@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}},
}

@inproceedings{22507,
  abstract     = {{Several methods, including order analysis, wavelet analysis and empirical mode decomposition have been proposed and successfully employed for the health state estimation of technical systems operating under varying conditions. However, where information such as the speed of rotating machinery, component specifications or other domain-specific information is unavailable, such methods are often infeasible. Thus, this paper investigates the application of classical time-domain features, features from the medical field and novel features from the highly comparative time-series analysis (HCTSA) package, for the health state estimation of rotating machinery operating under varying conditions. Furthermore, several feature selection methods are investigated to identify features as viable health indicators for the diagnostics and prognostics of technical systems. As a case study, the presented methods are evaluated on real-world and experimentally acquired vibration data of bearings operating under varying speed. The results show that the selected features can successfully be employed as health indicators for technical systems operating under varying conditions.}},
  author       = {{Aimiyekagbon, Osarenren Kennedy and Bender, Amelie and Sextro, Walter}},
  booktitle    = {{Proceedings of the Seventeenth International Conference on Condition Monitoring and Asset Management (CM 2021)}},
  keywords     = {{Wind turbine diagnostics, bearing diagnostics, non-stationary operating conditions, varying operating conditions, feature extraction, feature selection, fault detection, failure detection}},
  title        = {{{On the applicability of time series features as health indicators for technical systems operating under varying conditions}}},
  year         = {{2021}},
}

@inproceedings{37002,
  abstract     = {{HDL-mutation based fault injection and analysis is considered as an important coverage metric for measuring the quality of design simulation processes [20, 3, 1, 2]. In this work, we try to solve the problem of automatic simulation data generation targeting HDL mutation faults. We follow a search based approach and eliminate the need for symbolic execution and mathematical constraint solving from existing work. An objective cost function is defined on the test input space and serves the guidance of search for fault-detecting test data. This is done by first mapping the simulation traces under a test onto a control and data flow graph structure which is extracted from the design. Then the progress of fault detection can be measured quantitatively on this graph to be the cost value. By minimizing this cost we approach the target test data. The effectiveness of the cost function is investigated under an example neighborhood search scheme. Case study with a floating point arithmetic IP design has shown that the cost function is able to guide effectively the search procedure towards a fault-detecting test. The cost calculation time as the search overhead was also observed to be minor compared to the actual design simulation time.}},
  author       = {{Xie, Tao and Müller, Wolfgang and Letombe, Florian}},
  booktitle    = {{Proceedings of Euromicro DSD 2011}},
  isbn         = {{978-1-4577-1048-3}},
  keywords     = {{Hardware design languages, Cost function, Computational modeling, Fault detection, Data models, Analytical models, Testing}},
  publisher    = {{IEEE}},
  title        = {{{HDL-Mutation Based Simulation Data Generation by Propagation Guided Search}}},
  doi          = {{10.1109/DSD.2011.83}},
  year         = {{2011}},
}