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Kuiper test and autoregressive model-based approach for wireless sensor network fault diagnosis

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Abstract

Wireless sensor networks (WSNs) have recently received increasing attention in the areas of defense and civil applications of sensor networks. Automatic WSN fault detection and diagnosis is essential to assure system’s reliability. Proactive WSNs fault diagnosis approaches use embedded functions scanning sensor node periodically for monitoring the health condition of WSNs. But this approach may speed up the depletion of limited energy in each sensor node. Thus, there is an increasing interest in using passive diagnosis approach. In this paper, WSN anomaly detection model based on autoregressive (AR) model and Kuiper test-based passive diagnosis is proposed. First, AR model with optimal order is developed based on the normal working condition of WSNs using Akaike information criterion. The AR model then acts as a filter to process the future incoming signal from different unknown conditions. A health indicator based on Kuiper test, which is used to test the similarity between the training error of normal condition and residual of test conditions, is derived for indicating the health conditions of WSN. In this study, synthetic WSNs data under different cases/conditions were generated and used for validating the approach. Experimental results show that the proposed approach could differentiate WSNs normal conditions from faulty conditions. At last, the overall results presented in this paper demonstrate that our approach is effective for performing WSNs anomalies detection.

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Acknowledgments

The work described in this paper was supported in part by a collaborative project associated with China Electronic Product Reliability and Environmental Testing and Research Institute (CEPREI) from Guangdong Provincial Department of Science and Technology (Project number: 2011A011302002), in part by National Natural Science Foundation of China under Grant No. 51275474, in part by Zhejiang Provincial Natural Science Foundation of China under Grant No. LZ12E05002, and in part by the Open Research Project of the State Key Laboratory of Industrial Control Technology, Zhejiang University, China (No. ICT1443). The authors would like to thank Zhang Fan and Li Dong of CEPRI for providing technical support in this project, and would also like to thank the reviewers for their valuable comments and constructive suggestions to improve this paper.

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Authors and Affiliations

  1. College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou, China

    Xiaohang Jin, Yi Sun & Jihong Shan

  2. Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China

    Tommy W. S. Chow & Bill C. P. Lau

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  1. Xiaohang Jin
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Correspondence to Xiaohang Jin.

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Jin, X., Chow, T.W.S., Sun, Y. et al. Kuiper test and autoregressive model-based approach for wireless sensor network fault diagnosis. Wireless Netw 21, 829–839 (2015). https://doi.org/10.1007/s11276-014-0820-0

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  • DOI: https://doi.org/10.1007/s11276-014-0820-0

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