A method and system for predictive maintenance based on motor parameters

Abstract

The invention discloses a method and system for predictive maintenance based on motor parameters. The invention starts from the local operating conditions of the motor, collects two non-electrical acquisition parameters that are not directly related to the temperature and vibration of the motor for cross calculation, and uses a matrix The eigenvalue vector maps the real-time working state of the motor, which can realize the functional relationship between temperature, vibration and motor health, and can obtain the linear change relationship between the local and comprehensive health of the motor. Predictive maintenance advances the diagnosis time of traditional motor fault diagnosis, which can prevent irreversible damage to the motor. The invention can more accurately obtain the abnormal working state of the motor, separate the statistical calculation flow from the real-time calculation flow, reduce the edge calculation pressure of the acquisition device, and avoid unnecessary hardware costs; and can locate predictive maintenance in Part of the motor reduces the cost of manual inspection.

Description

technical field [0001] The invention relates to a method and system for predictive maintenance based on motor parameters, belongs to the field of information, and is suitable for maintenance of industrial sites, engineering teaching equipment and equipment with motor devices. Background technique [0002] In terms of predictive maintenance of motors, the country is still in the tentative stage, and there is no outstanding solution that can realize a unified predictive maintenance platform for motors of various types and industries. In order to realize the construction of the predictive platform, the daily operating health of the motor must first be determined, which requires statistics and analysis of the daily operating parameters of the motor. The current motor maintenance is mostly based on fault diagnosis algorithms, and the relevant electrical parameters of the motor can be derived mathematically to judge its operating status. This kind of algorithm, first, requires hi...

AI Technical Summary

Problems solved by technology

This kind of algorithm, first, requires high real-time performance, requires real-time collection and real-time calculation, and requires a large number of mathematical calculations in the collection equipment. The calculation here includes not only calculating the input data of the algorithm from the collected data, but also Including the calculation of the algorithm itself, in order to better maintain the effect, this kind of calculation has high requirements on the hardware of the acquisition equipment. If a large number of equipment needs to be collected, the cost will be doubled; second, this type of algorithm often produces acute Fault diagnosis can only be performed when there is a sudden fault. If the health of the motor is regarded as a value between 0 and 100, when the traditional fault diagnosis algorithm is applied, the change of the health of the motor is often a sudden decrease of a discrete value, which makes the equipment diagnosis The time from failure to irreversible damage to the equipment is too short, which is not conducive to the fault tolerance of the motor; third, the traditional fault diagnosis method often only judges the threshold value of one parameter, its accuracy is not high, and its robustness is poor

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