Incipient fault detection for the spindle bearing of a cement grinding machine based on vibrational resonance

• Published in: Measurement science & technology 2025-01, Vol.36 (1), p.16127
• Main Authors: Xiao, Lei, Zhao, Hailong, Gao, Shaofeng, Zhou, Qihong
• Format: Article
• Language: English
• ISSN: 0957-0233; 1361-6501
• DOI: 10.1088/1361-6501/ad8a7d

The spindle bearing of a circulation fan is an important component of a cement grinding machine. In addition to the faults on the spindle bearing, impeller wear and ash accumulation may cause dynamic unbalance and complex vibration interference as noise, which decreases the accuracy of fault detection based on vibrational signals and traditional signal processing-based methods at the early stage of a bearing fault. To address this issue, this paper presents a new fault detection method for the spindle bearing by utilizing extra injected noise and vibrational resonance. To enhance the fault signature and resonance performance, the nonlinear system of the traditional vibrational resonance is replaced by a new hybrid steady-state system, and the underdamped term is considered in the new system. The proposed system provides more possibilities to achieve resonance by adjusting the system parameters and overcomes the limitations of output saturation caused by the classical bistable system. The proposed method is validated by analyzing the collected vibration signals from a spindle bearing of a circulation fan in practice and is compared with other noise-elimination fault detection methods. The results demonstrate the effectiveness and superior performance of the proposed method.