Early failure mechanism research of electromechanical product based on meta-action

Early failure is the key factor that restricts the improvement of electromechanical product reliability. The research on early failure mechanism of electromechanical product can provide a basis for the subsequent failure cause tracing and failure diagnosis. At present, there are few systematic studies on the early failure mechanism of electromechanical product, which have the following shortcomings: firstly, the failure analysis objects in traditional failure methods cannot reflect the characteristic of electromechanical product that motion determination electromechanical product function; secondly, traditional failure analysis methods ignore the fact that mechanical and electronic systems are different in failure cause, failure mode and failure mechanism; thirdly, failure cause and failure mode are easily confused in traditional methods; finally, most of the traditional methods are qualitative analysis, which cannot directly show the generation process of failure. To address those problems, meta-action and meta-action unit of electromechanical product are selected as the analysis object herein. Early failure mode, early failure cause, and early failure mechanism of electromechanical product are defined and analyzed. A meta-action early failure mechanism quantitative analysis model considering electromechanical coupling is built, and the influence of failure cause on failure mode is analyzed. A CNC (computer numerical control) machine tool made in China is taken as an example. The results verify the applicability and correctness of the proposed method.

Automated summary

Early failure is a key factor limiting the improvement of electromechanical product reliability. However, there are shortcomings in the research on early failure mechanism, including the inability of traditional methods to reflect the characteristics of electromechanical products, ignorance of differences between mechanical and electronic systems, confusion between failure causes and modes, and lack of quantitative analysis capabilities.