An online warning method for motor abnormal state

Abstract

The invention belongs to the motor equipment monitoring and fault diagnosis technical field and discloses a motor abnormal state online early warning method. The method includes the following steps that: data of parameters related to the state of a motor are periodically acquired from the supervisory information system (SIS) of a thermal power plant, and a prediction model for motor three-phase winding temperature is established; the distribution characteristics of motor three-phase winding temperature variance is put into statistics on the basis of the acquired data; and online early warningis performed against the abnormal state of the motor according to different stages on the basis of the motor three-phase winding temperature variance and the prediction model. With the method of the invention adopted, the timeliness and precision of online early warning operation can be significantly improved; purposeful spot inspection tasks can be effectively performed; and operation and maintenance management costs can be greatly reduced with the normal and stable operation of a unit ensured. The method is particularly suitable for application conditions such as various types of middle- andlarge-scale thermal power plants.

Description

technical field [0001] The invention belongs to the technical field related to motor equipment monitoring and fault diagnosis, and more specifically relates to an online early warning method for abnormal state of a motor. Background technique [0002] As the core equipment of electric energy production, transmission, use and transformation of electric energy characteristics, electric motor occupies an increasingly important position in many industries and departments in modern society. Taking a thermal power plant as an example, a variety of auxiliary equipment, such as coal mills, three major fans and various pumps, all need motors to drive. Therefore, the motor is an indispensable device to ensure the stable operation of the power plant. The failure of the motor of important auxiliary equipment is likely to cause the whole generator set to reduce load or shut down in an emergency, which seriously affects the economy of the power plant and the social effect of the enterpri...

AI Technical Summary

Problems solved by technology

However, since the current SIS system usually uses a fixed threshold to alarm the parameters (for example, the general threshold is 100°C for the three-phase winding of the motor), when the alarm occurs, the state of the equipment has actually deteriorated to a certain extent

In this case, not only the power generation of the power plant decreases, but also various manpower and material resources also cause huge economic losses, that is, the timeliness of the alarm is not strong, it is easy to cause equipment under-repair, and reduce the reliability and economy of the unit.

[0004] In addition, the existing SIS system-based motor condition monitoring scheme basically relies on spot inspectors to use specific detection equipment to judge the state of the motor, but does not make full use of the massive operating data in the SIS system

This situation not only increases the consumption of manpower and material resources of the power plant, but also may cause the performance degradation of the motor to be not detected in time due to the long spot inspection cycle, resulting in low monitoring accuracy and automation level

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