve evaluation conclusion on the software evaluation interface, and gives the "signal normal" and "association correct" conclusions when all the signal curves are evaluated correctly, and gives the "signal abnormal" and "association abnormal" conclusions when there is signal evaluation abnormality.

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