Research on Fault Diagnosis Algorithm Based on Multi-Source Data Analysis-Reference-Cited by-同舟云学术

Research on Fault Diagnosis Algorithm Based on Multi-Source Data Analysis

Published:2015-03 Issue: Volume:738-739 Page:670-673
ISSN:1662-7482
Container-title:Applied Mechanics and Materials
language:
Short-container-title:AMM

Author:

Niu Lin¹,Li Ya Jin²,Huang Jin Xin¹,Zhan Jie¹,Ma Meng Chao¹,Cui Jin Tao¹,Lu Guo Tao¹

Affiliation:

1. State Grid of China Technology College

2. Shandong University

Abstract

Based on multi-source substation equipment inspection data, this article achieve fault diagnosis in the case of incomplete understanding of the mechanism of substation equipment, by establishing fault diagnosis model.This article selected a substation equipment failures and operational information in different conditions as simulation study. The simulation results show the feasibility of the algorithm. Compared with the traditional fault diagnosis model, this method is more flexible , have a stronger ability to handle noisy data and good prospects.

Publisher

Trans Tech Publications, Ltd.

Link

https://www.scientific.net/AMM.738-739.670.pdf

Reference8 articles.

1. GUO Chuang-xin, PENG Ming-wei, LIU Yi. Novel approach for fault diagnosis of the power grid with information fusion of multi-data resources[J]. Proceedings of the CSEE, 2009, 29(31): 1-7.

2. Guo Chuangxin，Zhu Chuanbai，Cao Yijia，et al．State of arts of fault diagnosis of power systems[J] ． Automation of Electric Power Systems，2006，30(8)：102-107(in Chinese).

3. ANGELO V, PLAMEN P. An eveolutionary approach to fuzzy rule-based model systhesis using indices for rules[J]. Fuzzy Sets and Systems, 2003, 127(3): 325-338.

4. XU Yan, LIU Jin-sheng, ZHANG Ya-gang, et al. Study of application of hierarchical luster analysis in power net fault location[J]. Power System Protection and Control, 2010, 38(12): 13-18.

5. SUN Ji-xiang. Modern pattern recognition[M]. Second edition. Beijing: Higher Education Press, (2008).