An aero-generator fault feature extraction method based on iSDAE

A technology of fault features and extraction methods, applied in the direction of motor generator testing, etc., can solve the problems of large noise interference, low diagnosis accuracy, time-consuming and laborious, etc., to achieve good robustness, improve fault diagnosis accuracy, The effect of improving the accuracy

Active Publication Date: 2017-02-22
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

However, the current feature extraction methods generally rely on manual extraction, which is time-consuming and labor-intensive, is greatly affected by noise interference, and is not universal. In view of the limitation of manual extraction features in the existing fault diagnosis technology, the diagnostic accuracy is not high. High problem, the present invention proposes an iSDAE-based aviation generator fault feature extraction method, the method can automatically learn the data features, obtain the distributed feature representation of the original data, and has a certain anti-noise ability, has a very Good robustness, effectively improving the accuracy of aircraft generator fault diagnosis

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  • An aero-generator fault feature extraction method based on iSDAE
  • An aero-generator fault feature extraction method based on iSDAE
  • An aero-generator fault feature extraction method based on iSDAE

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Embodiment Construction

[0025] The technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings. Such as figure 1 As shown, a specific implementation of an iSDAE-based aviation generator fault feature extraction method is as follows:

[0026] (1) Failure analysis. Carry out failure mode, impact and hazard analysis on the aero-generator to determine the failure mode of the aero-generator and the diagnostic signals to be collected. After analysis, the main failure modes of aeronautical generators are rotating rectifier failure, rotor winding failure, stator winding failure, shaft and bearing failure, etc. The diagnostic signals to be collected are the output voltage signal of the main generator, the excitation current signal of the AC exciter, the fuselage Vibration signal and shaft torque signal.

[0027] (2) Data collection. The fault simulation experiment is carried out on the generator fault simulation experiment platform, and the f...

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Abstract

The invention discloses an aero-generator fault feature extraction method based on iSDAE (improved Stacked Denoising Auto-Encoderes), and is mainly to solve the problem of not high diagnosis accuracy since the existing fault diagnosis technology is limited by artificial feature extraction. The method has the following specific steps: 1) fault analysis; 2) data acquisition; 3) data pre-processing; 4) training of the iSDAE (improved Stacked Denoising Auto-Encoderes); and 5) feature output. The method can learn data features automatically and obtains distributed feature representations of original data, has a certain noise immunity and good robustness and effectively improves aero-generator fault diagnosis correct rate.

Description

technical field [0001] The invention relates to an iSDAE (improved Stacked Denoising Autoencoders, improved stack denoising autoencoder)-based method for extracting fault features of an aero-generator, belonging to the technical field of generator state monitoring and fault diagnosis. Background technique [0002] The aviation generator is an important part of the main power supply of the aircraft. It is responsible for providing power for the instruments, meters, radar, lighting, radio communications and various control systems on the aircraft. Failure of any part of the aero-generator will not only affect its normal operation, but also may cause the aircraft to fail to fly normally, and even cause major aviation accidents in severe cases. Therefore, it has extremely important practical significance and huge economic benefits to carry out in-depth research on the fault diagnosis technology of aero-generators, make timely, accurate and rapid judgments on possible faults of a...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/34
CPCG01R31/34
Inventor 崔江唐军祥张卓然
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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