New energy remote test equipment fault diagnosis method based on data mining

Abstract

The invention discloses a new energy remote test equipment fault diagnosis method based on data mining, including the steps of obtaining the characteristic information parameters of equipment on site,building a database, building an equipment fault data model and an equipment normal running data model according to equipment running data source mining, making a fault diagnosis analysis of abnormaldata, issuing a warning for a fault, determining the cause of the fault, and the like. In view of the problems such as the complex structure of remote test equipment, the dynamic instability of running data, the serious cross impact of equipment faults and the difficulty in fault locating and warning, the method combines the offline modeling, the data mining technology and the Internet technologyto help the operation and maintenance personnel check faults quickly and to quantify the economic risk, safety risk and maintenance risk brought about by complex faults produced by the cross impact of covert faults and overt faults and control the spread of the covert faults of large complex detection equipment in time. The method has the advantages of high diagnosis accuracy, high speed, significantly improved maintenance efficiency, lower maintenance cost, and the like.

Description

technical field [0001] The invention relates to a data mining-based fault diagnosis method for new energy remote testing equipment. Background technique [0002] Stable work of test equipment is the foundation for completing new energy grid-connected test tasks. With the advancement of contemporary industrial technology, test equipment is developing in a diversified direction. In the process of development, the structure of the equipment is becoming more and more complex, the functions are becoming more and more powerful, the difficulty of maintenance is getting higher and higher, and the possibility of equipment failure is also getting higher and higher. Minor failures will affect the test performance of the equipment; when a major equipment failure occurs, the equipment will stop working and cause damage to its internal components, which may cause significant measurement errors and economic losses. Therefore, how to diagnose equipment faults is the most important thing to...

AI Technical Summary

Problems solved by technology

Therefore, the quality of data collected for diagnosis of new energy remote test equipment is high. At the same time, it is also necessary to collect environmental condition parameter data and equipment vibration during the transition process, which requires high transient data processing. Existing equipment diagnosis The data set collected and analyzed in the method and the data processing standard are not enough to meet the requirements of remote test equipment fault diagnosis. Here we propose a new equipment fault diagnosis method to enable new energy remote test equipment to diagnose quickly, accurately and comprehensively. , reduce accident losses, improve grid-connected power supply reliability, and have important economic and social benefits

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