Chaos-based method for detecting and classifying early single-point faults of mechanical component

Abstract

The invention discloses a chaos-based method for detecting and classifying early single-point faults of a mechanical component. The method comprises the following steps of: processing conventional sample fault signals in different states of the mechanical component to establish check intervals for different fault types; acquiring fault characteristic frequencies corresponding to all single-point fault states of the mechanical component to construct a frequency matrix of a Duffing chaotic oscillator; solving critical thresholds of periodic driving force amplitudes corresponding to different fault characteristic frequencies to construct a frequency-threshold matrix; and finally, adding a signal to be detected to calculate the maximum Lyapunov exponent matrix M, checking according to data inthe M, calculating correlation dimension of the signal to be detected if a fault signal is available, and classifying the faults to determine a fault mode in comparison with the established correlation dimension intervals for different fault types. By adopting the method, the early single-point faults of the mechanical component are detected and classified; and the method has high noise resistance capacity and extremely high fault detection success rate.

Description

technical field [0001] The invention relates to a chaos-based early single-point fault detection and classification method for mechanical parts, belonging to the technical field of fault diagnosis of mechanical parts. Background technique [0002] In modern industrial production, production equipment is developing in the direction of large-scale, complex, high-speed, automated and intelligent. Not only are the different parts of each equipment related to each other and tightly coupled, but there are also close connections between different equipment. Contact, forming a complete system during the operation of the equipment. For those large and complex electromechanical equipment that is usually difficult to grasp its operating status intuitively, whether the normal operation of some key equipment can be guaranteed is directly related to all levels of an enterprise's development. Serious or even catastrophic casualties and social impact will be produced. Since complex and ad...

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Problems solved by technology

[0005] The purpose of the present invention is to solve the problems of low detection success rate and difficulty in realizing early prediction in existing methods when detecting and classifying early single-point failures of mechanical parts, and the method of directly observing the phase trajectory has low work efficiency and cannot be automatically detected problems, as well as a large number of manual frequency adjustments and high professional requirements when using the Lyapunov index method for fault classification, combined with the respective advantages of the two detection methods of the Lyapunov index and the correlation dimension, a chaos-based mechanical Early single-point fault detection and classification method for components

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