Application of Acoustic Digital Twin Model for Fault Monitoring of Heavy Duty Gearbox

Cheng Lin, Jianrun Zhang, Liangquan Xu, Hao Peng
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Abstract

Heavy duty gearbox’s operating characteristic frequency is low. At present, various methods used to monitor the operation condition and analyze faults have their own traits and shortcomings. To realize the heavy duty gearbox’s operation condition monitoring and fault analysis, acoustic digital twin technology was proposed. Using noncontact far field acoustic signals, the operation condition can be monitored and faults can be analyzed. This new technology was characterized by locating and analyzing faults accurately. To improve the accuracy of the digital twin model, the contact stiffness model of the joint surface was further deduced. Finally, the frequency responses of sound pressure under different faults were compared and analyzed. It was shown that the proposed acoustic digital twin technology can be used to monitor the heavy-duty gearbox’s operation condition and analyze faults. Also, the results showed that this technology was feasible and accurate.
声学数字孪生模型在重型齿轮箱故障监测中的应用
重型变速箱工作特性频率低。目前,用于监测运行状态和分析故障的各种方法各有特点和不足。为实现重型齿轮箱运行状态监测和故障分析,提出了声学数字孪生技术。利用非接触式远场声信号,可以监测设备的运行状况,分析故障。该技术具有准确定位和分析故障的特点。为了提高数字孪生模型的精度,进一步推导了结合面接触刚度模型。最后,对不同故障条件下的声压频率响应进行了对比分析。实验结果表明,所提出的声学数字孪生技术可用于重型齿轮箱的运行状态监测和故障分析。结果表明,该技术是可行的、准确的。
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