Towards a data analytics framework for medium voltage power cable lifetime mangement

Jose I. Aizpurua, Brian G. Stewart, Stephen D. J. McArthur, Nitin Jajware, Martin Kearns, Sarijit Banerjee

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

Power cables are critical assets for the reliable and cost-effective operation of nuclear power plants. The unexpected failure of a power cable can lead to lack of export capability or even to catastrophic failures depending on the plant response to the cable failure and associated circuit. Prognostics and health management (PHM) strategies examine the health of the cable periodically to identify early indicators of anomalies, diagnose faults, and predict the remaining useful life. Traditionally, PHM-related strategies for power cables are considered separately with the associated penalties involved with this decision. Namely, there is a lack of consideration of the interactions and correlations between failure modes and PHM tests, which results in scalability issues of ad-hoc experiments, and accordingly incapability to exploit the full potential for PHM strategies in an effective manner. An effective and flexible PHM strategy should be able to consider not only different PHM strategies independently, but also it should be able to fuse these tests into a cable health state indicator. The main contribution of this paper is the proposal of a PHM-oriented data analytics framework for medium voltage power cable lifetime management which incorporates anomaly detection, diagnostics, prognostics, and health index modules. This framework includes the characterization of existing data sources and PHM-oriented data analytics for cable condition monitoring. This process enables the creation of a database of existing datasets, identification of complementary PHM techniques for an improved condition monitoring, and implementation of an end-to-end PHM framework.
LanguageEnglish
Title of host publication11th Nuclear Plant Instrumentation, Control and Human Machine Interface Technology
Place of PublicationLa Grange Park, Ill.
PublisherAmerican Nuclear Society
Number of pages10
Publication statusPublished - 9 Feb 2019
Event11th Nuclear Plant Instrumentation, Control and Human Machine Interface Technologies Conference

- Florida, Orlando, United States
Duration: 9 Feb 201914 Feb 2019
http://npic-hmit.ans.org/

Conference

Conference11th Nuclear Plant Instrumentation, Control and Human Machine Interface Technologies Conference

CountryUnited States
CityOrlando
Period9/02/1914/02/19
Internet address

Fingerprint

Cables
Health
Electric potential
Condition monitoring
Electric fuses
Failure modes
Nuclear power plants
Failure analysis
Scalability
Networks (circuits)

Keywords

  • data analytics
  • prognostic and health management
  • condition monitoring

Cite this

Aizpurua, J. I., Stewart, B. G., McArthur, S. D. J., Jajware, N., Kearns, M., & Banerjee, S. (2019). Towards a data analytics framework for medium voltage power cable lifetime mangement. In 11th Nuclear Plant Instrumentation, Control and Human Machine Interface Technology La Grange Park, Ill.: American Nuclear Society.
Aizpurua, Jose I. ; Stewart, Brian G. ; McArthur, Stephen D. J. ; Jajware, Nitin ; Kearns, Martin ; Banerjee, Sarijit. / Towards a data analytics framework for medium voltage power cable lifetime mangement. 11th Nuclear Plant Instrumentation, Control and Human Machine Interface Technology. La Grange Park, Ill. : American Nuclear Society, 2019.
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abstract = "Power cables are critical assets for the reliable and cost-effective operation of nuclear power plants. The unexpected failure of a power cable can lead to lack of export capability or even to catastrophic failures depending on the plant response to the cable failure and associated circuit. Prognostics and health management (PHM) strategies examine the health of the cable periodically to identify early indicators of anomalies, diagnose faults, and predict the remaining useful life. Traditionally, PHM-related strategies for power cables are considered separately with the associated penalties involved with this decision. Namely, there is a lack of consideration of the interactions and correlations between failure modes and PHM tests, which results in scalability issues of ad-hoc experiments, and accordingly incapability to exploit the full potential for PHM strategies in an effective manner. An effective and flexible PHM strategy should be able to consider not only different PHM strategies independently, but also it should be able to fuse these tests into a cable health state indicator. The main contribution of this paper is the proposal of a PHM-oriented data analytics framework for medium voltage power cable lifetime management which incorporates anomaly detection, diagnostics, prognostics, and health index modules. This framework includes the characterization of existing data sources and PHM-oriented data analytics for cable condition monitoring. This process enables the creation of a database of existing datasets, identification of complementary PHM techniques for an improved condition monitoring, and implementation of an end-to-end PHM framework.",
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Aizpurua, JI, Stewart, BG, McArthur, SDJ, Jajware, N, Kearns, M & Banerjee, S 2019, Towards a data analytics framework for medium voltage power cable lifetime mangement. in 11th Nuclear Plant Instrumentation, Control and Human Machine Interface Technology. American Nuclear Society, La Grange Park, Ill., 11th Nuclear Plant Instrumentation, Control and Human Machine Interface Technologies Conference

, Orlando, United States, 9/02/19.

Towards a data analytics framework for medium voltage power cable lifetime mangement. / Aizpurua, Jose I.; Stewart, Brian G.; McArthur, Stephen D. J.; Jajware, Nitin; Kearns, Martin; Banerjee, Sarijit.

11th Nuclear Plant Instrumentation, Control and Human Machine Interface Technology. La Grange Park, Ill. : American Nuclear Society, 2019.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

TY - GEN

T1 - Towards a data analytics framework for medium voltage power cable lifetime mangement

AU - Aizpurua, Jose I.

AU - Stewart, Brian G.

AU - McArthur, Stephen D. J.

AU - Jajware, Nitin

AU - Kearns, Martin

AU - Banerjee, Sarijit

PY - 2019/2/9

Y1 - 2019/2/9

N2 - Power cables are critical assets for the reliable and cost-effective operation of nuclear power plants. The unexpected failure of a power cable can lead to lack of export capability or even to catastrophic failures depending on the plant response to the cable failure and associated circuit. Prognostics and health management (PHM) strategies examine the health of the cable periodically to identify early indicators of anomalies, diagnose faults, and predict the remaining useful life. Traditionally, PHM-related strategies for power cables are considered separately with the associated penalties involved with this decision. Namely, there is a lack of consideration of the interactions and correlations between failure modes and PHM tests, which results in scalability issues of ad-hoc experiments, and accordingly incapability to exploit the full potential for PHM strategies in an effective manner. An effective and flexible PHM strategy should be able to consider not only different PHM strategies independently, but also it should be able to fuse these tests into a cable health state indicator. The main contribution of this paper is the proposal of a PHM-oriented data analytics framework for medium voltage power cable lifetime management which incorporates anomaly detection, diagnostics, prognostics, and health index modules. This framework includes the characterization of existing data sources and PHM-oriented data analytics for cable condition monitoring. This process enables the creation of a database of existing datasets, identification of complementary PHM techniques for an improved condition monitoring, and implementation of an end-to-end PHM framework.

AB - Power cables are critical assets for the reliable and cost-effective operation of nuclear power plants. The unexpected failure of a power cable can lead to lack of export capability or even to catastrophic failures depending on the plant response to the cable failure and associated circuit. Prognostics and health management (PHM) strategies examine the health of the cable periodically to identify early indicators of anomalies, diagnose faults, and predict the remaining useful life. Traditionally, PHM-related strategies for power cables are considered separately with the associated penalties involved with this decision. Namely, there is a lack of consideration of the interactions and correlations between failure modes and PHM tests, which results in scalability issues of ad-hoc experiments, and accordingly incapability to exploit the full potential for PHM strategies in an effective manner. An effective and flexible PHM strategy should be able to consider not only different PHM strategies independently, but also it should be able to fuse these tests into a cable health state indicator. The main contribution of this paper is the proposal of a PHM-oriented data analytics framework for medium voltage power cable lifetime management which incorporates anomaly detection, diagnostics, prognostics, and health index modules. This framework includes the characterization of existing data sources and PHM-oriented data analytics for cable condition monitoring. This process enables the creation of a database of existing datasets, identification of complementary PHM techniques for an improved condition monitoring, and implementation of an end-to-end PHM framework.

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M3 - Conference contribution book

BT - 11th Nuclear Plant Instrumentation, Control and Human Machine Interface Technology

PB - American Nuclear Society

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ER -

Aizpurua JI, Stewart BG, McArthur SDJ, Jajware N, Kearns M, Banerjee S. Towards a data analytics framework for medium voltage power cable lifetime mangement. In 11th Nuclear Plant Instrumentation, Control and Human Machine Interface Technology. La Grange Park, Ill.: American Nuclear Society. 2019