基于LSTM网络的IGBT参数预测硬件系统设计

Design of IGBT parameter prediction hardware system based on LSTM network

对绝缘栅双极型晶体管进行参数预测可以有效地避免因其失效带来的经济损失和安全问题。对绝缘栅双极型晶体管参数进行分析,设计了一个基于LSTM网络的绝缘栅双极型晶体管参数预测SoC硬件系统。该系统使用ARM处理器作为总控制器,控制各个子模块的调用和数据的传输,FPGA内通过对矩阵向量内积算法进行优化提高LSTM网络内部的数据运算速度,并且采用多项式近似的方法降低了激活函数所占用的资源。实验结果表明,系统的预测平均准确率为92.6%,计算速度相比于CPU快了3.74倍,同时具有低功耗的特点。

Parameter prediction of insulated gate bipolar transistor (IGBT) can effectively avoid the economic loss and safety problem caused by its failure. Based on the analysis of IGBT parameters, the paper designs a SoC hardware system of IGBT parameters prediction based on LSTM network. The system uses ARM processor as the general controller to control the call of each sub-module and the transmission of data. In the FPGA, the algorithm of matrix vector inner product is optimized to improve the data operation speed in the LSTM network. And the polynomial approximation method reduces the resources occupied by the activation function.The experimental results show that the average prediction accuracy of the system is 92. 6 %, the calculation speed is 3. 74 times faster than the CPU, and the system has the characteristics of low power consumption.