CN114348291A - Flight fault diagnosis method based on flight parameter data and simulation - Google Patents
Flight fault diagnosis method based on flight parameter data and simulation Download PDFInfo
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- 238000003745 diagnosis Methods 0.000 title claims abstract description 19
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- RZVHIXYEVGDQDX-UHFFFAOYSA-N 9,10-anthraquinone Chemical compound C1=CC=C2C(=O)C3=CC=CC=C3C(=O)C2=C1 RZVHIXYEVGDQDX-UHFFFAOYSA-N 0.000 claims abstract description 21
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- 230000002159 abnormal effect Effects 0.000 claims abstract description 5
- 238000010219 correlation analysis Methods 0.000 claims abstract description 4
- 238000004132 cross linking Methods 0.000 claims abstract description 4
- 238000007781 pre-processing Methods 0.000 claims abstract description 3
- 238000012216 screening Methods 0.000 claims abstract description 3
- 238000012545 processing Methods 0.000 claims description 5
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- 230000001360 synchronised effect Effects 0.000 claims description 2
- 238000004458 analytical method Methods 0.000 abstract description 8
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Abstract
The invention relates to the technical field of flight fault diagnosis, in particular to a flight fault diagnosis method based on flight parameter data and simulation, which comprises the following steps: analyzing and preprocessing airborne flight parameter data through flight parameter software, and converting the airborne flight parameter data into available flight parameter sequence data; importing the flight parameter sequence data into a flight control simulation test bed, wherein airborne equipment of the flight control simulation test bed corresponds to the state of an aircraft model output by an input signal in the flight parameter sequence data; and performing correlation analysis and data comparison on simulation test parameters output by the flight control simulation test bed and flight parameter data, screening abnormal points, and realizing primary fault diagnosis. The invention can verify the failure reason obtained by data analysis, and is suitable for the analysis of multi-point failure and cross-linking; the method is not limited by the influence of a safe flight library and a database; the flight process can be reproduced, and simultaneously, the flight process can be interrupted, and the physical signals of the airborne equipment can be detected on line.
Description
Technical Field
The invention relates to the technical field of flight fault diagnosis, in particular to a flight fault diagnosis method based on flight parameter data and simulation.
Background
The research of the flight fault of the airplane has great significance for the maintenance of the airplane. Flight parameter data reflects the state of various parts of the aircraft, including avionics bus data, weapons bus data, flight data, and the like. Through the analysis and the processing of the flight data in the flight parameter data and the correlation thereof, the method can provide help for the fault diagnosis, the investigation and the analysis of the flight control system of the airplane. The flight control simulation test bed comprises semi-physical simulation and full-digital simulation, and can realize the simulation of the whole process from take-off to landing of the airplane. The method comprises the following steps that at present, three types of research modes of airplane flight faults are provided, firstly, analysis and pretreatment are carried out on flying parameter data after flight, the flying parameter data are processed and abandoned through various algorithms, and the faults of products are judged; secondly, the flight parameter data are transmitted to the platform through the data chain in real time during flight, the data are trained and learned through the platform, and faults are judged in advance; thirdly, flight faults are simulated on a flight simulation platform, a response processing method is given according to the faults, and subsequent operation of the pilot is guided.
The article proposes that a multivariate linear regression algorithm is utilized to process and simulate a historical data segment related to a flight parameter record aiming at the characteristics of poor repeatability of output errors and the like of an airborne sensor, and assists in judging sensor faults and determining the calibration time of the sensor.
The method for evaluating the faults of the airplane control system based on flight parameter data is disclosed in 'computer measurement and control' published in 2019, volume 27, No. 7, No. 275-279, aiming at the problem of evaluating the faults of the control system of a certain airplane, the flight parameter data is trained to construct a black box model of the airplane control system; therefore, fault evaluation of the airplane control system is realized. Both papers discuss post-flight parameter data for fault analysis. Both papers discuss that the flight parameter data is used for data processing and data analysis to obtain a fault reason, but the reason cannot be returned to an airplane or a system for fault verification, and only a single fault point can be targeted, and systematic multi-point trigger fault analysis is difficult.
A patent CN201910647276.1 discloses an airborne flight parameter data diagnosis method based on deep learning, which can analyze data acquired by an airborne flight parameter device in real time to obtain the health condition of an airplane in the flying process and predict the risk of the airplane failure in advance. The deep learning method applied by the patent extremely depends on the safe flight library and the fault library, and has limitation on fault analysis of the primary aircraft or a small number of secondary aircraft.
Patent "a flight fault determination method based on simulation" (patent No. CN201510843787.2) discloses a flight fault determination method based on simulation, which simulates flight faults on a flight simulation platform and guides subsequent pilot operation according to a processing method of giving response to the faults. The patent is to carrying out fault analysis and judgement through telemetering measurement data to aircraft flight in-process simulation platform, to after the flight takes off and land, can't do semi-physical simulation to airborne equipment, the special dynamic acquisition of equipment physical signal.
Disclosure of Invention
In order to solve the technical problem, the invention provides a flight fault diagnosis method based on flight parameter data and simulation.
The technical problem to be solved by the invention is realized by adopting the following technical scheme:
a flight fault diagnosis method based on flight parameter data and simulation comprises the following steps:
(S1) airborne flight parameter data are analyzed and preprocessed through flight parameter software, and are converted into usable flight parameter sequence data;
(S2) importing the flight parameter sequence data into a flight control simulation test bed, wherein the airborne equipment and the airplane model of the flight control simulation test bed correspond to the state of outputting the input signal in the flight parameter sequence data to the airplane model;
(S3) performing correlation analysis and data comparison on the simulation test parameters output by the flight control simulation test bed and the flight parameter data, screening abnormal points, and realizing primary fault diagnosis;
(S4) aiming at an abnormal point or a state of a certain fault airplane, one or more airborne equipment is/are placed into the whole flight control simulation test bed to perform semi-physical simulation, cross-linking signals of the certain airborne equipment or among the airborne equipment are tested, and the fault is verified.
Preferably, the flight parameter data in step (S1) includes a steering column stem signal, a steering column beam signal, a foot pedal signal, a barometric altitude signal, a corrected airspeed signal, a left/right platband position signal, a left/right flaperon position signal, a left/right rudder position signal, a pitch rate signal, a lateral rate signal, a yaw rate signal, a normal overload signal.
Preferably, the specific process of analyzing and preprocessing the airborne flight parameter data in the step (S1) is as follows: the method comprises the steps of firstly analyzing, selecting a flight stage to be analyzed, identifying and eliminating singular data points, eliminating interference noise in flight parameter data, and carrying out interpolation smoothing processing on the data.
Preferably, in the step (S2), the flight control simulation test bed uses a reflective memory network, and the flight parameters are synchronized to the reflective memory network.
The invention has the beneficial effects that:
the method adopts a flight parameter data and flight control simulation fault diagnosis mode, compared with the method based on pure flight parameter data, the method can verify the fault reason obtained by data analysis, and meanwhile, the method can be suitable for analyzing multipoint faults and crosslinking; by adopting the semi-physical simulation mode of the flight control simulation test bed based on the flight parameter data, a small amount of flight data can be subjected to data analysis, and compared with a fault judgment method based on deep learning, the method is not limited by the influence of a safe flight library and a database; by the method of combining the real flight parameter data and the flight control simulation test bed, the flight process can be reproduced, the flight process can be interrupted, and the physical signals of the airborne equipment can be detected on line.
Drawings
The invention is further illustrated with reference to the following figures and examples:
FIG. 1 is a diagnostic flow chart of the present invention.
Detailed Description
In order to make the technical means, the creation features, the achievement purposes and the effects of the invention easy to understand, the invention is further explained in the following with the accompanying drawings and the embodiments.
As shown in fig. 1, a flight fault diagnosis method based on flight parameter data and simulation includes the following steps:
the method comprises the following steps of analyzing flight parameters of a certain flight through flight parameter software: steering column longitudinal rod signals, steering column cross rod signals, pedal signals, air pressure height signals, corrected airspeed signals, left/right horizontal tail position signals, left/right flaperon position signals, left/right rudder position signals, pitching speed signals, transverse speed signals, yawing speed signals, normal overload signals and other signals.
And step two, analyzing the analyzed flight parameter data, selecting a flight stage to be analyzed, identifying and eliminating singular data points, eliminating interference noise in the flight parameter data, and performing interpolation smoothing processing on the data to form available flight parameter sequence data.
And step three, sharing the data of the flight control simulation test bed by using a reflective memory network, synchronizing the flight parameter sequence data obtained in the step two into the reflective memory network, and operating a flight control simulation test airplane model to obtain simulation test data.
And fourthly, carrying out correlation analysis and data comparison on the simulation test data and the flight parameter data, comparing a steering column longitudinal rod signal, a steering column transverse rod signal, a left/right horizontal tail position signal, a left/right flap position signal and a left/right direction rudder position signal, finding that the corresponding relation between the steering column longitudinal rod signal and a horizontal tail steering engine in the two groups of data is inconsistent in the takeoff stage, and preliminarily judging that the electric transmission computer fails or the takeoff and landing signal is not transmitted.
And fifthly, aiming at the inconsistent situation, putting the telex system and the peripheral signals into the whole flight control simulation test bed to perform semi-physical simulation again, and finally obtaining the problem of the landing gear switch, thereby obtaining the purpose of verifying the fault.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are merely illustrative of the principles of the invention, but that various changes and modifications may be made without departing from the spirit and scope of the invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (4)
1. A flight fault diagnosis method based on flight parameter data and simulation is characterized in that: the method comprises the following steps:
(S1) airborne flight parameter data are analyzed and preprocessed through flight parameter software, and are converted into usable flight parameter sequence data;
(S2) importing the flight parameter sequence data into a flight control simulation test bed, wherein the airborne equipment and the airplane model of the flight control simulation test bed correspond to the state of outputting the input signal in the flight parameter sequence data to the airplane model;
(S3) performing correlation analysis and data comparison on the simulation test parameters output by the flight control simulation test bed and the flight parameter data, screening abnormal points, and realizing primary fault diagnosis;
(S4) aiming at an abnormal point or a state of a certain fault airplane, one or more airborne equipment is/are placed into the whole flight control simulation test bed to perform semi-physical simulation, cross-linking signals of the certain airborne equipment or among the airborne equipment are tested, and the fault is verified.
2. The flight fault diagnosis method based on flight parameter data and simulation as claimed in claim 1, wherein: the flight parameter data in the step (S1) includes a steering column longitudinal bar signal, a steering column lateral bar signal, a foot pedal signal, an air pressure altitude signal, a corrected airspeed signal, a left/right horizontal tail position signal, a left/right flap position signal, a left/right rudder position signal, a pitch rate signal, a lateral rate signal, a yaw rate signal, and a normal overload signal.
3. The flight fault diagnosis method based on flight parameter data and simulation as claimed in claim 1, wherein: the specific process of analyzing the airborne flight parameter data and preprocessing the data in the step (S1) is as follows: the method comprises the steps of firstly analyzing, selecting a flight stage to be analyzed, identifying and eliminating singular data points, eliminating interference noise in flight parameter data, and carrying out interpolation smoothing processing on the data.
4. The flight fault diagnosis method based on flight parameter data and simulation as claimed in claim 1, wherein: in the step (S2), the flight control simulation test bed adopts a reflective memory network, and the flight parameters are synchronized to the reflective memory network.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117446203A (en) * | 2023-10-26 | 2024-01-26 | 中航通飞华南飞机工业有限公司 | 429 bus general aircraft avionics cross-linking fault test method |
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