[{"author":[{"first_name":"Amelie","full_name":"Bender, Amelie","id":"54290","last_name":"Bender"},{"full_name":"Aimiyekagbon, Osarenren Kennedy","id":"9557","last_name":"Aimiyekagbon","first_name":"Osarenren Kennedy"},{"last_name":"Sextro","full_name":"Sextro, Walter","id":"21220","first_name":"Walter"}],"date_created":"2024-07-22T09:27:57Z","publisher":"IEEE Computer Society","date_updated":"2024-07-22T09:29:26Z","doi":"10.1109/PHM61473.2024.00038","conference":{"location":"Stockholm, Schweden","end_date":"2024-05-31","start_date":"2024-05-28","name":"2024 Prognostics and System Health Management Conference (PHM)"},"title":"Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment","publication_identifier":{"isbn":["979-8-3503-6058-5"]},"quality_controlled":"1","citation":{"bibtex":"@inproceedings{Bender_Aimiyekagbon_Sextro_2024, title={Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment}, DOI={<a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">10.1109/PHM61473.2024.00038</a>}, booktitle={Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)}, publisher={IEEE Computer Society}, author={Bender, Amelie and Aimiyekagbon, Osarenren Kennedy and Sextro, Walter}, year={2024} }","short":"A. Bender, O.K. Aimiyekagbon, W. Sextro, in: Proceedings of the 2024 Prognostics and System Health Management Conference (PHM), IEEE Computer Society, 2024.","mla":"Bender, Amelie, et al. “Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment.” <i>Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)</i>, IEEE Computer Society, 2024, doi:<a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">10.1109/PHM61473.2024.00038</a>.","apa":"Bender, A., Aimiyekagbon, O. K., &#38; Sextro, W. (2024). Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment. <i>Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)</i>. 2024 Prognostics and System Health Management Conference (PHM), Stockholm, Schweden. <a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">https://doi.org/10.1109/PHM61473.2024.00038</a>","chicago":"Bender, Amelie, Osarenren Kennedy Aimiyekagbon, and Walter Sextro. “Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment.” In <i>Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)</i>. IEEE Computer Society, 2024. <a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">https://doi.org/10.1109/PHM61473.2024.00038</a>.","ieee":"A. Bender, O. K. Aimiyekagbon, and W. Sextro, “Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment,” presented at the 2024 Prognostics and System Health Management Conference (PHM), Stockholm, Schweden, 2024, doi: <a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">10.1109/PHM61473.2024.00038</a>.","ama":"Bender A, Aimiyekagbon OK, Sextro W. Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment. In: <i>Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)</i>. IEEE Computer Society; 2024. doi:<a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">10.1109/PHM61473.2024.00038</a>"},"year":"2024","department":[{"_id":"151"}],"user_id":"54290","_id":"55336","language":[{"iso":"eng"}],"keyword":["retrofit","diagnosis","prognostics","RUL prediction","missing data","ball bearings"],"publication":"Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)","type":"conference","status":"public","abstract":[{"text":"Predicting the remaining useful life of technical \r\nsystems has gained significant attention in recent years due to \r\nincreasing demands for extending the lifespan of degrading system \r\ncomponents. Therefore, already used systems are retrofitted by \r\nintegrating sensors to monitor their performance and \r\nfunctionality, enabling accurate diagnosis of their condition and \r\nprediction of their remaining useful life. One of the main \r\nchallenges in this field is identified in the missing data from the \r\ntime where the retrofitted system has already run but without \r\nbeing monitored by sensors. In this paper, a novel approach for \r\nthe combined diagnostics and prognostics of retrofitted systems is \r\nproposed. The methodology aims to provide an accurate diagnosis \r\nof the system’s health state and estimation of the remaining useful \r\nlife by a combination of a machine learning and expert knowledge. \r\nTo evaluate the effectiveness of the proposed methodology, a case \r\nstudy involving a retrofitted system in an industrial setting is \r\nselected and applied. It is demonstrated that the approach \r\neffectively diagnose the current system’s health state and \r\naccurately predict its remaining useful life, thereby enabling \r\npredictive maintenance and decision-making. Overall, our \r\nresearch contributes to advancing the field of condition \r\nmonitoring for retrofitted systems by providing a comprehensive \r\nmethodology that addresses the challenge of missing data.","lang":"eng"}]},{"department":[{"_id":"151"}],"user_id":"54290","_id":"13460","type":"conference","status":"public","editor":[{"last_name":"Beer","full_name":"Beer, Michael","first_name":"Michael"},{"last_name":"Zio","full_name":"Zio, Enrico","first_name":"Enrico"}],"author":[{"first_name":"Amelie","id":"54290","full_name":"Bender, Amelie","last_name":"Bender"},{"first_name":"Lennart","last_name":"Schinke","full_name":"Schinke, Lennart"},{"first_name":"Walter","full_name":"Sextro, Walter","id":"21220","last_name":"Sextro"}],"date_updated":"2023-09-22T07:31:53Z","oa":"1","conference":{"end_date":"2019.09.26","location":"Hannover","name":"29th European Safety and Reliability Conference ","start_date":"2019.09.22"},"main_file_link":[{"open_access":"1","url":"http://rpsonline.com.sg/proceedings/9789811127243/html/0445.xml"}],"publication_identifier":{"isbn":["978-981-11-2724-3"]},"publication_status":"published","page":"1262-1269","citation":{"ama":"Bender A, Schinke L, Sextro W. Remaining useful lifetime prediction based on adaptive failure thresholds. In: Beer M, Zio E, eds. <i>Proceedings of the 29th European Safety and Reliability Conference (ESREL2019)</i>. ; 2019:1262-1269.","ieee":"A. Bender, L. Schinke, and W. Sextro, “Remaining useful lifetime prediction based on adaptive failure thresholds,” in <i>Proceedings of the 29th European Safety and Reliability Conference (ESREL2019)</i>, Hannover, 2019, no. 29, pp. 1262–1269.","chicago":"Bender, Amelie, Lennart Schinke, and Walter Sextro. “Remaining Useful Lifetime Prediction Based on Adaptive Failure Thresholds.” In <i>Proceedings of the 29th European Safety and Reliability Conference (ESREL2019)</i>, edited by Michael Beer and Enrico Zio, 1262–69, 2019.","apa":"Bender, A., Schinke, L., &#38; Sextro, W. (2019). Remaining useful lifetime prediction based on adaptive failure thresholds. In M. Beer &#38; E. Zio (Eds.), <i>Proceedings of the 29th European Safety and Reliability Conference (ESREL2019)</i> (Issue 29, pp. 1262–1269).","mla":"Bender, Amelie, et al. “Remaining Useful Lifetime Prediction Based on Adaptive Failure Thresholds.” <i>Proceedings of the 29th European Safety and Reliability Conference (ESREL2019)</i>, edited by Michael Beer and Enrico Zio, no. 29, 2019, pp. 1262–69.","short":"A. Bender, L. Schinke, W. Sextro, in: M. Beer, E. Zio (Eds.), Proceedings of the 29th European Safety and Reliability Conference (ESREL2019), 2019, pp. 1262–1269.","bibtex":"@inproceedings{Bender_Schinke_Sextro_2019, title={Remaining useful lifetime prediction based on adaptive failure thresholds}, number={29}, booktitle={Proceedings of the 29th European Safety and Reliability Conference (ESREL2019)}, author={Bender, Amelie and Schinke, Lennart and Sextro, Walter}, editor={Beer, Michael and Zio, Enrico}, year={2019}, pages={1262–1269} }"},"language":[{"iso":"eng"}],"keyword":["RUL prediction","adaptive threshold","prognostics","condition monitoring"],"publication":"Proceedings of the 29th European Safety and Reliability Conference (ESREL2019)","abstract":[{"lang":"eng","text":"Remaining useful lifetime (RUL) predictions as part of a condition monitoring system are focused in more and more research and industrial applications. To establish an efficient and precise estimate of the RUL of a technical product, different  uncertainties  have  to  be  handled.  To  minimize  the  uncertainties  of  the  RUL  estimation,  a  reliable and accurate prognostic approach as well as a good failure threshold are important. Regarding the failure threshold, most often  an  expert  sets  a  fixed  failure  threshold.  However,  neither  the  a  priori  known  failure  threshold  nor  a  fixedthreshold value are feasible in every application. Especially in the case of varying characteristics of the monitored system, an adaptive failure threshold is of great importance concerning the accuracy of the RUL estimation.  Rubber-metal-elements, which are used in a wide range of applications for vibration and sound isolation, are mon-itored by thermocouples to allow for lifetime predictions. Therefore, the element’s state is described by its temper-ature during its service life. Aiming to establish accurate RUL predictions of a rubber-metal-element, uncertainties due to nonlinear material characteristics and changing operational conditions have to be considered. Consequently, different temperature-based failure threshold definitions are implemented and compared within a particle filtering approach. "}],"date_created":"2019-09-30T08:49:19Z","title":"Remaining useful lifetime prediction based on adaptive failure thresholds","issue":"29","quality_controlled":"1","year":"2019"}]