关键特征点的智能识别及其在操动机构电磁铁运行状态监测中的应用

Intelligent identification of key characteristic points and its application in electromagnet operation condition monitoring of operating mechanism

作为断路器操作机构开合动作的触发器,电磁铁的工作状态对于确保操作机构的工作状态具有重要意义。然而,由于复杂电气环境的干扰和传感条件的限制,电磁铁的鲁棒性状态监测存在很大的不足。本文提出了一种两阶段混合方法来诊断运行机构电磁铁的运行状态。该方法通过智能识别电磁铁电流信号的关键特征点,间接实现对电磁铁状态的智能诊断。在第一识别阶段,提出了适合一维信号的智能U-Net神经网络,通过获取的电磁铁电流信号实现关键特征点的自适应识别。在第二个状态监测阶段,根据关键特征点的位置和电流值,可以具体识别电磁铁的运行状态。实验结果表明,所提出的方法能有效识别关键点,识别成功率接近100%。所提出的方法只需少量故障样本就能实现对各种电磁铁故障的自适应识别。因此,所提出的方法为电磁铁的稳健状态识别提供了保障,并具有抗干扰性强的优点。

The electromagnet’s state of operation plays a crucial role in maintaining the operational mechanism of circuit breakers,as it acts as a trigger for the opening and closing action of the mechanism.However,due to the interference of complex electrical environments and the limitation of sensing conditions,there are significant deficiencies in the robust condition monitoring of electromagnets.A hybrid two-stage method was proposed to diagnose the running state of the electromagnet of the operating mechanism.By intelligently identifying the key characteristic points of the electromagnet current signal,the proposed method indirectly realized the intelligent diagnosis of the state of the electromagnet.In the first identification stage,an intelligent U-Net neural network suitable for the one-dimensional signal was proposed to realize the adaptive identification of crucial feature points via the obtained current signal of electromagnets.In the second condition monitoring stage,based on the position and the current value of the key feature points,the operating state of the electromagnet could be identified specifically.The experimental findings demonstrated that the suggested strategy was capable of successfully identifying the key characteristic points,with a near-perfect recognition success rate.The proposed method realized the adaptive identification of various electromagnet faults with only a few fault samples,which provided a guarantee for robust state identification of electromagnets and had the advantage of high interference resistance.