Detection method for familial defects of power equipment of power supply plant

Abstract

The invention relates to a detection method for familial defects of power equipment of a power supply plant. The method comprises the following steps of S1, endowing equipment in a power generation system with KKS codes respectively, and obtaining historical defect records of the equipment in the power generation system from a database; S2, according to the historical defect records of the equipment in the database, calculating a defect rate threshold d0 of the equipment; S3, according to serial numbers, types and manufacturers of the equipment, obtaining a classification matrix of the equipment; S4, comparing the values of d1, d2, ..., dM, and defining the equipment manufacturer with the defect rate value greater than the defect rate threshold d0 as the equipment manufacturer with the familial defects; S5, calculating a correlation coefficient r between the equipment manufacturer with the familial defects and the defect rate of the equipment, and when r is greater than a critical value r0, determining that the equipment manufacturer really has the familial defects; and S6, taking the KKS code of the equipment corresponding to the defect with the correlation higher than a familialdefect judgment threshold as the KKS code of the equipment with the familial defects, and calculating the defect rate df of the equipment manufacturer with the familial defects.

Description

technical field [0001] The invention belongs to the technical field of power generation, and in particular relates to a detection method for familial defects of power equipment in a power supply plant Background technique [0002] Electric power production is a huge and complex system engineering, with scattered production facilities, wide geographical distribution, many production links, strong technical performance, and the characteristics of simultaneous completion of production, supply and sales. The traditional technical supervision and management mode is only one-way open management. The organizational efficiency is not high, the information is not smooth, and the management is mechanical. There is no systematic and networked closed-loop management. There are poor technical supervision and management information and long supervision timeliness Problems, supervision and management are always in a passive state. Moreover, equipment management is often limited to the col...

AI Technical Summary

Problems solved by technology

In the traditional statistical analysis of defect data, there is a problem that only a large number of frequent defects of a certain type of equipment can be statistically analyzed in each time period, and the large number of frequent defects and other attributes of the equipment itself cannot be found. Inter-correlation and inter-correlation with other devices, so that it is impossible to find out the real reason for the frequent occurrence of this defect

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