Multi-parameter joint diagnosis method for typical faults of asynchronous motor

Abstract

The invention relates to a multi-parameter joint diagnosis method for typical faults of an asynchronous motor. The method comprises the following steps of firstly, acquiring temperature, current waveform data, vibration speed data and current data of the asynchronous motor under a load during normal operation at intervals after a system is started and operates stably, acquiringdata of a time axisenvelope line according to the data to serve as judgment parameters for normal operation of the asynchronous motor, takingthe ratio of two groups of amplitude average values before and after online monitoring operation as a fault judgment parameter of the vibration signal,wherein the ratio of the maximum value of the current amplitude envelope data to the rated current value input by the motor isused as a judgment parameter of the current time domain fault, and the maximum value of the frequency band variation of the current data spectrum result and the current amplitude average value is weighted and averaged to be used as a fault diagnosis parameter under the motor current spectrum,and finally, continuously acquiring temperature, current waveform data, vibration speed data and current data of the asynchronous motor during operation, and realizing comprehensive evaluation of operation parameters, operation states and service life conditions.

Description

technical field [0001] The invention belongs to the technical field of motor fault diagnosis, and in particular relates to a multi-parameter joint diagnosis method for a typical fault of an asynchronous motor. Background technique [0002] With the deepening of Industry 4.0 worldwide, from the perspective of my country's national policy orientation and industrial development direction, industrial development is developing in a more intelligent direction. And with the improvement of the quality of human life, some repeatable and cumbersome workflows will be replaced by real-time detection and self-diagnosis equipment. As the motor is widely used in industrial production and an indispensable bottom-level operating actuator, its intelligence level also directly reflects and affects the development process of industrial intelligence. The intelligence of the motor can be started from two aspects, one is the flexibility and high efficiency of its own control and execution; the ot...

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Problems solved by technology

For example: ABB company has a device that obtains motor information based on vibration, but through experiments, its readiness is not enough, and it is still in the stage of obtaining data to optimize the system

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