A Method for Extracting Feature Information of Fault Signals of Aeroengine Rotor System

Abstract

The invention discloses a method for extracting the fault signal feature information of an aero-engine rotor system, and the method comprises the steps: collecting a rotor rub-impact vibration signal,and carrying out the FDM decomposition of the collected rotor rub-impact vibration signal to obtain complete rotor rub-impact vibration signal FIBFs components; constructing a Hankel matrix of the rotor rub-impact vibration signal after noise reduction, and drawing a singular value curve of the rotor rub-impact vibration signal after noise reduction; determining a singular value catastrophe point, carrying out the reconstruction of an order number, and carrying out the envelope spectrum analysis, thereby achieving the effective extraction of fault information. According to the invention, themethod achieves the reasonable extraction of the fault feature frequency of a rotor system based on the FDM decomposition and singular value differential spectrum analysis, and achieves the efficientfiltering of the noise signal component in the rub-impact vibration signal, thereby achieving the extraction of the weak fault feature information from the low-frequency strong noise background, and achieving the effective extraction of the fault information.

Description

technical field [0001] The invention relates to a method for extracting feature information of signals, in particular to a method for extracting feature information of fault signals of an aeroengine rotor system. Background technique [0002] The aircraft engine is the heart of the aircraft. It is the system with the highest failure rate, the most complicated adjustment and the largest maintenance workload in the aviation machinery equipment. The quality of its working status directly affects the safety, reliability and operation of the aircraft. Once the engine fails during operation, it may cause the aircraft to fail to fly normally, endanger personal safety, and cause significant social and economic losses. [0003] According to statistics, the failure rate of aero-engines accounts for about 30% of all aircraft failures, and about 40% of major flight accidents due to mechanical reasons are caused by engine failures. Engines are different from general machinery due to thei...

AI Technical Summary

Problems solved by technology

[0005] These methods have made some contributions to the fault diagnosis and signal feature extraction of the aero-engine rotor system. The operating state of the system is not comprehensive enough

[0006] At the same time, the patent with the authorized announcement number of CN101968379B and the patent application with the application publication number of CN107506709A respectively disclose two methods for extracting characteristic information of the fault signal of the rotor system of the aeroengine. Both methods use the eddy current displacement sensor to measure the vibration signal , and use wavelet clustering with different ideas to analyze, mine hidden feature information from a large number of vibration displacement signals, and realize the extraction of working condition features. The former method still has certain deficiencies in the extraction accuracy and speed, and the latter An extraction method has made a breakthrough improvement on the basis of the former, but it still has a common problem with the former, that is, the noise background spectrum cannot be effectively filtered out in the extraction results, and the weak fault feature information and The frequency spectrum impact amplitude of fault feature information is close, which affects the reasonable extraction of rotor fault features to a certain extent. make further improvements

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