Method and system for monitoring power equipment failures

Abstract

The invention provides a method and a system for monitoring power equipment failures. The method includes the steps of acquiring status indicator data of power equipment; determining whether the status indicator data are abnormal or not according to a preset status indicator threshold and acquiring abnormal status indictor data; determining the types of power equipment failures according to the abnormal status indicator data and a preset failure judgment model, and acquiring preset processing instructions for the failure types. The equipment status indicator data include online detection status indicator data and observation status indicator data. The failure judgment model includes association between the status indicator data and the failure types, weight of the association, and processing instructions for the failure types. The method and system can be used for diagnosing, processing and preventing power equipment failures, and power equipment is safer.

Description

technical field [0001] The invention relates to the technical field of power equipment monitoring, in particular to a power equipment failure monitoring method and a power equipment failure monitoring system. Background technique [0002] During the operation and maintenance of equipment, electric power enterprises can collect data representing the health status of equipment and whether there are faults (including dominant and hidden faults) through manual collection by operators, online monitoring, and preventive tests. data. The status standard data of the equipment is multi-faceted. For example, for a power transformer, we can obtain the temperature of each part through infrared temperature measurement, so as to know whether the equipment has a heating fault and where the fault is. This is the data that we need to use the instrument to obtain whether there is a fault in the equipment, that is, the status index data of the equipment. Similarly, we obtain most of the exte...

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Problems solved by technology

[0003] However, at present, in actual equipment defect diagnosis and processing, these data cannot be effectively applied to equipment fault diagnosis due to different professional management categories and different informatization implementation methods, and equipment faults are diverse. When a fault occurs , some are obvious to the operator, but some occur inside the equipment or cannot be detected by the existing detection technology. Those faults that cannot be directly detected or need to be confirmed by reasoning are hidden faults. Diagnosis and treatment of permanent faults have always been the focus and difficulty in equipment fault diagnosis.

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