基于深度信念网络的变频电机局部放电起始电压预测

Prediction of partial discharge inception voltage for inverter-fed motor based on deep belief network

局部放电是导致变频电机匝间绝缘过早失效的主要原因,匝间绝缘局部放电起始电压(PDIV)的预测对变频电机绝缘设计具有重要意义,因此提出一种基于深度信念网络的匝间绝缘PDIV预测方法。首先建立基于汤逊理论的局部放电仿真模型,计算不同仿真参数下匝间绝缘模型的PDIV;其次分析匝间绝缘PDIV的影响因素,建立深度信念网络提取影响因素和PDIV之间的非线性关系;然后根据仿真分析与试验测试,验证本文所提方法的有效性;最后通过平均影响值算法探究了匝间绝缘PDIV的主要影响因素。实验结果表明,该方法预测结果的最大相对误差为5.9%,为变频电机匝间绝缘设计和状态评估提供了新思路。

Partial discharge(PD) is the main cause of premature failure for the turn-to-turn insulation system in the inverter-fed motor. The prediction of PD inception voltage(PDIV) for the turn-to-turn insulation plays a significant role in the insulation design of inverter-fed motors. Therefore, a PDIV prediction method for turn-to-turn insulation based on the deep belief network(DBN) is proposed in this paper. Firstly, a PD simulation model is formulated, which is based on Townsend theory. The PDIV of different simulation parameters for the turn-to-turn insulation is calculated. Secondly, the influence factors of PDIV on the turn-to-turn insulation are analyzed. The DBN is implemented to mine the non-linear relationship between the influence factors and the PDIV. Furthermore, the effectiveness of the proposed method is evaluated by simulation analysis and experiment. Finally, the principal influence factors of the turn-to-turn insulation are investigated by the mean impact value algorithm. The case study demonstrates that the max relative error of the proposed method is 5.9%. It provides a novel idea for the condition assessment and insulation design of inverter-fed motors.