A method for identification of rolling bearing fault damage degree

Abstract

The invention discloses a method for identifying the fault damage degree of a rolling bearing, which respectively includes fault vibration signal collection, calculation of the gradient spectrum value of the mathematical form, calculation of the change rate of the gradient spectrum value of the mathematical form, determination of the optimal scale range of the structural element, and calculation of the high-order differential mathematical form Gradient spectrum value, calculation of high-order differential mathematical form gradient spectrum entropy value, definition of fault damage degree discrimination, calculation of fault damage degree discrimination degree and judgment of fault damage degree are several steps. The invention can effectively identify the damage degree of the fault of the inner ring of the bearing, has a higher recognition accuracy rate of the damage degree, and can greatly improve the efficiency of identification. The identification of damage degree and fault prediction provides a new method, which is practical and worthy of popularization.

Description

technical field [0001] The invention belongs to the technical field of fault detection of mechanical parts, and in particular relates to a method for identifying the fault damage degree of a rolling bearing. Background technique [0002] Rolling bearings are important components in rotating machinery. Working in harsh environments for a long time, under the joint influence of load bearing, transmission, impact and other loads, they are prone to failures such as bearing fatigue spalling, pitting, and severe plastic deformation in the contact area, which in turn leads to machine failure. Accidents such as breakage and outage occur frequently, so it is very necessary to carry out fault monitoring, state analysis and diagnosis of rolling bearings. [0003] The evolution of bearing faults has a development process from mild to severe, and fault quantitative diagnosis is an effective description method to realize the fault evolution process. Existing diagnostic methods can be sum...

AI Technical Summary

Problems solved by technology

Most of these analysis methods are qualitative analysis of bearing faults, that is, to determine whether the fault exists and the type of fault, while the research on quantitative diagnosis of bearing faults, that is, to determine the degree of fault damage and the remaining life is relatively small, and traditional mathematics The shape spectrum is difficult to accurately describe the shape complexity of the signal, and the insufficient ability to distinguish fault modes leads to unsatisfactory identification of fault damage degrees.

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