罗步升,林志超,何小龙.基于拓扑解析与深度学习融合的低压集抄系统故障诊断方法[J].电测与仪表,2019,56(20):145-152. LUO Busheng,LIN Zhichao,HE Xiaolong.Fault Diagnosis Method for Low-voltage Centralized Meter Reading System Based on Physical ToPology-Data Learning[J].Electrical Measurement & Instrumentation,2019,56(20):145-152.
基于拓扑解析与深度学习融合的低压集抄系统故障诊断方法
Fault Diagnosis Method for Low-voltage Centralized Meter Reading System Based on Physical ToPology-Data Learning
Aiming at the problems that the faults in low-voltage centralized meter reading system are complex and the current operation and maintenance is difficult to meet the harsh user demand, we proposed a fault diagnosis method for LV centralized meter reading system based on topology analysis-deep learning. Starting from the two stages, planning and operation, we analyzed the transformer-concentrator association and concentrator-electric energy meter association to diagnose the physical topology of LV centralized meter reading system. Based on the determined physical topology and information flow path, a deep belief network fault diagnosis model is automatically established by offline learning with emerging fault events. Online obtaining the vital systematic operation character, the system fault section feature vector is established and sent to the well-trained fault diagnosis model for final diagnosis result. The result of the case study have showed that the proposed method can effectively and accurately diagnose the fault in LV centralized meter reading system, and it’s effective to deal with the case of the missing information and wrong information.
