Improvement Of Mechanical Characteristic State Assessment And Maintenance Strategy Management Of Circuit Breakers

Under the guidance of the concept of sustainable development,the pace of social and economic development is getting faster and faster,and the power load is also increasing.The importance of the power system need not be described.How to ensure that the power system operates more reliably is the current power and related industries.One of the key issues.The high-voltage circuit breaker plays a role of control and protection in the entire transmission and transformation line.It is an extremely important component.Once the high-voltage circuit breaker fails to work properly,the damage caused is immeasurable.With the rapid increase in the number of newly-operated circuit breakers in recent years,the current state maintenance and regular maintenance methods have been difficult to meet the demand.The operation and maintenance personnel have a huge workload and cannot meet the requirements for small maintenance of the circuit breaker every year.Sometimes There will be a situation where it is not in place,but there is also a problem of overhaul.Therefore,it is urgent to adjust the maintenance strategy through technical means to improve the reliability of equipment,reduce the workload of maintenance and repair personnel,and reduce the operation and maintenance costs.The main research contents of this paper are as follows:First,analyze and compare the problems existing in the current circuit breaker maintenance work.Secondly,through the analysis of the cause of the circuit breaker failure and the application of artificial intelligence in China's power industry,it is determined that the establishment of the circuit breaker health evaluation model can promote the differential maintenance and improve the maintenance efficiency.In this paper,a reliable evaluation model is established by means of BP neural network.The input and output layers of the neural network are determined through case study,theoretical analysis and expert advice,and BP neural network training is completed by using historical running waveform data.Finally,through the monitoring data of 24 circuit breakers in Beijing in 2018,the effectiveness of the research is verified,and the feasibility of the health model proposed in this paper is determined.It is clear that the health model established in this paper can improve the field work efficiency and improve the detection.Means,reducing resource waste,is an effective way to achieve differential maintenance;at the same time,using data comparison method,the comparison between the number of training groups and the training effect is given,and the BP neural network is used to evaluate the mechanical characteristics of other types of circuit breakers..According to the health model proposed in this paper,combined with the actual operation,the improvement idea of the evaluation model is proposed,and the practical guiding significance of the differential maintenance of the circuit breaker is further improved.