Anomaly detection in time series data using a combination of wavelets, neural networks and Hilbert transform

被引：16

作者：

Kanarachos, S. ^{[1
]}

Mathew, J. ^{[1
]}

Chroneos, A. ^{[1
]}

Fitzpatrick, M. ^{[1
]}

机构：

[1] Coventry Univ, Fac Engn & Comp, Coventry, W Midlands, England

来源：

2015 6TH INTERNATIONAL CONFERENCE ON INFORMATION, INTELLIGENCE, SYSTEMS AND APPLICATIONS (IISA) | 2015年

关键词：

anomaly detection; wavelets; neural networks; Hilbert;

D O I：

10.1109/IISA.2015.7388055

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper, a new signal processing algorithm for detecting anomalies in time series data is proposed. Real time detection of anomalies is crucial in structural health monitoring applications as it can be used for an early detection of structural damage as well as for discovery of abnormal operating conditions that can shorten a structure's life. A new algorithm -a combination of wavelets, neural networks and Hilbert transform-is presented and discussed in this study. The algorithm has been evaluated for a number of benchmark tests, commonly used in the literature, and has been found to perform robustly.

引用

页数：6

共 15 条

[1] Damage localization based on symbolic time series analysis [J].

Alamdari, Mehrisadat Makki ;

Samali, Bijan ;

Li, Jianchun .

STRUCTURAL CONTROL & HEALTH MONITORING, 2015, 22 (02) :374-393

[2]

Amer M., 2013, P ACM SIGKDD WORKSH, P8, DOI [10.1145/2500853.2500857, DOI 10.1145/2500853.2500857]

[3] Haar wavelets for efficient similarity search of time-series: With and without time warping [J].

Chan, FKP ;

Fu, AWC ;

Yu, C .

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2003, 15 (03) :686-705

[4] Multi-scale anomaly detection algorithm based on infrequent pattern of time series [J].

Chen, Xiao-Yun ;

Zhan, Yan-Yan .

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2008, 214 (01) :227-237

[5]

Dasgupta D., 1996, P 5 INT C INT SYST R

[6] AN OUTLIER MAP FOR SUPPORT VECTOR MACHINE CLASSIFICATION [J].

Debruyne, Michel .

ANNALS OF APPLIED STATISTICS, 2009, 3 (04) :1566-1580

[7] Bearing fault detection based on hybrid ensemble detector and empirical mode decomposition [J].

Georgoulas, George ;

Loutas, Theodore ;

Stylios, Chrysostomos D. ;

Kostopoulos, Vassilis .

MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2013, 41 (1-2) :510-525

[8]

Gu William, 2013, 2013 IEEE International Conference on Big Data, P50, DOI 10.1109/BigData.2013.6691733

[9]

Haykin Simon, 1994, Neural Networks, V2

[10]

Kanarachos S., 2006, P 5 WSEAS INT C CIRC, P209

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