基于杂散磁场感知与NBCNN-LSTM-Attention深度回归建模的永磁直线电机气隙磁密测量研究

Research on air gap magnetic density measurement of permanent magnet linear motor based on stray field sensing and NBCNN-LSTM-Attention depth regression modeling

本文提出一种基于隧道磁阻(TMR)传感器和噪声注入卷积神经网络(NBCNN)、长短期记忆网络(LSTM)、注意力机制动态集成神经网络预测模型(NBCNN-LSTM-Attention)的双边永磁同步直线电机气隙磁密新型非侵入式测量方法。首先,建立直线电机气隙磁场的解析模型和有限元模型作为数据基础,探寻直线电机的外部空间杂散磁场和内部中心气隙磁场存在非线性映射关系。其次,引入TMR传感器测量直线电机外部杂散磁场信号,并对传感器的安装位置进行优化,将内外一维磁密信号进行相似度特征匹配,以获取传感器最优测量位置。然后,将电机外部杂散磁场数据作为输入,内部气隙磁场数据作为输出,建立NBCNN-LSTM-Attention网络的内外磁场高精度映射模型,实现“用外代内”的非侵入式气隙磁密高精密测量。最后,搭建直线电机气隙磁密测量实验平台和高斯计对比测量实验平台,验证了本文所提方法的先进性和优越性。

A new non-invasive measurement method of air gap magnetic density of bilateral permanent magnet synchronous linear motor(BPMSLM)based on the tunneling magnetoresistance(TMR)sensor and the dynamic integrated neural network prediction model based on noise-boosted convolutional neural network(NBCNN),long short-term memory network(LSTM),attention mechanism is proposed.Firstly,the analytical model and the finite element model of air gap magnetic field of linear motor are tormulated as data basis.The nonlinear mapping relationship between external space stray magnetic field and internal central air gap magnetic field of linear motor is explored.Secondly,the TMR sensor is introduced to measure the external stray magnetic field signal of the linear motor,the installation position of the sensor is optimized,and the similarity characteristics of the internal and external one-dimensional magnetic density signals are matched to obtain the optimal measurement position of the sensor.Then,taking the external stray magnetic field data of the motor as the input and the internal air gap magnetic field data as the output,a high-precision mapping model of the internal and external magnetic fields of NBCNN-LSTM-Attention network is established to realize the non-invasive high-precision measurement of air gap magnetic density.Finally,the experimental platform for measuring the air gap magnetic density of linear motor and the experimental platform for comparative measurement of Gauss meter are built,which verifies the advancement and superiority of the proposed method.