Fault diagnosis method and apparatus for rolling bearing

Abstract

The embodiments of the invention provide a fault diagnosis method and apparatus for a rolling bearing. The fault diagnosis method for the rolling bearing comprises the following steps: acquiring vibration signals of the rolling bearing, and solving a time-frequency spectrum of the vibration signals; according to the time-frequency spectrum, determining an optimal order component of the vibration signals; according to the optimal order component, performing angle re-sampling on the vibration signals to obtain angle domain signals; and performing envelope analyzing on the angle domain signals, and determining fault positions of the rolling bearing, wherein determination of the optimal order component comprises: setting an equivalent frequency conversion scope and searching for all order components from the time-frequency spectrum; and calculating order energy of the order components and determining the optimal order component from the equivalent frequency conversion scope. The fault diagnosis method and apparatus for the rolling bearing realize automatic and rapid determination of the optimal order component so as to provide a basis for fault diagnosis of the rolling bearing, improve the fault diagnosis accuracy and avoid interference of manual factors.

Description

technical field [0001] The invention relates to the technical field of mechanical fault monitoring, in particular to a fault diagnosis method and device for rolling bearings. Background technique [0002] In industrial applications, rolling bearings are vulnerable parts as well as critical monitoring components, and thus require fault diagnosis. Taking the rolling bearing of a wind turbine as an example, due to the low speed of the main shaft of the direct drive wind turbine, the fault characteristic frequency of the rolling bearing is in a low frequency band, and the early fault characteristics are relatively weak. In addition, due to large changes in wind speed, wind turbines generally work under variable speed conditions, which increases the difficulty of rolling bearing fault diagnosis. [0003] The order analysis technique is a common method to solve the fault diagnosis of rolling bearings under the condition of variable speed. Specifically, the rotational speed signa...

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Problems solved by technology

[0004] However, the above method has the following disadvantages: firstly, the hardware order and calculation order cannot get rid of the hardware dependence; secondly, the common instantaneous frequency estimation method needs to artificially set the peak search curve, and the artificial interference factors are too large. Weak early faults with variable speed cannot achieve accurate feature extraction, which in turn makes the accuracy of fault diagnosis low

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