Ramanujan-gram:一种强噪声下的自主弱周期故障提取方法

IF 5.7 2区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Haiyang Pan, Hong Feng, Jian Cheng, Jinde Zheng
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引用次数: 0

摘要

在强噪声的影响下,滚动轴承的周期故障特征不明显,增加了准确提取周期故障特征的难度。提出了一种强噪声条件下的自主弱周期故障提取方法——Ramanujan-gram。Ramanujan-gram最大的优点是利用Ramanujan特征提取技术对各频带的分量进行重构,克服了传统的峭图方法所采用的滤波方法噪声鲁棒性弱的缺点,提高了周期故障特征提取的精度。同时,采用基于阶数统计滤波器的自适应频带分割方法进行自适应频带分割,克服了固定频带分割的二叉树结构可能破坏最优解调频带的缺点。考虑到峰度指标难以准确评价分量中的周期故障信息,Ramanujan-gram采用自适应方包络谱加权峰度指标来提高周期故障信息的评价精度。滚动轴承的测试信号验证了Ramanujan-gram具有较强的噪声鲁棒性,是强噪声条件下弱周期故障提取的有效方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ramanujan-gram: an autonomous weak period fault extraction method under strong noise
Under the influence of strong noise, period fault features of rolling bearing are not obvious, which increases the difficulty of accurately extracting period fault features. An autonomous weak period fault extraction method under strong noise named Ramanujan-gram is proposed in this paper. The greatest advantage of Ramanujan-gram is that it uses the Ramanujan feature extraction technique to reconstruct the components in each frequency band, which can overcome the weakness of the weak noise robustness of the filter methods used by the traditional kurtogram methods and improve the accuracy of period fault feature extraction. Meanwhile, the adaptive frequency band segmentation method based on the order statistical filter is used for adaptive frequency band segmentation, which overcomes the defect that the binary tree structure of fixed frequency band segmentation may destroy the optimal demodulated frequency band. Considering that kurtosis index is difficult to accurately evaluate period fault information in components, Ramanujan-gram adopts adaptive square envelope spectrum weighted kurtosis index to improve the evaluation accuracy of period fault information. The test signals of rolling bearing verify that Ramanujan-gram has strong noise robustness and is an effective method for weak period fault extraction under strong noise.
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来源期刊
CiteScore
12.80
自引率
12.10%
发文量
181
审稿时长
4.8 months
期刊介绍: Structural Health Monitoring is an international peer reviewed journal that publishes the highest quality original research that contain theoretical, analytical, and experimental investigations that advance the body of knowledge and its application in the discipline of structural health monitoring.
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