A physically inspired and bounded metric learning framework for fault detection and multi-class classification in mechanical systems

Research article (Expert Systems with Applications, 2025) · cited 12× · AI/ML
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A physically inspired and bounded metric learning framework for fault detection and multi-class classification in mechanical systems

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A physically inspired and bounded metric learning framework for fault detection and multi-class classification in mechanical systems is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). A physically inspired and bounded metric learning framework for fault detection and multi-class classification in mechanical systems. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-physically-inspired-and-bounded-metric-learning-framework-for-fault-detection-and-multi-class-classification-in-mechan
MLA “A physically inspired and bounded metric learning framework for fault detection and multi-class classification in mechanical systems.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-physically-inspired-and-bounded-metric-learning-framework-for-fault-detection-and-multi-class-classification-in-mechan.
BibTeX @misc{4ortxyz_a-physically-inspired-and-bounded-metric-learning-framework-for-fault-detection-and-multi-class-classification-in-mechan_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A physically inspired and bounded metric learning framework for fault detection and multi-class classification in mechanical systems}}, year = {2026}, url = {https://4ort.xyz/entity/a-physically-inspired-and-bounded-metric-learning-framework-for-fault-detection-and-multi-class-classification-in-mechan}, note = {Accessed: 2026-05-24}}
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