Anomaly Detection of Polymer Resettable Circuit Protection Devices

As circuit protection devices, failure or abnormal behavior of polymer positive-temperature-coefficient resettable devices can cause damage to circuits. It is necessary to detect anomalies in the resettable circuit protection devices to provide early warning of failure and avoid damage to a circuit. In this paper, a novel anomaly detection method, the cross-validation-based sequential probability ratio test, is developed and applied to the failure precursor parameters of the resettable circuit protection devices to conduct anomaly detection. The cross-validation-based sequential probability ratio test integrates the advantages of both the sequential probability ratio test for in situ anomaly detection and the cross-validation technique for model parameter selection to reduce the probability of false and missed alarms in anomaly detection. The cross-validation-based sequential probability ratio test solves the model parameter selection difficulty of the traditional sequential probability ratio test and improves its performance in anomaly detection.

[1]  J. Andel Sequential Analysis , 2022, The SAGE Encyclopedia of Research Design.

[2]  M. Pecht,et al.  A Wireless Sensor System for Prognostics and Health Management , 2010, IEEE Sensors Journal.

[3]  K. Worden,et al.  Statistical Damage Classification Using Sequential Probability Ratio Tests , 2002 .

[4]  李翔,et al.  A new support vector machine optimized by improved particle swarm optimization and its application , 2006 .

[5]  Ricardo Massa Ferreira Lima,et al.  GA-based method for feature selection and parameters optimization for machine learning regression applied to software effort estimation , 2010, Inf. Softw. Technol..

[6]  M. Stone,et al.  Cross‐Validatory Choice and Assessment of Statistical Predictions , 1976 .

[7]  Michael G. Pecht,et al.  A prognostics and health management roadmap for information and electronics-rich systems , 2010, Microelectron. Reliab..

[8]  M.G. Pecht,et al.  Prognostics and health management of electronics , 2008, IEEE Transactions on Components and Packaging Technologies.

[9]  Browne,et al.  Cross-Validation Methods. , 2000, Journal of mathematical psychology.

[10]  Ping-Feng Pai,et al.  Software reliability forecasting by support vector machines with simulated annealing algorithms , 2006, J. Syst. Softw..

[11]  B. Efron Estimating the Error Rate of a Prediction Rule: Improvement on Cross-Validation , 1983 .

[12]  Youn Min Chou,et al.  Transforming Non-Normal Data to Normality in Statistical Process Control , 1998 .

[13]  Michael G. Pecht,et al.  Sensor Systems for Prognostics and Health Management , 2010, Sensors.

[14]  Michael Pecht,et al.  Failure Precursors for Polymer Resettable Fuses , 2010, IEEE Transactions on Device and Materials Reliability.

[15]  Kuan-Yu Chen,et al.  Forecasting systems reliability based on support vector regression with genetic algorithms , 2007, Reliab. Eng. Syst. Saf..

[16]  Kenny C. Gross,et al.  Proactive Fault Monitoring in Enterprise Servers , 2005, CDES.

[17]  Michael G. Pecht,et al.  A fusion prognostics method for remaining useful life prediction of electronic products , 2009, 2009 IEEE International Conference on Automation Science and Engineering.

[18]  Marion R. Reynolds,et al.  The SPRT control chart for the process mean with samples starting at fixed times , 2001 .

[19]  P. Lall,et al.  Prognostics and health management of electronics , 2006, 2006 11th International Symposium on Advanced Packaging Materials: Processes, Properties and Interface.

[20]  D. Cox,et al.  An Analysis of Transformations , 1964 .

[21]  Adrian Miron A WAVELET APPROACH FOR DEVELOPMENT AND APPLICATION OF A STOCHASTIC PARAMETER SIMULATION SYSTEM , 2001 .

[22]  Ching-Ping Wong,et al.  Study on effect of carbon black on behavior of conductive polymer composites with positive temperature coefficient , 2000 .

[23]  Zne-Jung Lee,et al.  Parameter determination of support vector machine and feature selection using simulated annealing approach , 2008, Appl. Soft Comput..

[24]  M. Pecht,et al.  Physics-of-failure: an approach to reliable product development , 1995, IEEE 1995 International Integrated Reliability Workshop. Final Report.