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- W2904090237 abstract "Abstract The Probability‐of‐Detection (POD) measure quantifies the performance of a measurement device to nondestructive testing taking into account statistical variability. The time and cost involved have given rise to Model‐Assisted POD to improve the effectiveness of POD models with little or no specimen testing. Similar criteria regarding capabilities of FDI (Fault Detection and Isolation) or diagnostic approaches applied to vibration‐based analysis are currently not known. This results from complexity of the dynamical behaviors in relation to faults, sensor positions (observability), and feature extraction tasks. In this contribution the complexity of POD‐based analysis applied to fault detection of elastic mechanical structures is examined. Based on experimental results of mechanical modifications on an elastic beam, the POD of different FDI‐procedures are examined. Different sensor types are used for eigenfrequency analysis. Depending on the modes considered it can be shown why this classical approach often does not lead to satisfying results. To fuse the POD values, suitable assumptions in combination with a new method are applied to eigenfrequency‐based analysis as detection task." @default.
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- W2904090237 date "2018-12-01" @default.
- W2904090237 modified "2023-10-16" @default.
- W2904090237 title "Fault diagnosis using Probability of Detection (POD)‐based sensor/information fusion for vibration‐based analysis of elastic structures" @default.
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- W2904090237 doi "https://doi.org/10.1002/pamm.201800474" @default.
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