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计算机系统应用英文版:2015,24(1):98-103

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基于改进余弦相似度的粒子滤波故障预报

蒋欣^1,2, 王开军^1,2, 陈黎飞^1,2

(1.福建师范大学数学与计算机科学学院, 福州 350007;2.福建师范大学福建省网络安全与密码技术重点实验室, 福州 350007)

Particle Filter Fault Prediction Based on Improved Cosine Similarity

JIANG Xin^1,2, WANG Kai-Jun^1,2, CHEN Li-Fei^1,2

(1.Fujian Normal University, Mathematics and Computer Science College, Fuzhou 350007, China;2.Fujian Normal University, Fujian Province Network Security and Cryptography Laboratory, Fuzhou 350007, China)

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本文已被：浏览 1828次下载 2638次
Received:April 17, 2014 Revised:May 20, 2014

中文摘要: 现有的粒子滤波故障预报方法主要是通过粒子滤波算法得到对应时刻的预测值, 然后比较其与实际值的差值来对故障进行预报.从分析设备正常工作的时间序列数据与潜在故障引起的异常数据之间的相似性的新角度, 设计了系统正常度和系统异常度来判别设备是否正常运行, 进而对潜在的故障进行预测.实验结果验证了该方法的可行性, 并能及时准确地预报出系统故障.

中文关键词: 相似性度量正常度异常度粒子滤波故障预报

Abstract:The existing particle filter fault prediction method is the corresponding time's predictive value obtained from particle filter algorithm. The particle filter algorithm predicts the system fault by comparison of the predict value and actual value. This paper designs a new method identifying the function of system equipment. By analysis of the normal working equipment's time-series data and abnormal data, it can predict the potential system fault. Experimental results demonstrate the feasibility of this method and the accuracy of predicting system fault.

keywords: similarity measure normal degree abnormal degree particle filter fault prediction

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基金项目:国家自然科学基金项目(61175123);福建省自然科学基金(2013J01223);福建省高校服务海西建设重点项目

引用文本：
蒋欣,王开军,陈黎飞.基于改进余弦相似度的粒子滤波故障预报.计算机系统应用,2015,24(1):98-103
JIANG Xin,WANG Kai-Jun,CHEN Li-Fei.Particle Filter Fault Prediction Based on Improved Cosine Similarity.COMPUTER SYSTEMS APPLICATIONS,2015,24(1):98-103

Author Name	Affiliation
JIANG Xin	Fujian Normal University, Mathematics and Computer Science College, Fuzhou 350007, China Fujian Normal University, Fujian Province Network Security and Cryptography Laboratory, Fuzhou 350007, China
WANG Kai-Jun	Fujian Normal University, Mathematics and Computer Science College, Fuzhou 350007, China Fujian Normal University, Fujian Province Network Security and Cryptography Laboratory, Fuzhou 350007, China
CHEN Li-Fei	Fujian Normal University, Mathematics and Computer Science College, Fuzhou 350007, China Fujian Normal University, Fujian Province Network Security and Cryptography Laboratory, Fuzhou 350007, China

Author Name	Affiliation
JIANG Xin	Fujian Normal University, Mathematics and Computer Science College, Fuzhou 350007, China Fujian Normal University, Fujian Province Network Security and Cryptography Laboratory, Fuzhou 350007, China
WANG Kai-Jun	Fujian Normal University, Mathematics and Computer Science College, Fuzhou 350007, China Fujian Normal University, Fujian Province Network Security and Cryptography Laboratory, Fuzhou 350007, China
CHEN Li-Fei	Fujian Normal University, Mathematics and Computer Science College, Fuzhou 350007, China Fujian Normal University, Fujian Province Network Security and Cryptography Laboratory, Fuzhou 350007, China