A method for analyzing and troubleshooting defects in power communication equipment

By improving the Apriori algorithm, a correlation analysis of the defect data of power communication equipment is generated, a defect-influence factor database is generated, and frequent item sets and strong rules are identified. The problem of insufficient ability to identify the causes of power communication equipment defects and fault points in the existing technology is solved, and efficient fault traceability and positioning is achieved.

CN114090647BActive Publication Date: 2025-08-08GUO JIA DIAN WANG YOU XIAN GONG SI XI NAN FEN BU +1
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Patent Information

Application Number
CN202111233433.8
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2021-10-22
Publication Date
2025-08-08
Estimated Expiration
2041-10-22

AI Technical Summary

Technical Problem

The prior art is difficult to efficiently identify the defect causes of power communication equipment and detect fault points, resulting in large maintenance work burdens and increased risk of power grid operation.

Method used

The improved Apriori algorithm is used to conduct correlation analysis on the defect data of power communication equipment, and the defect-influence factor database is generated through layered processing and quantitative encoding, frequent item sets and strong rules are identified, and equipment defects and fault locations with high support are preferred.

Benefits of technology

Effectively identify the causes and fault points of power communication equipment, reduce the maintenance work burden, and improve the safety of power grid operation.

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Abstract

The present invention discloses a method for analyzing and troubleshooting defects in power communication equipment. The method comprises: collecting historical power communication equipment defect data from the power communication equipment transmission network to generate a primary database of power communication equipment defects; quantifying the primary database of power communication equipment defects according to data discretization rules pre-determined based on the characteristics of power communication equipment defects to generate a database of power communication equipment defect-influencing factors; and importing a pre-built improved Apriori algorithm model for analysis to obtain frequent item sets with varying support and confidence levels and two types of strong rules. Advantages: Based on the physical model of power communication equipment and based on the characteristics of the equipment defect database, the method improves the traditional Apriori algorithm and performs correlation analysis on power communication equipment defects based on the improved Apriori algorithm, effectively identifying and detecting the causes of power communication equipment failures and locating the fault points.
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