基于DSP的滚动轴承故障识别系统设计

Design of Fault Identification System for Rolling Bearing Based on DSP

为提高滚动轴承故障识别的准确性,基于层次熵分析提出了一种新的滚动轴承故障特征提取方法。介绍了样本熵和多尺度熵,基于层次熵分析对实验数据进行分解。然后计算各分解节点的样本熵,并将其作为特征向量。利用支持向量机对滚动轴承故障进行识别。基于DSP设计了一个滚动轴承故障识别系统,给出了其硬件结构包括人机交互界面、RS485通信、DSP控制器、信号预处理、信号采集等部分,同时给出了对应的软件设计方法。最后,通过应用实例验证了所述滚动轴承识别系统的可行性和有效性。

In order to improve the accuracy of the rolling bearing fault identification, a novel method of rolling bearing fault feature extraction is put forward based on hierarchical entropy analysis. Sample entropy and multi-scale entropy are introduced. The experimental data decomposition is carried on based on hierarchical entropy analysis. Then the sample entropies of decomposition nodes are calculated and they are considered as feature vectors. The rolling bearing fault identification is obtained by using support vector machine. A rolling bearing fault diagnosis system is designed based on DSP. And its hardware structure includes human-computer interaction interface, RS485 communication, DSP controller, signal preprocessing, signal acquisition and so on. The corresponding software design method is also presented. Finally, an application example is used to verify the feasibility and effectiveness of the rolling beating identification system.