Cognitive calculation-based wind power fault operation and maintenance management method

Abstract

The invention discloses a cognitive calculation-based wind power fault operation and maintenance management method. The method comprises the following steps: performing feature analysis on a turn-to-turn short circuit fault of a stator of a wind turbine generator; establishing a wind power fault operation and maintenance cognitive calculation model based on a Bayesian network according to a feature analysis result; collecting behavior actions and emotional state signals of operation and maintenance personnel in real time; and sending the acquired behavior action and emotion state signals intoa wind power fault operation and maintenance cognitive calculation model, and iterating the Bayesian network by using a Markov chain Monte Carlo method to obtain a cognitive result of the operation and maintenance personnel. According to the invention, emotion factors are considered in operation and maintenance personnel capability evaluation so as to cope with extremely severe conditions of fan maintenance, and by referring to the wind power fault operation and maintenance cognitive calculation model, power enterprises can more efficiently dispatch personnel, and the operation and maintenancecost is practically reduced.

Description

technical field [0001] The invention relates to the field of wind power, in particular to a method for managing wind power fault operation and maintenance based on cognitive computing. Background technique [0002] As a typical representative of clean energy, wind energy has developed rapidly in recent years. The capacity and complexity of wind turbines have been increasing, making the operation and maintenance tasks more and more complicated. The difficulty and cost of wind power operation and maintenance have brought huge challenges, and it is easy to cause power generation loss or even personal safety problems due to the different levels of operation and maintenance personnel. The proportion of accidents caused by improper operation and maintenance in wind turbine accidents is as high as 32.5%. It can be seen that the cognitive computing of operation and maintenance personnel is very important. Accurate cognitive computing is a prerequisite for operation and maintenance m...

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Problems solved by technology

[0003] The literature "Human reliability analysis of power system operation and its database system research" proposes human reliability analysis methods in three scenarios: time-related, process-related, and emergency-related, which can quantify the probability of human error; Human Factors Based on Hidden Markov Equipment Forced Outage Rate Model" also uses Hidden Markov to identify human factors in equipment strong wave outage in the above three scenarios; the literature "The impact of human errors on the reliability of protection systems "Based on the condition-based maintenance environment, the human error rate prediction technology (THERP), the human cognitive reliability model technology (HCR) and the Markov method are used to analyze the impact of human error on the reliability index of the protection system; Human factors and their impacts have been analyzed usefully, but no practical and effective solutions have been proposed, and these previous studies have not taken into account the emotional state of operation and maintenance personnel, ignoring the effect of emotional state on rigorous operations in extreme cases. Influence of the industry, there is little discussion in the industry on the cognitive computing of multi-dimensional consideration of operation and maintenance personnel

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