Denoising method for fault vibration signal of aeroengine rotor system

Abstract

The invention discloses a denoising method for a fault vibration signal of an aeroengine rotor system. The method comprises the steps that an anti-vibration vibration signal of an aeroengine rotor iscollected, and repeated row filtering processing and threshold value optimalizing are carried out on the signal; the suboptimal solution found by particle swarm optimization through iterative optimization is assigned to the initial solution in a tabu search algorithm; the fitness value is calculated; by continuously searching the neighborhood of the initial value; and a taboo table and a special pardon criterion are flexibly used at the same time, so that the tabu search algorithm can accept some low-quality inferior solutions to a certain extent. The algorithm is prevented from falling into local extremum. The global optimization ability of the algorithm is enhanced. The problem that particle swarm optimization slows down at the later stage is effectively solved. In comparison, although the convergence speed of hybrid particle swarm optimization has a certain decline, a group is effectively prevented from falling into the local optimal solution too early. The possibility of finding the global optimal solution for the group is improved. The optimization performance of the algorithm is improved as a whole.

Description

technical field [0001] The invention relates to a method for extracting signal feature information, in particular to a method for denoising a fault vibration signal of an aeroengine rotor system. Background technique [0002] With the continuous development and progress of modern science and technology, on the one hand, rotating machinery is developing towards high speed and high efficiency, and at the same time, it is facing the challenges of more demanding working and operating environments, which leads to a corresponding increase in the potential risk of failure. The core component rotor system is one of the parts with the highest failure rate. Especially the aero-engine rotor system of the aircraft is the system with the highest failure rate, the most complicated adjustment and the largest maintenance workload in the aeromechanical equipment, and its working status directly affects the safety, reliability and operation of the aircraft; Faults during operation may cause ...

AI Technical Summary

Problems solved by technology

[0005] 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 aeroengine rotor system. Both methods use the eddy current displacement sensor to measure the vibration signal, and Wavelet clustering with different concepts is used for analysis, and hidden feature information is mined from a large number of vibration displacement signals to realize the extraction of working condition features. The former method still has certain deficiencies in extraction accuracy and speed, and the latter method The extraction method has made a breakthrough improvement on the basis of the former one, 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 fault feature The impact amplitude of the information frequency spectrum is close, which affects the reasonable extraction of rotor fault features to a certain extent. Therefore, in order to remove noise interference and more reasonably diagnose and signal feature extraction of aeroengine rotor system faults, further research needs to be done in other directions. improvement; therefore, the noise reduction research on the fault vibration signal of the rotor system is of great significance to prevent the occurrence of sudden major accidents

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