文献详情
Adaptive tensor morphology and its application in bearing failure diagnosis
文献类型会议
作者Wang, Long Sheng[1];Lv, Yong[2];Yuan, Rui[3]
机构
2015
会议名称International Conference on Energy Equipment Science and Engineering, ICEESE 2015
页码范围2323-2329
会议地点Guangzhou, China
会议开始日期2015-05-30
会议结束日期2015-05-31
收录情况EI(20162402496391)  
所属部门机械自动化学院
期刊等级
人气指数28
浏览次数22
语言外文
摘要Mathematical morphology is a common non-linear signal filtering method. The fixed preset shapes are known as structural elements, which are all rigid structural elements. When using morphological filtering based on rigid structural elements, it may destroy valuable information and data because its structure cannot fit the general mechanical fault vibration signal. This paper presents a novel adaptive morphological filtering method based on the local structuring tensor. According to the local information structure of the signal to build the tensor elliptical structure elements, the sizes and shapes of the tensor elliptical structure element, which can replace the linear and circular structuring element from the mathematical model is adaptively selected. The different shapes and sizes of tensor elliptical structure elements represent different information characteristics, so as to filter the different types of signal segments. The comparative study of the proposed morphological filtering method in this paper and some other similar methods can lead to a conclusion that the results show there is a better noise reduction effect of adaptive tensor morphology based on tensor elliptical structure elements. In application researches, the effect of fault feature extraction of the proposed method is much better than the morphological filtering based on linear and circular structure elements when it is applied in the signals of inner and outer rings of fault bearing which can verify the effectiveness of the proposed method. ? 2015 Taylor & Francis Group, London.
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Bearing fault diagnosis based on weighted phase space reconstruction.

Lv, Yong;Zhang, Hongwei;Li, Yourong,等.2010 International Conference on Digital Manufacturing and Automation, ICDMA 2010.2010,1,315-318.

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