@inproceedings{e5376b34d1f341e8998051ae5a8fd8a0,
title = "Intelligent technique and its application in fault diagnosis of locomotive bearing based on granular computing",
abstract = "This paper presents a new approach to intelligent fault diagnosis of the machinery based on granular computing. The tolerance granularity space mode is constructed by means of the inner-class distance defined in the attributes space. Different features of the vibration signals, including time domain statistical features and frequency domain statistical features, are extracted and selected using distance evaluation technique as the attributes to construct the granular structure. Finally, the proposed approach is applied to fault diagnosis of locomotive bearings, testing results show that the proposed approach can reliably recognize different faulty categories and severities.",
keywords = "Fault diagnosis, Granular computing, Granularity structure, Tolerance relations",
author = "Zhang Zhousuo and Yan Xiaoxu and Cheng Wei",
year = "2009",
doi = "10.1007/978-3-642-01513-7\_81",
language = "英语",
isbn = "3642015123",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 3",
pages = "744--754",
booktitle = "Advances in Neural Networks - ISNN 2009 - 6th International Symposium on Neural Networks, ISNN 2009, Proceedings",
edition = "PART 3",
note = "6th International Symposium on Neural Networks, ISNN 2009 ; Conference date: 26-05-2009 Through 29-05-2009",
}