A wind turbine troubleshooting method and system based on structured knowledge base

Abstract

The invention discloses a wind turbine generator fault maintenance method based on a structured knowledge base. The method comprises the following steps that S01, the structural knowledge base of windturbine generator faults is established, and the running data of the wind turbine generator is collected in real time; S02, when the fault occurs on the wind turbine generator, effectiveness discrimination is performed on the fault information, and when the fault is effective, S03 is entered; and S03, the running data, the fault information and the fault wind turbine set position information aretransmitted into the structured knowledge base, and a fault treatment scheme is obtained by matching. The invention further discloses a fault maintenance system which comprises a first module, a second module and a third module, wherein the first module is used for acquiring the running data of the wind turbine generator; the second module is used for carrying out effectiveness discrimination on the fault information when the wind turbine generator breaks down; and the third module is used for transmitting the running data, the fault information and the fault wind turbine set position information into the preset structured knowledge base when the fault is effective, and the fault treatment scheme is obtained by matching. The method and the system have the advantages of standardization in maintenance, high efficiency and the like.

Description

technical field [0001] The invention mainly relates to the technical field of wind power generation, in particular to a method and system for troubleshooting a wind turbine based on a structured knowledge base. Background technique [0002] Wind turbines are large mechatronic equipment integrating mechanical components and electrical systems. They mostly operate in places with harsh natural conditions such as high temperature, severe cold, thunderstorms, high posters, strong sandstorms, etc. The designed service life of the wind turbines is as long as 20 years. Effective operation and maintenance is the key factor to ensure the best performance of the fan in the whole life cycle. However, the traditional maintenance methods of my country's wind power industry still have the following problems: 1) In the current maintenance process of wind turbines, most of the offline experience summary and transmission are based on traditional paper methods, resulting in untimely and untime...

AI Technical Summary

Problems solved by technology

However, the traditional maintenance methods of my country's wind power industry still have the following problems: 1) In the current maintenance process of wind turbines, most of the offline experience summary and transmission are based on traditional paper methods, resulting in untimely and untimely inheritance of maintenance experience. Comprehensive, unable to automatically match the maintenance methods of units with different configurations, unable to effectively structure and regularize the fault experience, and then standardize it eventually, the efficiency of experience transfer is low, and most of the equipment fault handling depends on experienced operation and maintenance personnel. Experienced operation and maintenance personnel are highly dependent; 2) The overall quality and technical level of operation and maintenance personnel are not high, the technology is not open enough, business and technical training is not sufficient and inconvenient, and the operation and maintenance capabilities urgently need to be upgraded

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