{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T16:14:25Z","timestamp":1776183265900,"version":"3.50.1"},"reference-count":129,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2020,4,8]],"date-time":"2020-04-08T00:00:00Z","timestamp":1586304000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002347","name":"Bundesministerium f\u00fcr Bildung und Forschung","doi-asserted-by":"publisher","award":["03El6012A"],"award-info":[{"award-number":["03El6012A"]}],"id":[{"id":"10.13039\/501100002347","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state-of-the-art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale.<\/jats:p>","DOI":"10.3390\/s20072099","type":"journal-article","created":{"date-parts":[[2020,4,9]],"date-time":"2020-04-09T03:40:19Z","timestamp":1586403619000},"page":"2099","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":98,"title":["Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4126-4785","authenticated-orcid":false,"given":"Martin W.","family":"Hoffmann","sequence":"first","affiliation":[{"name":"ABB AG, Corporate Research Germany, 68526 Ladenburg, Germany"}]},{"given":"Stephan","family":"Wildermuth","sequence":"additional","affiliation":[{"name":"ABB AG, Corporate Research Germany, 68526 Ladenburg, Germany"}]},{"given":"Ralf","family":"Gitzel","sequence":"additional","affiliation":[{"name":"ABB AG, Corporate Research Germany, 68526 Ladenburg, Germany"}]},{"given":"Aydin","family":"Boyaci","sequence":"additional","affiliation":[{"name":"ABB AG, Corporate Research Germany, 68526 Ladenburg, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9200-5025","authenticated-orcid":false,"given":"J\u00f6rg","family":"Gebhardt","sequence":"additional","affiliation":[{"name":"ABB AG, Corporate Research Germany, 68526 Ladenburg, Germany"}]},{"given":"Holger","family":"Kaul","sequence":"additional","affiliation":[{"name":"ABB AG, Corporate Research Germany, 68526 Ladenburg, Germany"}]},{"given":"Ido","family":"Amihai","sequence":"additional","affiliation":[{"name":"ABB AG, Corporate Research Germany, 68526 Ladenburg, Germany"}]},{"given":"Bodo","family":"Forg","sequence":"additional","affiliation":[{"name":"Heimann Sensor GmbH, 01109 Dresden, Germany"}]},{"given":"Michael","family":"Suriyah","sequence":"additional","affiliation":[{"name":"Institute of Electric Energy Systems and High Voltage Technology, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany"}]},{"given":"Thomas","family":"Leibfried","sequence":"additional","affiliation":[{"name":"Institute of Electric Energy Systems and High Voltage Technology, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany"}]},{"given":"Volker","family":"Stich","sequence":"additional","affiliation":[{"name":"FIR (Institute for Industrial Management) at the RWTH Aachen University, 52074Aachen, Germany"}]},{"given":"Jan","family":"Hicking","sequence":"additional","affiliation":[{"name":"FIR (Institute for Industrial Management) at the RWTH Aachen University, 52074Aachen, Germany"}]},{"given":"Martin","family":"Bremer","sequence":"additional","affiliation":[{"name":"FIR (Institute for Industrial Management) at the RWTH Aachen University, 52074Aachen, Germany"}]},{"given":"Lars","family":"Kaminski","sequence":"additional","affiliation":[{"name":"FIR (Institute for Industrial Management) at the RWTH Aachen University, 52074Aachen, Germany"}]},{"given":"Daniel","family":"Beverungen","sequence":"additional","affiliation":[{"name":"Chair of Business Information Systems, Paderborn University, 33098 Paderborn, Germany"}]},{"given":"Philipp","family":"zur Heiden","sequence":"additional","affiliation":[{"name":"Chair of Business Information Systems, Paderborn University, 33098 Paderborn, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9954-462X","authenticated-orcid":false,"given":"Tanja","family":"Tornede","sequence":"additional","affiliation":[{"name":"Software Innovation Campus Paderborn, Department of Computer Science and Heinz Nixdorf Institute, Paderborn University, 33098 Paderborn, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1007\/s10273-019-2408-x","article-title":"Zielvorgaben und staatliche Strategien f\u00fcr eine nachhaltige Energieversorgung","volume":"99","author":"Schiffer","year":"2019","journal-title":"Wirtschaftsdienst"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1016\/j.enpol.2016.05.004","article-title":"Coal, nuclear and renewable energy policies in Germany: From the 1950s to the \u2018Energiewende\u2019","volume":"99","author":"Renn","year":"2016","journal-title":"Energy Policy"},{"key":"ref_3","unstructured":"(2019). Bericht zum Zustand und Ausbau der Verteilernetze 2018, Bundesnetzagentur f\u00fcr Elektrizit\u00e4t, Gas, Telekommunikation, Post und Eisenbahnen. Report."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/j.energy.2016.06.029","article-title":"Distributed solar and wind power\u2013Impact on distribution losses","volume":"112","author":"Goop","year":"2016","journal-title":"Energy"},{"key":"ref_5","unstructured":"European SmartGrids Technology Platform (2006). Vision and Strategy for Europe\u2019s Electricity Networks of the Future. EUR 22040. European Commission."},{"key":"ref_6","unstructured":"Flexibilit\u00e4t im Stromversorgungssystem (2017). Bestandsaufnahme, Hemmnisse und Ans\u00e4tze zur verbesserten Erschlie\u00dfung von Flexibilit\u00e4t, Bundesnetzagentur f\u00fcr Elektrizit\u00e4t, Gas, Telekommunikation, Post und Eisenbahnen. Discussion Paper."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1007\/s00502-017-0549-4","article-title":"Neue Anforderungen an die Mittelspannungs- und Niederspannungs-Stromversorgung im st\u00e4dtischen und l\u00e4ndlichen Raum","volume":"134","author":"Schmautzer","year":"2017","journal-title":"Elektrotech. Inftech"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Kumar, G.V.B., Sarojini, R.K., Palanisamy, K., Padmanaban, S., and Holm-Nielsen, J.B. (2019). Large Scale Renewable Energy Integration: Issues and Solutions. Energies, 12.","DOI":"10.3390\/en12101996"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Mobley, R.K. (2002). An Introduction to Predictive Maintenance, Elsevier.","DOI":"10.1016\/B978-075067531-4\/50006-3"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Friedman, J., Hastie, T., and Tibshirani, R. (2001). The elements of statistical learning, Springer.","DOI":"10.1007\/978-0-387-21606-5"},{"key":"ref_11","unstructured":"Rykov, M. (2020, March 30). The Top 10 Industrial AI use cases. Available online: https:\/\/iot-analytics.com\/the-top-10-industrial-ai-use-cases."},{"key":"ref_12","unstructured":"Rykov, M., and Scully, P. (2019). Industrial AI Market Report 2020\u20132025, IoT Analytics."},{"key":"ref_13","unstructured":"Turrin, S., Deck, B., Egman, M., and Cavalli, L. (2015, January 15\u201318). Medium voltage equipment monitoring and diagnostics: Technological maturity makes concepts compatible with expectations. Proceedings of the 23rd International Conference on Electricity Distribution, Lyon, France."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1108\/13552510410553244","article-title":"A decision analysis model for maintenance policy selection using a CMMS","volume":"10","author":"Labib","year":"2004","journal-title":"J. Qual. Maint. Eng."},{"key":"ref_15","unstructured":"Uzelac, N., Heinrich, C., Pater, R., Arnold, J., Eichhoff, D., Ferraro, V., Gariboldi, N., Germain, M., Gioseffi, A., and Ito, T. (2018). Non-intrusive methods for condition assessment of distribution and transmission switchgear. Technical Brochures 737, CIGRE."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Jadin, M.S., and Taib, S. (2012). Recent progress in diagnosing the reliability of electrical equipment by using infrared thermography. Infrared Phys. Technol., 236\u2013245.","DOI":"10.1016\/j.infrared.2012.03.002"},{"key":"ref_17","unstructured":"Russell, S., and Norvig, P. (2002). Artificial Intelligence: A Modern Approach, Prentice Hall."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Amihai, I., Gitzel, R., Kotriwala, A.M., Pareschi, D., Subbiah, S., and Sosale, G. (2018, January 11\u201314). An Industrial Case Study Using Vibration Data and Machine Learning to Predict Asset Health. Proceedings of the 2018 IEEE 20th Conference on Business Informatics (CBI), Vienna, Austria.","DOI":"10.1109\/CBI.2018.00028"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Gitzel, R., Amihai, I., and Garcia Perez, M. (2019, January 4\u20136). Towards Robust ML-Algorithms for the Condition Monitoring of Switchgear. Proceedings of the 1st Conference on Societal Automation, Krakow, Poland.","DOI":"10.1109\/SA47457.2019.8938089"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Amihai, I., Chioua, M., Gitzel, R., Kotriwala, A.M., Pareschi, D., Sosale, G., and Subbiah, S. (2018, January 18\u201320). Modeling Machine Health Using Gated Recurrent Units with Entity Embeddings and K-Means Clustering. Proceedings of the 2018 IEEE 16th International Conference on Industrial Informatics (INDIN), Porto, Portugal.","DOI":"10.1109\/INDIN.2018.8472065"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1109\/MPAE.2005.1436498","article-title":"Time management for assets: Chronological strategies for power system asset management","volume":"3","author":"Shahidehpour","year":"2005","journal-title":"IEEE Power Energy Mag."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.mfglet.2014.12.001","article-title":"A cyber-physical systems architecture for industry 4.0-based manufacturing systems","volume":"3","author":"Lee","year":"2015","journal-title":"Manuf. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/s12525-017-0270-5","article-title":"Conceptualizing smart service systems","volume":"29","author":"Beverungen","year":"2019","journal-title":"Electron. Mark."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1016\/j.procir.2016.11.152","article-title":"The digital twin: Realizing the cyber-physical production system for industry 4.0","volume":"61","author":"Uhlemann","year":"2017","journal-title":"Procedia Cirp"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1016\/j.eng.2019.01.014","article-title":"Digital Twins and Cyber\u2013Physical Systems toward Smart Manufacturing and Industry 4.0: Correlation and Comparison","volume":"5","author":"Tao","year":"2019","journal-title":"Engineering"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3585","DOI":"10.1109\/ACCESS.2018.2793265","article-title":"Digital Twin and Big Data Towards Smart Manufacturing and Industry 4.0: 360 Degree Comparison","volume":"6","author":"Qi","year":"2018","journal-title":"IEEE Access"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1109\/TPWRD.2006.876661","article-title":"Estimation of the Lifetime of the Electrical Components in Distribution Networks","volume":"22","author":"Zhang","year":"2007","journal-title":"IEEE Trans. Power Delivery"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1183","DOI":"10.1109\/TDEI.2007.4339478","article-title":"Component reliability modeling of distribution systems based on the evaluation of failure statistics","volume":"14","author":"Zhang","year":"2007","journal-title":"IEEE Trans. Dielectr. Electr. Insul."},{"key":"ref_29","unstructured":"(1996). IEEE Guide for Diagnostics and Failure Investigation of Power Circuit Breakers. IEEE Std C37.10-1995, IEEE."},{"key":"ref_30","unstructured":"(2001). IEEE Guide for the Selection of Monitoring for Circuit Breakers. IEEE Std C37.10.1-2000, IEEE."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Paoletti, G.J., and Herman, G. (2013, January 14\u201318). Monitoring of electrical equipment failure indicators and zero-planned outages: Past, present and future maintenance practices. Proceedings of the Industry Applications Society 60th Annual Petroleum and Chemical Industry Conference, Wilwaukee, WI, USA.","DOI":"10.1109\/PCICon.2013.6666042"},{"key":"ref_32","unstructured":"Saeli, C., Serpellini, F., Gatti, C., Bianco, A., and de Natale, G. (2012, January 19\u201321). How to guarantee continuity of supply and reliability in the smart grids?. Diagnostic systems in the MV network components, circuit breakers and switch disconnectors. In Proceedings of the 2012 Petroleum and Chemical Industry Conference Europe Conference Proceedings (PCIC EUROPE), Prague, Czech Republik."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Andru\u015fc\u0103, M., Adam, M., Pantelimon, R., and Baraboi, A. (2013, January 23\u201325). About diagnosis of circuit breakers. Proceedings of the 2013 8th International Symposium on Advanced Topics in Electrical Engineering (ATEE), Bucharest, Romania.","DOI":"10.1109\/ATEE.2013.6563368"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1724","DOI":"10.1109\/61.193977","article-title":"Mechanical failure detection of circuit breakers","volume":"3","author":"Lai","year":"1988","journal-title":"IEEE Trans. Power Delivery"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2458","DOI":"10.1109\/TPWRD.2005.855486","article-title":"Continuous monitoring of circuit breakers using vibration analysis","volume":"20","author":"Hoidalen","year":"2005","journal-title":"IEEE Trans. Power Delivery"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"454","DOI":"10.1109\/TPWRD.2003.809615","article-title":"New fault diagnosis of circuit breakers","volume":"18","author":"Lee","year":"2003","journal-title":"IEEE Trans. Power Delivery"},{"key":"ref_37","unstructured":"Hou, N. (1998, January 18\u201321). The infrared thermography diagnostic technique of high-voltage electrical equipments with internal faults. Proceedings of the POWERCON \u201998. 1998 International Conference on Power System Technology. Proceedings (Cat. No.98EX151), Beijing, China."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Craig, T. (2017, January 26\u201328). Condition monitoring in low voltage circuit breaker technology. Proceedings of the IET International Conference on Resilience of Transmission and Distribution Networks (RTDN 2017), Birmingham, UK.","DOI":"10.1049\/cp.2017.0341"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.applthermaleng.2013.07.028","article-title":"Application of infrared thermography for predictive\/preventive maintenance of thermal defect in electrical equipment","volume":"61","author":"Huda","year":"2013","journal-title":"Appl. Therm. Eng."},{"key":"ref_40","unstructured":"IEC (2000). IEC 60270, High-voltage test techniques\u2014Partial discharge measurement, Version 2000, IEC. [3rd ed.]."},{"key":"ref_41","unstructured":"Janus, P. (2012). Acoustic Emission Properties of Partial Discharges in the Time-Domain and Their Applications, KTH. XR-EE-ETK 2012 004."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"K\u00fcchler, A. (2017). Hochspannungstechnik (in german), esp. Ch 3.6: Teilentladungen, Springer.","DOI":"10.1007\/978-3-662-54700-7"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Florkowski, M., Florkowska, B., and Zydron, P. (2014, January 8\u201311). Influence of high voltage harmonics on partial discharge patterns modulation. Proceedings of the 2014 ICHVE International Conference on High Voltage Engineering and Application, Poznan, Poland.","DOI":"10.1109\/ICHVE.2014.7035403"},{"key":"ref_44","unstructured":"(2014). IEEE Recommended Practice and Requirements for Harmonic Control in Electric Power Systems. IEEE Std 519-2014 (Revision of IEEE Std 519-1992), IEEE."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Stroganov, K., Kronidov, T., Luylin, B., Kalinin, V., and Plessky, V.P. (2014, January 23\u201326). SAW temperature sensors for electric power transmission lines. Proceedings of the European Frequency and Time Forum (EFTF), Neuchatel, Switzerland.","DOI":"10.1109\/EFTF.2014.7331452"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"8811","DOI":"10.1109\/TIE.2019.2891447","article-title":"A -12.3 dBm UHF Passive RFID Sense Tag for Grid Thermal Monitoring","volume":"66","author":"Wang","year":"2019","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Lu, H., and Yuan, Y. (2014, January 15\u201317). Substation equipment temperature monitoring system design based on self-powered wireless temperature sensors. Proceedings of the 2nd International Conference on Systems and Informatics (ICSAI), Shanghai, China.","DOI":"10.1109\/ICSAI.2014.7009287"},{"key":"ref_48","unstructured":"Wildermuth, S., Ahrend, U., and Hochlehnert, M. (2014, January 3\u20134). Infrared Temperature Measurement System for Condition Monitoring of High Voltage Generator Circuit Breakers. Proceedings of the 17. ITG\/GMA Symposium, Sensors and Measuring Systems, Nuremberg, Germany."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.infrared.2016.12.003","article-title":"Diagnosis of the three-phase induction motor using thermal imaging","volume":"81","author":"Glowacz","year":"2017","journal-title":"Infrared Phys. Technol."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.infrared.2013.03.006","article-title":"Infrared thermography for condition monitoring\u2014A review","volume":"60","author":"Bagavathiappan","year":"2013","journal-title":"Infrared Phys. Technol."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Chaturvedi, D.K., Iqbal, M.S., and Pratap, M. (2015, January 27\u201328). Intelligent health monitoring system for three phase induction motor using infrared thermal image. Proceedings of the 2015 international conference on energy economics and environment (ICEEE), Noida, India.","DOI":"10.1109\/EnergyEconomics.2015.7235083"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Li, B., Zhu, X., Zhao, S., and Niu, W. (2006, January 22\u201326). HV Power Equipment Diagnosis Based on Infrared Imaging Analyzing. Proceedings of the 2006 International Conference on Power System Technology, Chongqing, China.","DOI":"10.1109\/ICPST.2006.321512"},{"key":"ref_53","unstructured":"Smedberg, M. (2006). Thermographic decision support--detecting and classifying faults in infrared images. [Master\u2019s Thesis, Royal Institute of Technology]."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Chou, Y., and Yao, L. (2009, January 4\u20137). Automatic Diagnostic System of Electrical Equipment Using Infrared Thermography. Proceedings of the 2009 International Conference of Soft Computing and Pattern Recognition, Malacca, Malaysia.","DOI":"10.1109\/SoCPaR.2009.41"},{"key":"ref_55","unstructured":"So, A.T.P., Chan, W.L., Tse, C.T., and Lee, K.K. (1993, January 19\u201322). Fuzzy logic based automatic diagnosis of power apparatus by infrared imaging. Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems, Yokohama, Japan."},{"key":"ref_56","first-page":"346","article-title":"Modular online monitoring system to allow condition-based maintenance for medium voltage switchgear","volume":"2017","author":"Perdon","year":"2017","journal-title":"CIRED"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"2154","DOI":"10.1109\/TPWRD.2015.2423686","article-title":"Contact Force Monitoring and Its Application in Vacuum Circuit Breakers","volume":"32","author":"Tang","year":"2017","journal-title":"IEEE Trans. Power Delivery"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Hauschild, W., and Lemke, E. (2019). High-Voltage Test and Measuring Techniques, Chapter 4: Partial Discharge Measurement, Springer.","DOI":"10.1007\/978-3-319-97460-6"},{"key":"ref_59","unstructured":"IEC (2016). IEC TS 62478: High voltage test techniques\u2014Measurement of partial discharges by electromagnetic and acoustic methods, IEC."},{"key":"ref_60","unstructured":"(2020, March 30). ABB Ability(TM) Condition Monitoring for switchgear \u2013 SWICOM. Available online: https:\/\/new.abb.com\/medium-voltage\/service\/advanced-services\/condition-monitoring-for-switchgear-SWICOM."},{"key":"ref_61","unstructured":"Franke, U., and Sartori, P. (2019). Machine politics: Europe and the AI revolution, European Council on Foreign Relations."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1109\/MIE.2014.2312079","article-title":"Industrie 4.0: Hit or hype? [Industry Forum]","volume":"8","author":"Drath","year":"2014","journal-title":"IEEE Ind. Electron. Mag."},{"key":"ref_63","first-page":"70","article-title":"A new era","volume":"4","author":"Krueger","year":"2014","journal-title":"ABB Rev."},{"key":"ref_64","unstructured":"Sendler, U. Das Internet der Dinge, Dienste und Menschen. Industrie 4.0 grenzenlos, Springer."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"2367","DOI":"10.1007\/s00170-018-3106-3","article-title":"A reference framework and overall planning of industrial artificial intelligence (I-AI) for new application scenarios","volume":"101","author":"Zhang","year":"2019","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"ref_66","unstructured":"Ahlborn, K., Bachmann, G., Biegel, F., Bienert, J., Falk, S., Fay, A., Gamer, T., Garrels, K., Grotepass, J. (2019). Plattform Industrie 4.0: Technology Scenario \u2018Artificial Intelligence in Industrie 4.0\u2032."},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Gamer, T., Kloepper, B., and Hoernicke, M. (2019, January 14\u201317). The way toward autonomy in industry-taxonomy, process framework, enablers, and implications. Proceedings of the IECON 2019-45th Annual Conference of the IEEE Industrial Electronics Society, Lisbon, Portugal.","DOI":"10.1109\/IECON.2019.8927127"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"454","DOI":"10.1016\/j.ifacol.2019.06.104","article-title":"The Autonomous Industrial Plant-Future of Process Engineering, Operations and Maintenance","volume":"52","author":"Gamer","year":"2019","journal-title":"IFAC-PapersOnLine"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1007\/s00184-008-0220-5","article-title":"Remaining useful life in theory and practice","volume":"69","author":"Banjevic","year":"2009","journal-title":"Metrika"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.neucom.2018.03.067","article-title":"Time series feature extraction on basis of scalable hypothesis tests (tsfresh\u2014a python package)","volume":"307","author":"Christ","year":"2018","journal-title":"Neurocomputing"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1007\/s10618-016-0483-9","article-title":"The Great Time Series Classification Bake Off: A Review and Experimental Evaluation of Recent Algorithmic Advances","volume":"31","author":"Bagnall","year":"2017","journal-title":"Data Min. Knowl. Discov."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1093\/imamat\/24.1.59","article-title":"Nearest neighbour searches and the curse of dimensionality","volume":"24","author":"Marimont","year":"1979","journal-title":"IMA J. Appl. Math."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/0169-7439(87)80084-9","article-title":"Principal component analysis","volume":"2","author":"Wold","year":"1987","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/0165-1684(90)90158-U","article-title":"Fast Fourier transforms: A tutorial review and a state of the art","volume":"19","author":"Duhamel","year":"1990","journal-title":"Signal Process."},{"key":"ref_76","unstructured":"Stoica, P., and Moses, R.L. (2005). Spectral Analysis of Signals, Prentice Hall."},{"key":"ref_77","unstructured":"Ryuichi, I. (2002). New detection method of faulty distribution power apparatus using thermal images. SPIE, 4710."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"2293","DOI":"10.1109\/TIM.2016.2579440","article-title":"NSCT-based infrared image enhancement method for rotating machinery fault diagnosis","volume":"65","author":"Bai","year":"2016","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"5200","DOI":"10.1016\/j.eswa.2011.11.019","article-title":"Bearing fault prognosis based on health state probability estimation","volume":"39","author":"Kim","year":"2012","journal-title":"Expert Syst. Appl."},{"key":"ref_80","unstructured":"Drucker, H., Burges, C.J.C., Kaufman, L., Smola, A.J., and Vapnik, V. (1998). Support vector regression machines. Advances in neural Information Processing Systems, The MIT Press."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"812","DOI":"10.1109\/TII.2014.2349359","article-title":"Machine learning for predictive maintenance: A multiple classifier approach","volume":"11","author":"Susto","year":"2014","journal-title":"IEEE Trans. Ind. Inf."},{"key":"ref_82","unstructured":"Gugulothu, N., TV, V., Malhotra, P., Vig, L., Agarwal, P., and Shroff, G. (2017). Predicting remaining useful life using time series embeddings based on recurrent neural networks. arXiv."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1038\/323533a0","article-title":"Learning representations by back-propagating errors","volume":"323","author":"Rumelhart","year":"1986","journal-title":"Nature"},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1080\/00031305.1992.10475879","article-title":"An introduction to kernel and nearest-neighbor nonparametric regression","volume":"46","author":"Altman","year":"1992","journal-title":"Am. Stat."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"2276","DOI":"10.1109\/TIE.2016.2623260","article-title":"Direct remaining useful life estimation based on support vector regression","volume":"64","author":"Khelif","year":"2016","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_86","doi-asserted-by":"crossref","unstructured":"Rahmani, A.J., and Haddadnia, O. (2010, January 1\u20133). Seryasat Intelligent fault detection of electrical equipment in ground substations using thermo vision technique. Proceedings of the 2010 2nd International Conference on Mechanical and Electronics Engineering, Kyoto, Japan.","DOI":"10.1109\/ICMEE.2010.5558469"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.measurement.2014.07.010","article-title":"Feature extraction and classification for detecting the thermal faults in electrical installations","volume":"57","author":"Jadin","year":"2014","journal-title":"Measurement"},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"754","DOI":"10.1109\/TDEI.2013.6518945","article-title":"Application of K-Means method to pattern recognition in on-line cable partial discharge monitoring","volume":"20","author":"Peng","year":"2013","journal-title":"IEEE Trans. Dielectr. Electr. Insul."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"2380","DOI":"10.1109\/TPWRD.2011.2162858","article-title":"Using k-means clustering and parameter weighting for partial-discharge noise suppression","volume":"26","author":"Lin","year":"2011","journal-title":"IEEE Trans. Power Delivery"},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"1080","DOI":"10.1109\/TDEI.2015.7076809","article-title":"Partial discharge recognition in gas insulated switchgear based on multi-information fusion","volume":"22","author":"Li","year":"2015","journal-title":"IEEE Trans. Dielectr. Electr. Insul."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"1363","DOI":"10.1109\/TPWRD.2004.839187","article-title":"Separation of corona using wavelet packet transform and neural network for detection of partial discharge in gas-insulated substations","volume":"20","author":"Chang","year":"2005","journal-title":"IEEE Trans. Power Delivery"},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"721","DOI":"10.1109\/TDEI.2010.5492244","article-title":"Investigation of a comprehensive identification method used in acoustic detection system for GIS","volume":"17","author":"Si","year":"2010","journal-title":"IEEE Trans. Dielectr. Electr. Insul."},{"key":"ref_93","doi-asserted-by":"crossref","unstructured":"Nguyen, M.-T., Nguyen, V.-H., Yun, S.-J., and Kim, Y.-H. (2018). Recurrent neural network for partial discharge diagnosis in gas-insulated switchgear. Energies, 11.","DOI":"10.3390\/en11051202"},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"1044","DOI":"10.1109\/TPWRD.2017.2748146","article-title":"A RankBoost-based data-driven method to determine maintenance priority of circuit breakers","volume":"33","author":"Zhong","year":"2018","journal-title":"IEEE Trans. Power Delivery"},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.epsr.2016.08.018","article-title":"Substations SF6 circuit breakers: Reliability evaluation based on equipment condition","volume":"142","author":"Vianna","year":"2017","journal-title":"Electr. Power Syst. Res."},{"key":"ref_96","doi-asserted-by":"crossref","unstructured":"Zarkovic, M., and Stojkovic, Z. (2019). Artificial intelligence SF6 circuit breaker health assessment. Electr. Power Syst. Res., 175.","DOI":"10.1016\/j.epsr.2019.105912"},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1007\/s10257-008-0105-1","article-title":"The Service System Is the Basic Abstraction of Service Science","volume":"7","author":"Maglio","year":"2008","journal-title":"Inf. Syst. e-Bus. Manag."},{"key":"ref_98","unstructured":"(2009). Report to NIST on the Smart Grid Interoperability Standards Roadmap, Electric Power Research Institute (EPRI)."},{"key":"ref_99","unstructured":"Gergen, M.J., Campopiano, M.T., and Meyer, A.H. (2014). CPUC Opens Rulemaking to Incorporate Distributed Energy Resources Into Grid Planning Process for California\u2019s Investor-Owned Utilities, Latham\u2019s Clean Energy Law Report, Latham & Watkins LLP."},{"key":"ref_100","unstructured":"L\u00fcttenberg, H., Bartelheimer, C., and Beverungen, D. (2018, January 23\u201328). Designing Predictive Maintenance for Agricultural Machines. Proceedings of the Proceedings of the Twenty-Sixth European Conference on Information Systems (ECIS2018), Portsmouth, UK."},{"key":"ref_101","first-page":"16","article-title":"An IoT Based Predictive Connected Car Maintenance","volume":"4","author":"Dhall","year":"2017","journal-title":"Int. J. Interact. Multimed. Artif. Intell."},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"12114","DOI":"10.1109\/ACCESS.2017.2698060","article-title":"A Real-Time IR-Fusion Switchgear Contact Monitoring System (SCMS)","volume":"5","author":"Yan","year":"2017","journal-title":"IEEE Access"},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1109\/TPAMI.2011.108","article-title":"Machine learning for the New York City power grid","volume":"34","author":"Rudin","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1007\/s12599-018-0526-4","article-title":"Recombinant service systems engineering","volume":"60","author":"Beverungen","year":"2018","journal-title":"Bus. Inf. Syst. Eng."},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"1101","DOI":"10.1002\/dac.2417","article-title":"Internet of things","volume":"25","author":"Xia","year":"2012","journal-title":"Int. J. Commun. Syst."},{"key":"ref_106","first-page":"163","article-title":"Platform rules: Multi-sided platforms as regulators","volume":"1","author":"Boudreau","year":"2009","journal-title":"Platforms, Mark. Innov."},{"key":"ref_107","first-page":"92","article-title":"Strategies for two-sided markets","volume":"84","author":"Eisenmann","year":"2006","journal-title":"Harv. Bus. Rev."},{"key":"ref_108","unstructured":"Parker, G., and van Alstyne, M. (2012). A Digital Postal Platform: Definitions and a Roadmap, MIT."},{"key":"ref_109","unstructured":"DIN SPEC 33453\u2014 (2019). Entwicklung digitaler Dienstleistungssysteme; Norm, Deutsches Institut f\u00fcr. Normung e.V. (DIN)."},{"key":"ref_110","doi-asserted-by":"crossref","unstructured":"Ullah, I., Yang, F., Khan, R., Liu, L., Yang, H., Gao, B., and Sun, K. (2017). Predictive maintenance of power substation equipment by infrared thermography using a machine-learning approach. Energies, 10.","DOI":"10.3390\/en10121987"},{"key":"ref_111","doi-asserted-by":"crossref","unstructured":"Biasse, J.-M., Ferraro, V., Brun, P., Yang, Y., and Wang, G. (2016, January 25\u201328). New features for MV switchgear are now available to move to condition based maintenance. Proceedings of the 2016 International Conference on Condition Monitoring and Diagnosis (CMD), Xi\u2019an, China.","DOI":"10.1109\/CMD.2016.7757779"},{"key":"ref_112","unstructured":"Hussain, G.A., Hummes, D., Shafiq, M., and Safdar, M.S. (2019, January 7\u20138). Proceedings of the 2019 IEEE Texas Power and Energy Conference (TPEC), College Station, TX, USA."},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"7262","DOI":"10.1109\/JSEN.2015.2474122","article-title":"Online Condition Monitoring of MV Switchgear Using $ D $-Dot Sensor to Predict Arc-Faults","volume":"15","author":"Hussain","year":"2015","journal-title":"IEEE Sens. J."},{"key":"ref_114","doi-asserted-by":"crossref","unstructured":"Zhang, C., Dong, M., Ren, M., Huang, W., Zhou, J., Gao, X., and Albarrac\u00edn, R. (2018). Partial discharge monitoring on metal-enclosed switchgear with distributed non-contact sensors. Sensors, 18.","DOI":"10.3390\/s18020551"},{"key":"ref_115","doi-asserted-by":"crossref","unstructured":"Hou, Z., Wu, J., Ren, S., Yang, C., Mao, C., and Li, H. (2018, January 21\u201322). Development of a Novel Comprehensive Online Monitor for MV Switchgears Based on Modbus. Proceedings of the 2018 8th International Conference on Power and Energy Systems (ICPES), Colombo, Sri Lanka.","DOI":"10.1109\/ICPESYS.2018.8626894"},{"key":"ref_116","doi-asserted-by":"crossref","unstructured":"Romano, P., Parastar, A., Imburgia, A., Blennow, J., Bongiorno, M., di Tommaso, A.O., Hammarstr\u00f6m, T., and Serdyuk, Y. (2018, January 21\u201324). Partial Discharge Measurements under DC Voltages Containing Harmonics Produced by Power Electronic Devices. Proceedings of the 2018 IEEE Conference on Electrical Insulation and Dielectric Phenomena (CEIDP), Cancun, Mexico.","DOI":"10.1109\/CEIDP.2018.8544850"},{"key":"ref_117","doi-asserted-by":"crossref","unstructured":"Ahrend, U., Aleksy, M., Berning, M., Gebhardt, J., Mendoza, F., and Schulz, D. (2019, January 4\u20136). Challenges of the digital transformation: The role of sensors, sensor networks, IoT-devices, and 5G. Proceedings of the 2019 First International Conference on Societal Automation (SA), Krakow, Poland.","DOI":"10.1109\/SA47457.2019.8938077"},{"key":"ref_118","unstructured":"Laitinen, T., Lyly, T., Stenstrand, M., Tammi, J., Albrecht, R., Nyberg, J., and Saksela, K. (2018, January 26\u201331). Wireless sensor units for acoustic monitoring of switching devices. Proceedings of the CIGRE Session; Paris, France."},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"1495","DOI":"10.1007\/s10994-018-5735-z","article-title":"ML-Plan: Automated machine learning via hierarchical planning","volume":"107","author":"Mohr","year":"2018","journal-title":"Mach. Learn."},{"key":"ref_120","unstructured":"Hoffmann, M.W., Drath, R., and Ganz, C. (2020, January 12\u201313). Proposal for requirements on industrial AI solutions. Proceedings of the ML4CPS 2020, Berlin, Germany."},{"key":"ref_121","unstructured":"(2019). High-Level Expert Group on Artificial Intelligence (HLEG AI), Ethics guidelines for trustworthy AI, European Commission."},{"key":"ref_122","unstructured":"(2020). ZVEI Guidelines of the electrical industry for the responsible use of data and platforms, ZVEI."},{"key":"ref_123","doi-asserted-by":"crossref","unstructured":"Krueger, M., Chew, E.K., Ouertani, Z., and Gitzel, R. (2015, January 13\u201316). Integrative Service Innovation: An Industrial Use Case. Proceedings of the IEEE 17th International Conference on Business Informatics, Lisbon, Portugal.","DOI":"10.1109\/CBI.2015.31"},{"key":"ref_124","unstructured":"Wirth, R., and Hipp, J. CRISP-DM: Towards a standard process model for data mining. Proceedings of the Proceedings of the 4th international conference on the practical applications of knowledge discovery and data mining."},{"key":"ref_125","unstructured":"Kloepper, B., Hoffmann, M.W., and Ottewill, J.R. (2020). Stepping up value in AI industrial projects with co-innovation. ABB Review, 36\u201341."},{"key":"ref_126","unstructured":"(2019). Critical Infrastructure Protection- Actions Needed to Address Significant Cybersecurity Risks Facing the Electric Grid, United States Government Accountability Office (USGAO)."},{"key":"ref_127","doi-asserted-by":"crossref","unstructured":"Marrella, A., Monreale, A., Kloepper, B., and Krueger, M.W. (2016, January 12\u201315). Privacy-Preserving Outsourcing of Pattern Mining of Event-Log Data-A Use-Case from Process Industry. Proceedings of the 2016 IEEE International Conference on Cloud Computing Technology and Science (CloudCom), Luxembourg City, Luxembourg.","DOI":"10.1109\/CloudCom.2016.0095"},{"key":"ref_128","doi-asserted-by":"crossref","unstructured":"Stoustrup, J., Annaswamy, A., Chakrabortty, A., and Qu, Z. (2019). Smart Grid Control: Overview and Research Opportunities, Springer.","DOI":"10.1007\/978-3-319-98310-3"},{"key":"ref_129","doi-asserted-by":"crossref","first-page":"1554","DOI":"10.1109\/TSMC.2018.2884952","article-title":"A Survey on Security Communication and Control for Smart Grids Under Malicious Cyber Attacks","volume":"49","author":"Peng","year":"2019","journal-title":"IEEE Trans. Syst. Man, Cybern. Syst."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/7\/2099\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:16:35Z","timestamp":1760174195000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/7\/2099"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,8]]},"references-count":129,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2020,4]]}},"alternative-id":["s20072099"],"URL":"https:\/\/doi.org\/10.3390\/s20072099","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4,8]]}}}