基于轴承故障诊断的软刚臂模型实验设计研究

Design and Research of Soft Yoke Model Experiment Based on Bearing Fault Diagnosis

  • 摘要: 针对软刚臂上铰点推力滚子轴承的故障信号易被其他信号干扰的问题,提出了最小熵解卷积(MED)理论,并以明珠号FPSO系泊腿推力滚子轴承为研究对象,设计了大比尺模型实验,模型实验包括单点平台、软刚臂、系泊支架3个部分。试验中,六自由度平台代替浮体做艏摇运动,通过完好的推力滚子轴承与故障的推力滚子轴承加速度信号做比较,对轴承故障进行分析,验证了MED方法的可行性与模型实验的正确性。结论表明,MED方法能很好地突出振动信号的脉冲冲击成分,对轴承工作状态进行初期的诊断识别。同时,考虑轴承诊断的模型装置也为高校的专业教学与科学研究提供了实验平台。

     

    Abstract: In response to the fault vibration signal of upper hinge point of soft yoke mooring system susceptible to interference of other signals, the theory of minimum entropy deconvolution was proposed. With the thrust roller bearing in mooring leg of Mingzhu FPSO as the study object, the paper designed a large scale model experiment. The model experiment includes three parts, i.e. single point platform, soft yoke mooring system and mooring support. In the experiment, the platform with six degrees of freedom replaces the floating body to do the yaw movement. By comparing the acceleration signals of the intact thrust roller bearing and the faulty thrust roller bearing, the bearing fault was analyzed, and the feasibility of the minimum entropy deconvolution (MED) analysis method and the correctness of the model experiment were verified. The results show that the MED method can highlight the pulse impact components of vibration signals, and judge and recognize the initial working state of bearing. Meanwhile, the model device considering bearing diagnosis also provides an experimental platform for professional teaching and scientific research for colleges and universities.

     

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