Track 31: Operational Condition Assessment and Fault Diagnosis for Power Equipment 电力装备运行状态评估与故障诊断技术
Organizers / 组织者
Professor/Director of High-Voltage Department, Chongqing University
教授/高压系系主任, 重庆大学
Doctor, Aalborg University
博士, 丹麦奥尔堡大学
Abstract / 论坛简介
English: Power equipment is the physical cornerstone for the safe and stable operation of modern power grids, and it is rapidly developing towards intelligence, greenness, and high-end direction. Power equipment, such as transformers, bushings, circuit breakers, cables, GIS, etc., face complex operating conditions during operation. The evaluation of their operating status and fault diagnosis technology are key to ensuring the safe and stable operation of the power grid. This topic focuses on key issues such as power equipment state perception, intelligent evaluation, and proactive fault warning. It focuses on advanced sensing technology, live detection technology, digital twin technology, artificial intelligence fault diagnosis methods, and electrical insulation material performance state evaluation technology, providing a communication platform for promoting the development of power equipment operation state evaluation and fault diagnosis technology.
中文: 电力装备是现代电网安全稳定运行的物理基石,其正向智能化、绿色化和高端化方向快速发展。电力装备(如变压器、套管、断路器、电缆、GIS 等)在运行过程中面临着复杂运行工况,其运行状态评估与故障诊断技术是保障电网安全稳定运行的关键。本专题聚焦电力装备状态感知、智能评估与故障主动预警等关键问题,重点探讨先进传感技术、带电检测技术、数字孪生技术、人工智能故障诊断方法、电工绝缘材料性能状态评估技术等,为推动电力装备运行状态评估与故障诊断技术发展提供交流平台。
Topics / 主题范围
- Online monitoring and advanced sensing technology for the operation status of power equipment / 电力装备运行状态在线监测与先进感知技术
- Multi-source data fusion and intelligent state assessment methods / 多源数据融合与智能状态评估方法
- Fault diagnosis and proactive warning technology for power equipment / 电力装备故障诊断与故障主动预警技术
- Fault diagnosis technology for power equipment based on artificial intelligence and machine learning / 基于人工智能与机器学习的电力装备故障诊断技术
- Digital twin technology and full lifecycle management technology for power equipment / 电力装备数字孪生技术与全寿命周期管理技术
- Evaluation technology for performance degradation of electrical insulation materials / 电工绝缘材料性能劣化评估技术
- Analysis and experience summary of typical power equipment failure cases / 典型电力装备故障案例分析与经验总结