Research On Power Cable Fault Online Monitoring And Situation Assessment System

Power cable plays an important role in power transmission,and its reliable operation is related to the stability and safety of the whole power system.At present,the maintenance of power cables usually adopts regular inspection and power outage maintenance,which not only takes up a lot of human and material resources,but also can not timely monitor the sudden failure of cables.Therefore,this paper applies electrical equipment fault diagnosis technology,Internet of things technology,cloud computing and edge computing,deep learning algorithm and data visualization technology to design the power cable fault online monitoring and evaluating system,and realizes the power cable fault online monitoring and operation situation health assessment.This paper expounds the research background and significance of power cable fault monitoring,in view of the domestic and foreign related research status quo of power cable fault monitoring,analyzes the temporal characteristics of power cable fault occurs,and combined with the scene of the actual demand,with power cable sheath grounding current,tapping temperature and quantity of environmental parameters as the main monitoring of power cable fault analysis and judgment;By discussing the problems existing in the current fault monitoring system,the functional requirements of the system are analyzed from multiple angles and in depth,and the power cable fault online monitoring system is designed.The system is composed of edge computing layer and cloud computing layer,the edge computing layer includes perception layer and transport layer,and the cloud computing layer includes data management layer and user application layer.Among them,the perception layer completes data acquisition,analysis and processing,the transport layer uploads the processed data to the cloud computing layer through LPWAN technology,the data management layer performs data management and analysis,and the user application layer implements visual human-computer interaction on the Web end for the processed data.When the monitoring data is abnormal,the Web terminal will display the fault information in real time.Meanwhile,the mobile terminal will push the fault information and display the fault status of the cable through the wechat mini program to remind the staff to rectify the fault of the power cable in time.In order to quickly judge the abnormal state of power cables and deal with the abnormal state in time,this paper constructs an edge data analysis and processing model based on adaptive threshold selection algorithm in the perception layer,and sends useful data reflecting the state of equipment to the cloud computing layer for data processing.At the same time,based on the LSTM network model,this paper takes the multi-time sequence fusion data of power cables as the power cable health status assessment quantity,applies CNN network and attention mechanism to optimize and improve the feature extraction performance of the model,constructs the cable operation situation health assessment model,and realizes the power cable operation situation health assessment.Through the cable monitoring data of Tongting mine,the performance of the model is verified.The experiment proves that the optimized model has a good effect on the health assessment of power cable operation situation.Finally,the system is tested experimentally.The results show that the system designed in this paper meets the design requirements,provides an effective solution for the safe operation and efficient management of the power supply system,and provides a strong support for the safe production of the power industry.Figure [55] Table [11] Reference [82]...