Single-channel gearbox multi-fault separation dual-core micro-processing system

Abstract

The invention relates to a single-channel gearbox multi-fault separation dual-core micro-processing system and belongs to the gearbox fault diagnosis technology and signal processing technology field.The system of the invention is the dual-core micro-processing system of DSP and ARM. A DSP core includes a phase space reconstruction parameter estimation module, a phase space reconstruction module,a reconstruction parameter adjustment module, a reconstruction signal separation module, and a Fourier transform module. An ARM core includes a time frequency domain spectrogram drawing module. A time delay reconstruction method is used to expand, which avoids human intervention of a reconstructed signal taking experience as a judgment standard. A principal component analysis method is used to reduce influences of a noise and redundancy in a gearbox on the reconstructed signal. A limited support sample kernel function and FastICA fusion algorithm is used to the estimate a source signal probability density function, and then a nonlinear function according with a statistical characteristic of a source signal is obtained. And finally the signal is effectively separated. In the invention, theinfluence of improper selection of reconstruction parameters and a separated nonlinear function is greatly reduced on the aspect of gearbox multi-fault separation.

Description

technical field [0001] The invention relates to the technical field of gearbox fault diagnosis technology and signal processing and analysis, and relates to a single-channel gearbox multi-fault separation dual-core micro-processing system. Background technique [0002] The gearbox is an important mechanism for mechanical equipment to transmit power, and at the same time, it is also one of the important research objects in mechanical fault diagnosis. Therefore, it is of great significance to carry out research on gearbox fault diagnosis technology to ensure the safe operation of mechanical equipment. The difficulty of fault detection lies in compound faults, and the estimation of the number of compound faults is even more difficult in compound fault diagnosis. In order to grasp the running state of the gearbox, the general acceleration sensor picks up its vibration signal. However, the sensor can only be installed on the outer surface of the gearbox, which leads to the vibr...

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Problems solved by technology

However, there will be wrong choices in the selection of nonlinear functions in the FastICA algorithm, which will make the FastICA algorithm fall into local extremes and make the separation performance worse. Therefore, the selection of nonlinear functions is very important, but it is very difficult.

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