电枢匝间绝缘参数智能优化测试技术及其应用

Intelligent Optimization Test Model of Armature Turn-To-Turn Insulation Parameter and Its Application

为减少传统测试方法和测试人员对电枢匝间绝缘参数的测试带来的误差,提高测试效率和电枢质量,基于电枢匝间绝缘参数测量原理建立了测量模型,并采用函数链神经网络与自适应混沌优化算法相结合对电枢匝间绝缘参数测量模型进行了校正。应用结果表明,该电枢匝间绝缘参数智能优化测量模型相对误差小于1.0%,具有较高的精度。

In order to reduce the error brought by traditional test method, a test model of armature turn-to-turn insulation parameter is established based on its measurement mechanism in the paper, and its parameters adjustment by using function link neural network and chaos optimization algorithm are introduced. The application results reveal that the relative error of the intelligent optimization test model is less than 1%, and is of high accuracy.