基于D-S证据理论的轴心轨迹自动识别方法  

Automatic Identification Method of Axis Orbits Based on D-S Evidential Theory

作　　者：袁倩[1] 孙冬梅[1] 范文[1] 

机构地区：[1]南京工业大学电气工程与控制科学学院,江苏南京211816

出　　处：《机床与液压》2017年第7期167-171,139,共6页Machine Tool & Hydraulics

基　　金：国家自然科学基金资助项目(51277092);江苏省人事厅江苏省博士后资助计划(1201012C);江苏省科技支撑计划项目(BE2011188)

摘　　要：旋转机械的轴心轨迹包含了其运行状态的丰富信息,是判断转子运行状态和故障征兆的重要依据。提出对轴心轨迹的图像利用不变矩和傅里叶描述子提取特征,采用D-S证据理论对轴心轨迹特征参数进行融合识别诊断,并与传统BP神经网络识别方法比较,证明D-S证据理论提高了识别的准确性。将所提的方法应用于磁轴承故障诊断中,利用实测振动信号验证该方法的实用性,最终结果表明识别结果与轨迹形状相符合,说明文中提出的方法不仅能够较好的提取轴心轨迹图像特征,并能有效地对轴心轨迹进行识别,提高磁轴承故障诊断的精度。Rotating mechanical axisorbit contains the rich information of its running state, which is the important basis for identification of rotor running state and fault sign. Invariant moment and Fourier descriptorare proposed to beutilized to extract the axisorbit image features. The D-S evidentialtheory was adopted to orbit characteristic parameters into the fusion and diagnosisidentification, andthcn compared with the traditional BP neural network identification method, the result shown that the D-S evidential theory improved the identification accuracy. The proposed method was applied to magnetic bearing fault diagnosis, the measured vibration signal was usedto verify the practicability of this method, and the final results showed that the identification result was inconsistent with orbit shape. It isproved that the proposed method can not only extract axisorbitimage features, but also effectively carry outtheaxis orbitiden- tification to improve the precision of the magnetic bearing fault diagnosis.

关 键 词：磁轴承转子 轴心轨迹 不变矩 傅里叶描述子 D—S证据理论 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]