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| 基于改进阈值原则与样本熵的轴承阈值降噪方法 |
| Bearing Threshold Noise Reduction Method Based on Improved Threshold Principle and Sample Entropy |
| 投稿时间：2023-11-20 修订日期：2023-11-20 |
| DOI： |
| 中文关键词: 小波 阈值降噪 改进阈值原则 样本熵 轴承 |
| 英文关键词: wavelet, threshold noise reduction, improved threshold principle, sample entropy, bearing |
| 基金项目:国家自然科学基金项目（面上项目，重点项目，重大项目） |
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| 中文摘要: |
| 为了提高对故障轴承信号的降噪效果、降低重构信号中噪声信号的比例，提出基于改进阈值原则结合样本熵的小波阈值降噪算法。采用小波变换对信号进行多层分解，以样本熵为标准采用改进阈值原则设置不同分解层的阈值，最后重构降噪后的小波系数实现信号的最终降噪。仿真和实验比较的结果中表明：基于改进阈值原则的小波阈值降噪方法对轴承信号能进行有效降噪，降噪效果优于传统的通用阈值原则和固定阈值原则。 |
| 英文摘要: |
| In order to improve the noise reduction effect of fault bearing signals and reduce the proportion of noise signals in reconstructed signals, a wavelet threshold noise reduction algorithm based on improved threshold principle combined with sample entropy is proposed.The signal is decomposed into multiple layers by wavelet transform, and the thresholds of different decomposition layers are set using the improved threshold principle based on sample entropy. Finally, the wavelet coefficients after noise reduction are reconstructed to achieve the final noise reduction of the signal.The results of simulation and experimental comparison show that the wavelet threshold noise reduction method based on improved threshold principle can effectively denoise bearing signals, and the noise reduction effect is better than the traditional general threshold principle and fixed threshold principle. |
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