Dong Wang
21 Papers
1 Citations
Dong Wang is an academic researcher. The author has contributed to research in topics: Computer science & Interpretability. The author has an hindex of 3, co-authored 15 publications.
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Papers
Investigation on optimal discriminant directions of linear discriminant analysis for locating informative frequency bands for machine health monitoring
TL;DR: Linear discriminant analysis (LDA) is a supervised machine learning algorithm for dimensionality reduction and pattern recognition, which aims to simultaneously maximize a separation between different classes and minimize a variance within classes as discussed by the authors .
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Investigations on the sensitivity of sparsity measures to the sparsity of impulsive signals
TL;DR: In this paper , the sensitivity of sparsity measures to the sparsity of impulsive signals is investigated in the domain of machine condition monitoring, and it is shown that the Gini index has the most stable sensitivity to sparsity.
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Novel sparse representation degradation modeling for locating informative frequency bands for Machine performance degradation assessment
TL;DR: Based on the sparsity property of fault signals in the frequency domain, a novel sparse representation degradation modeling methodology that integrates sparse representation and monotonic degradation modeling is proposed in this paper to enrich performance degradation assessment.
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Interpretable temporal degradation state chain based fusion graph for intelligent bearing fault detection
TL;DR: This study proposes an interpretable temporal degradation state chain based fusion graph model for intelligent bearing fault detection, achieving over 97.8% anomaly detection accuracy on XJTU-SY and 92.8% on NASA bearing datasets, with enhanced model interpretability and transparency.
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Guest Editorial Special Section for Third International Conference on Sensing, Measurement, and Data Analytics in the Era of Artificial Intelligence (ICSMD 2022)
TL;DR: The Third International Conference on Sensing, Measurement, and Data Analytics (ICSMD 2022) brought together 500 attendees for 100+ oral and 70+ poster presentations, featuring three keynote speeches and discussions on sensing technology, measurement methodology, and AI-driven data analytics.
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