基于DSP+FPGA架构的DWT-SVM机载设备故障诊断方法研究

Fault Diagnosis of DWT-SVM for Airborne Equipment Based on DSP+FPGA Architecture Platform

针对机载设备故障诊断实时性差、效率低等问题,提出了一种基于DSP+FPGA架构的DWT-SVM故障诊断方法。首先提取传感器数据的时频域特征,构建故障特征向量,进而利用支持向量机实现机载设备的故障诊断。设计了基于DSP+FPGA异构计算架构的PHM平台,实现了基于DWT-SVM故障诊断算法的嵌入式计算,为实现机载设备故障诊断算法的加速计算问题提供了一种解决途径。实验结果表明,本平台的机载设备故障诊断加速计算效率提升5.63倍,而功耗仅为PC平台的17.7%。

Aiming at the problems of poor real-time performance and low efficiency for airborne equipment fault diagnosis,a DWT-SVM fault diagnosis implementation method based on DSP+FPGA architecture is proposed.Firstly,the time-frequency domain characteristics of the sensor data are extracted,and the fault feature vector is constructed.Then the support vector machine is used to realize the fault diagnosis of the airborne equipment.The PHM platform based on DSP+FPGA heterogeneous computing architecture is designed.The embedded computing based on DWT-SVM fault diagnosis algorithm is implemented,which provides a solution for the accelerated calculation of airborne equipment fault diagnosis algorithm.The experimental results show that the efficiency of the on-board equipment fault diagnosis acceleration calculation is 5.63 times of that of the PC platform,while the power consumption is only 17.7%of the PC platform.