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| A Fault Diagnosis Method for Heavy-load Low-speed Bearing |
| Received:June 10, 2020 |
| DOI：10.11980/j.issn.0254-508X.2020.09.008 |
| Key Words:heavy load low speed bearing vibration detection method fault diagnosis Fast Kurtogram envelope analysis method |
| Fund Project:陕西省技术创新引导专项（项目编号：2020CGHJ-007）。 |
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| Abstract:On the paper production line， especially on high grammage paper board machines， there are many heavy-load low-speed rotating equipment， such as press rolls and dryers. Compared with high-speed equipment， their vibration characteristics are weak and difficult to extract. At the same time， low-speed bearings are often subject to heavy loads and vulnerable to damage， which can lead to equipment failure and even shutdown. Therefore， on-line fault diagnosis of heavy-load and low-speed bearings is very important. Based on the analysis of the difficulties in the diagnosis of heavy-load low-speed bearing vibration and the current common methods of fault diagnosis， this paper proposed a bearing fault diagnosis method based on Fast Kurtogram envelope demodulation analysis. First， the Fast Kurtogram method was used to calculate the maximum spectral kurtosis value of the vibration signal to determine the optimal band-pass filter coefficient. Then band-pass filter was used to perform noise reduction on the vibration signal. Finally， the Hilbert transform method was used to process the noise reduction signal， and the envelope spectrum was analyzed to obtain the diagnosis result. With the help of the bearing failure test bench designed by the team， the advantages， disadvantages， and applicability of the method proposed in this paper were experimentally researched， the effectiveness of the algorithm in this paper were verified， and some recommendations were put forward for engineering applications. |
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