IMPROVE - Innovative Modelling Approaches for Production Systems to Raise Validatable Efficiency : Intelligent Methods for the Factory of the Future. - Niggemann, Oliver; Schüller, Peter (Berlin, Heidelberg : Springer Berlin / Heidelberg, 2018)
2.1 Anomaly detection with quantization error -- 2.2 Localization of anomalies -- 2.3 SOM trajectory tracking with timed automata -- 3 Experiments -- 3.1 Quantization error anomaly detection and anomaly localization -- 3.2 Trajectory tracking with automata -- 4 Conclusion -- Acknowledgments. -- References -- 5 A Sampling-Based Method for Robust and Efficient Fault Detection in Industrial Automation Processes -- 1 Introduction -- 2 Fault detection with stochastic process models -- 3 Fault detection for application cases with noisy measurements -- 3.1 Probability density models -- 3.2 Particle filter based fault detection -- 3.3 Parallel implementation -- 4 Evaluation and Discussion -- 4.1 Fault detection results -- 4.2 Runtime analysis -- 5 Conclusion -- Acknowledgments. -- Appendix A: Fault detection for observable process variables -- Appendix B: Metropolis Resampling -- References -- 6 Validation of similarity measures for industrial alarm flood analysis -- 1 Introduction -- 2 Clustering methodology -- 2.1 Alarm log acquisition -- 2.2 Flood detection and preprocessing -- 2.3 Alarm flood clustering -- 2.4 Distance matrix postprocessing -- 3 Evaluation methodology -- 3.1 Synthetic flood generation -- 3.2 Cluster Membership of Synthetic Floods -- 3.3 Cluster Stability -- 4 Empirical evaluation results -- 4.1 Visualization on a demonstrative set of 25 floods -- 4.2 Clustering with synthetic floods on the full dataset -- 5 Conclusion -- Acknowledgement -- References -- 7 Concept for Alarm Flood Reduction with Bayesian Networks by Identifying the Root Cause -- 1 Introduction -- 2 State of the Art of Alarm Management -- 3 Knowledge Representation -- 4 Concept for Alarm Flood Reduction -- 4.1 Learning Phase -- 4.2 Operation Phase -- 5 Conclusion -- Acknowledgment -- References.
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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2023. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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