基于集成学习的操作机构控制电路故障分类

Fault Classification of Operating Mechanism Control Circuits Based on Integrated Learning

摘要: 实时监测和故障诊断是智能化高压配电系统稳定正常运行的关键，为了实现在电力系统中准确识别故障的要求，本文提出了一种基于集成学习的电力系统故障分类模型，通过对特征空间中的非线性规律进行编码的多项式特征衍生，极大地提高了特征的效用。该方法能够有效识别控制系统中各元器件是否发生故障。对提高压断路器设备监测效率、降低安全事故率、提升配电系统智能化改造具有一定的应用价值和现实意义。

Abstract: Real-time monitoring and fault diagnosis is the key to the stable and normal operation of the intelligent high-voltage distribution system, in order to achieve the requirements of accurate fault identification in the power system, this paper proposes a fault classification model of power system based on integrated learning, which greatly improves the utility of features by encoding the nonlinear law in the feature space. This method can effectively identify whether each component in the control system is faulty. It has certain application value and practical significance for improving the monitoring efficiency of pressure circuit breaker equipment, reducing the safety accident rate, and improving the intelligent transformation of the power distribution system.