@article{51518, abstract = {{In applications of piezoelectric actuators and sensors, the dependability and particularly the reliability throughout their lifetime are vital to manufacturers and end-users and are enabled through condition-monitoring approaches. Existing approaches often utilize impedance measurements over a range of frequencies or velocity measurements and require additional equipment or sensors, such as a laser Doppler vibrometer. Furthermore, the non-negligible effects of varying operating conditions are often unconsidered. To minimize the need for additional sensors while maintaining the dependability of piezoelectric bending actuators irrespective of varying operating conditions, an online diagnostics approach is proposed. To this end, time- and frequency-domain features are extracted from monitored current signals to reflect hairline crack development in bending actuators. For validation of applicability, the presented analysis method was evaluated on piezoelectric bending actuators subjected to accelerated lifetime tests at varying voltage amplitudes and under external damping conditions. In the presence of a crack and due to a diminished stiffness, the resonance frequency decreases and the root-mean-square amplitude of the current signal simultaneously abruptly drops during the lifetime tests. Furthermore, the piezoelectric crack surfaces clapping is reflected in higher harmonics of the current signal. Thus, time-domain features and harmonics of the current signals are sufficient to diagnose hairline cracks in the actuators.}}, author = {{Aimiyekagbon, Osarenren Kennedy and Bender, Amelie and Hemsel, Tobias and Sextro, Walter}}, issn = {{2079-9292}}, journal = {{Electronics}}, keywords = {{piezoelectric transducer, self-sensing, fault detection, diagnostics, hairline crack, condition monitoring}}, number = {{3}}, publisher = {{MDPI AG}}, title = {{{Diagnostics of Piezoelectric Bending Actuators Subjected to Varying Operating Conditions}}}, doi = {{10.3390/electronics13030521}}, volume = {{13}}, year = {{2024}}, } @article{44672, abstract = {{With enhancing digitalization, condition monitoring is used in an increasing number of application fields across various industrial sectors. By its application, increased reliability as well as reduced risks and costs can be achieved. Based on different approaches, technical systems are monitored and measured data is analyzed to enable condition-based or predictive maintenance. To this end, machine learning approaches are usually implemented to diagnose the health states or predict the health index of the monitored system. However, these trained models are often black-box models, not intuitively explainable for a human. To overcome this shortcoming, a model-based approach based on physics is developed for piezoelectric bending actuators. Such a model enables a transparent representation of the system. Moreover, the model-based approach is extended by a parameter-estimation to account for sudden changes in behavior e. g. caused by occurring cracks.}}, author = {{Bender, Amelie}}, issn = {{0924-4247}}, journal = {{Sensors and Actuators A: Physical}}, keywords = {{Condition Monitoring, Model-based approach Diagnostics, Varying conditions, Explainability, Piezoelectric bending actuators}}, publisher = {{Elsevier BV}}, title = {{{Model-based condition monitoring of piezoelectric bending actuators}}}, doi = {{10.1016/j.sna.2023.114399}}, volume = {{357}}, year = {{2023}}, } @inproceedings{13460, abstract = {{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. }}, author = {{Bender, Amelie and Schinke, Lennart and Sextro, Walter}}, booktitle = {{Proceedings of the 29th European Safety and Reliability Conference (ESREL2019)}}, editor = {{Beer, Michael and Zio, Enrico}}, isbn = {{978-981-11-2724-3}}, keywords = {{RUL prediction, adaptive threshold, prognostics, condition monitoring}}, location = {{Hannover}}, number = {{29}}, pages = {{1262--1269}}, title = {{{Remaining useful lifetime prediction based on adaptive failure thresholds}}}, year = {{2019}}, } @inproceedings{9969, abstract = {{Zuverlässigkeit, Sicherheit und Verfügbarkeit gewinnen bei der Anwendung von technischen Systemen eine immer größere Bedeutung. Aus diesem Grund hat sich Condition Monitoring, die Zustandsüberwachung eines technischen Produkts, in verschiedenen Industriebranchen etabliert. Die sensorbasierte Überwachung eines Produkts während seiner Betriebsdauer in Kombination mit Condition Monitoring Methoden ermöglichen die Bestimmung des aktuellen Zustands des Produkts und somit eine Diagnose, ob das Produkt seine ihm zugeschriebene Funktion zum aktuellen Zeitpunkt erfüllt. Neben Diagnosen bietet Condition Monitoring auch die Möglichkeit Prognosen aufzustellen, dabei wird die restliche Nutzungsdauer des Produkts aufbauend auf geeigneten Sensordaten geschätzt. So kann eine intelligente Wartungsplanung umgesetzt werden, die im Gegensatz zu klassischen Ansätzen keine festen Wartungsintervalle benötigt und die Nachteile einer rein reaktiven Wartung kompensiert. Stattdessen ist es möglich ein Element bis vor das Ende seiner Lebensdauer zu nutzen und erst dann zu warten, um eine optimale Nutzung zu gewährleisten. Durch eine Bestimmung der verbleibenden Restlebensdauer während des Betriebs ist eine optimale Wartungsplanung möglich, wodurch die Verfügbarkeit und die Auslastung der überwachten Produkte signifikant gesteigert werden kann. In dieser Arbeit soll ein produktspezifisches Condition Monitoring System für Gummi-Metall-Elemente entwickelt werden. Diese Elemente werden zur Federung, Geräusch- und/oder Schwingungsisolation in vielen verschiedenen Anwendungen eingesetzt, wie bspw. in Nutz- und Schienenfahrzeugen oder Windenergieanlagen. In Industrie und Forschung werden bereits Zustandsüberwachungen von Systemen mit integrierten Gummi-Metall-Elementen eingesetzt, allerdings noch keine Condition Monitoring Systeme zur alleinigen Zustandsüberwachung dieser Elemente. Aktuell ist es üblich die Lebensdauer dieser Elemente aufbauend auf beschleunigten Lebensdauerversuchen und Erfahrungswerten abzuschätzen. Mit dem Ziel die Lebensdauer des fokussierten Produkts präziser vorherzusagen und damit eine intelligente Wartungsplanung zu ermöglichen, wird die Entwicklung eines Condition Monitoring Systems für Gummi-Metall-Elemente angestrebt und in dieser Arbeit erläutert.}}, author = {{Bender, Amelie and Kaul, Thorben and Sextro, Walter}}, booktitle = {{Verlagsschriftenreihe des Heinz Nixdorf Instituts Band 369, Paderborn, 2017}}, keywords = {{Zustandsüberwachung, Condition Monitoring, Prognose, Gummi-Metall-Elemente, Restlebensdauerschätzung}}, pages = {{347--358}}, title = {{{Entwicklung eines Condition Monitoring Systems für Gummi-Metall-Elemente}}}, year = {{2017}}, } @inproceedings{9791, abstract = {{The rapid development of communication and information technology opens up fascinating perspectives, which go far beyond the state of the art in mechatronics: mechatronic systems with inherent partial intelligence. These so called self-optimizing systems adapt their objectives and behavior autonomously and flexibly to changing operating conditions. On the one hand, securing the dependability of such systems is challenging due to their complexity and non-deterministic behavior. On the other hand, self-optimization can be used to increase the dependability of the system during its operation. However, it has to be ensured, that the self-optimization works dependable itself. To cope with these challenges, the multi-level dependability concept was developed. It enables predictive condition monitoring, influences the objectives of the system and determines suitable means to improve the system's dependability during its operation. In this contribution we introduce a procedure for the conceptual design of an advanced condition monitoring based on the system's principle solution. The principle solution describes the principal operation mode of the system and its desired behavior. It is modeled using the specification technique for the domain-spanning description of the principle solution of a self-optimizing system and consists of a coherent system of eight partial models (e.g. requirements, active structure, system of objectives, behavior, etc.). The partial models are analyzed separately in order to derive the components of the multi-level dependability concept. In particular, the reliability analysis of the partial model active structure is performed to identify the system elements to be monitored and parameters to be measured. The principle solution is extended accordingly: e.g. with system elements required for the realization of the dependability concept. The advantages of the method are shown on the self-optimizing guidance module of a railroad vehicle.}}, author = {{Sondermann-Wölke , Christoph and Meyer, Tobias and Dorociak, Rafal and Gausemeier, Jürgen and Sextro, Walter}}, booktitle = {{Proceedings of the 11th International Probabilistic Safety Assessment and Management Conference (PSAM11) and The Annual European Safety and Reliability Conference (ESREL2012)}}, keywords = {{Mechatronic Systems, Principle Solution, Condition Monitoring, Conceptual Design}}, title = {{{Conceptual Design of Advanced Condition Monitoring for a Self-Optimizing System based on its Principle Solution}}}, year = {{2012}}, } @article{9761, abstract = {{New mechatronic systems, called self-optimizing systems, are able to adapt their behavior according to environmental, user and system specific influences. Self-optimizing systems are complex and due to their non-deterministic behavior comprise hidden risks, which cannot be foreseen in the design phase of the system. Therefore, modifications of the ISO 17359 condition monitoring policy for being able to cope with this new kind of systems are presented. Besides avoiding critical situations evoked by self-optimization, the proposed concept uses self-optimization to increase the dependability of the system. This concept is applied to the active guidance module of an innovative rail-bound vehicle. First test drives provide information for the enhancement of the implementation of realtime switching to appropriate control strategies. The different control strategies are investigated in detail. It is illustrated that influences on the system like different track sections or the desired velocity of the RailCab effect the system and can lead to a higher amount of flange contacts, which indicate higher wear and thus a reduction of the availability of the system. Therefore, these influences should be minded within the condition monitoring policy. Consequently, this article presents the condition monitoring policy for self-optimizing function modules and its application to the active railway guidance module.}}, author = {{Sondermann-Wölke, Christoph and Sextro, Walter}}, journal = {{International Journal On Advances in Intelligent Systems}}, keywords = {{dependability, condition monitoring, selfoptimization, active railway guidance module}}, number = {{1 - 3}}, pages = {{65 -- 74}}, title = {{{Integration of Condition Monitoring in Self-optimizing Function Modules Applied to the Active Railway Guidance Module}}}, volume = {{3}}, year = {{2010}}, } @inproceedings{9742, abstract = {{New mechatronic systems, called self-optimizing systems, are able to adapt their behavior according to environmental, user and system specific influences. Self-optimizing systems are complex and due to their non-deterministic behavior comprise hidden risks, which cannot be foreseen in the design phase of the system. Therefore, this paper presents modifications of the current condition monitoring policy, to be able to cope with this new kind of systems. Beside avoiding critical situations evoked by self-optimization, the proposed concept uses self-optimization to increase the dependability of the system. In this case, the concept is applied to the active guidance module of an innovative rail-bound vehicle.}}, author = {{Sondermann-Wölke, Christoph and Sextro, Walter}}, booktitle = {{Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns, 2009. COMPUTATIONWORLD '09. Computation World:}}, keywords = {{condition monitoring, mechatronic systems, rail bound vehicle, rail guidance module, self-optimization, self-optimizing function modules, condition monitoring, mechatronics, railway rolling stock, self-adjusting systems}}, pages = {{15 --20}}, title = {{{Towards the Integration of Condition Monitoring in Self-Optimizing Function Modules}}}, doi = {{10.1109/ComputationWorld.2009.47}}, year = {{2009}}, }