Tribological state online identification method based on friction signal recursive characteristics

Abstract

The invention discloses a tribological state online identification method based on friction signal recursive characteristics. The method comprises the following steps that: friction vibration signalsin a friction and wear process are collected through an acceleration sensor installed on the side edge of a clamp on a sliding friction and wear testing machine and are expressed as X=[x (1), x (2),..., x (t),..., x (n)]; nonlinear feature extraction is carried out ton the obtained friction vibration signals and a quantitative recursion parameters of the signals are extracted; feature extraction is carried out on the extracted quantitative recursive parameters, and a feature parameter set which has been subjected to dimension reduction and obtained by processing is adopted as a characterization quantity of the recursive characteristic of the friction signals; a system-dependent polynomial fitting equation of the characteristic parameter set relative to friction control parameters is established, and the polynomial fitting equation is made to predict the recursive characteristic parameters of the friction vibration signals under different control parameter conditions and by means of nonlinear mapping and mathematical modeling capability of self-organized data mining; and the frictional wear state of the actually measured friction signals is accurately identified. According to the method of the invention, the tribological state of a sliding friction pair can be effectively monitored and identified.

Description

technical field [0001] The invention relates to an online tribological state identification method based on the recursive characteristics of friction signals, belonging to the field of tribological state identification. Background technique [0002] Wear surfaces, friction signals, and abrasive particles (wear debris) produced during the wear process are all important products during the operation of the tribological system. Important reference. However, for continuously operating mechanical equipment, the wear surface morphology cannot be obtained directly; and the collection and analysis of abrasive particles also need to be assisted by steps such as oil cultivation and spectrum preparation, which cannot meet the real-time requirements. Therefore, it is urgent to establish an effective tribological state identification method based on friction signals, in order to realize the online tribological state identification of mechanical equipment by making full use of the fricti...

AI Technical Summary

Problems solved by technology

However, traditional geometric invariants such as correlation dimension are limited by the length of data in the characterization process, which makes it difficult to meet the needs of real-time characterization and monitoring. Tribological state identification results

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