Aero-engine bearing fault diagnosing method

A technology for aero-engine and fault diagnosis, which is used in mechanical bearing testing, mechanical component testing, and machine/structural component testing. performance, improving accuracy, and precise identification

Active Publication Date: 2017-08-11
CHONGQING TECH & BUSINESS UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to provide a fault diagnosis method for aero-engine bearings, which aims to solve the problem that in the current fau

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[0034] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0035] The present invention monitors the working state of the turbojet engine in real time, collects five kinds of signals including vibration signal, engine speed, engine exhaust temperature, fuel flow, and engine thrust, and adopts deep wavemantz to the collected signals in various modes. After feature extraction, the data fusion technology is adopted to fuse the state features of various modes as the basis for fault diagnosis.

[0036] The application principle of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0037] like figure 1 As shown, the aeroengine beari...

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Abstract

The invention discloses an aero-engine bearing fault diagnosing method. The method comprises: first, acquiring the vibration signal of a turbojet engine, the engine speed, the engine rotation speed, the engine exhaust temperature, the fuel flow, and the engine thrust; extracting the classical time-domain statistical characteristics, the frequency-domain characteristics of the various signals and obtaining the time-frequency domain characteristics based on wavelet packet decomposition; then using the deep Boltzmann machine to perform characteristics learning to the characteristic parameters of the various signals; then, proceeding to use the data integration technology to integrate the characteristics of the various sources learned by the deep Boltzmann machine; and finally, using the integrated characteristic parameters as the input of the classifier to the support vector machine, and classifying and identifying the engine fault. The method of the invention improves the identification precision and stability of the turbojet engine bearing fault, effectively mining the essential characteristics of data and greatly increasing the fault precision of the turbojet engine bearing.

Description

technical field [0001] The invention belongs to the technical field of engine fault diagnosis, and in particular relates to an aeroengine bearing fault diagnosis method. Background technique [0002] General aviation activities are developing rapidly in our country. It has been widely used in flight operations in agriculture, forestry, fishery and construction, and is especially active in the fields of emergency rescue and disaster relief, meteorological monitoring, and scientific experiments. The reliability of general aviation aircraft has always been a priority in the aviation industry, because once a failure occurs, the consequences will be disastrous. For general aviation aircraft, predictive maintenance is of great significance in improving aircraft reliability and reducing operation and maintenance costs. The engine is the heart of an aircraft, and it is also the focus of aircraft predictive maintenance. Rolling bearings are one of the most vulnerable components of...

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Application Information

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IPC IPC(8): G01M13/04
CPCG01M13/045
Inventor 陈志强刘传文李川陈旭东刘杰喻其炳白云姚行艳余婷梃
Owner CHONGQING TECH & BUSINESS UNIV
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