High-speed automaton fault diagnosis method based on movement patterns and impact signal analysis

Abstract

The invention discloses a high-speed automaton fault diagnosis method based on movement patterns and impact signal analysis, which aims at automatic fault diagnosis, warning and forecasting. The method comprises the following steps of: selecting three testing points including the point in front of a case, the point in the case and the point behind the case, and testing the impact vibration generated by the high-speed actions and a hitting process of a cannon automaton through a high temperature resistant acceleration transducer; using a computer DASP (dynamic adaptive speculative preprocessor) system to acquire and record three groups of impact acceleration response signals at positions of the three testing points; preprocessing the signals with zero mean, filtering, re-sampling and outlier deletion; performing time domain analysis on the impact signals, and forming an expert rule according to the movement patterns, wherein the expert rule is used for identifying states of main components of the automaton; and performing frequency domain short-time Fourier transform analysis and entropy-spectrum analysis on the impact response signals after widening, building a neural network model according to inherent characteristics and movement patterns of each component of the automaton to identify network training classes, and diagnosing faults of the automaton through a three-layer BP neural network trained by a particle swarm optimization proportion gradient momentum conjugation algorithm.

Description

technical field [0001] The invention relates to the field of high-speed automaton impact signal analysis and fault diagnosis. Specifically, it is a technology for the high-speed impact action of various mechanisms in the high-speed automaton, arranging measuring points at appropriate positions outside the chassis to measure the impact response signal, and performing data analysis and fault diagnosis according to the movement form of the automaton. Background technique [0002] The scientific and technological content of current military equipment is getting higher and higher, but the maintenance and support methods are relatively backward. The traditional method uses listening, touching, watching and frequent dismantling and dismantling. The maintenance cost is high, the cycle is long, and subject to subjective factors. The interference easily causes misdiagnosis and missed diagnosis, which is far from meeting the needs of reality. The automaton of the high-firing antiaircr...

AI Technical Summary

Problems solved by technology

[0002] The scientific and technological content of current military equipment is getting higher and higher, but the maintenance and support methods are relatively backward. The traditional method uses listening, touching, watching and frequent dismantling and dismantling. The maintenance cost is high, the cycle is long, and subject to subjective factors Interference easily leads to misdiagnosis and missed diagnosis, which is far from meeting the needs of reality

The automaton of the high-firing antiaircraft gun in the experiment was prone to failure due to manufacturing and assembly errors and harsh working conditions (such as excessive load, high-speed impact, poor lubrication)

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