Rolling bearing fault diagnosis method based on data-driven random fuzzy evidence acquisition and Dempster–Shafer evidence theory

Research article (Advances in Mechanical Engineering, 2016) · cited 19× · AI/ML
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Rolling bearing fault diagnosis method based on data-driven random fuzzy evidence acquisition and Dempster–Shafer evidence theory

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Rolling bearing fault diagnosis method based on data-driven random fuzzy evidence acquisition and Dempster–Shafer evidence theory is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Rolling bearing fault diagnosis method based on data-driven random fuzzy evidence acquisition and Dempster–Shafer evidence theory. Retrieved May 24, 2026, from https://4ort.xyz/entity/rolling-bearing-fault-diagnosis-method-based-on-data-driven-random-fuzzy-evidence-acquisition-and-dempstershafer-evidenc
MLA “Rolling bearing fault diagnosis method based on data-driven random fuzzy evidence acquisition and Dempster–Shafer evidence theory.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/rolling-bearing-fault-diagnosis-method-based-on-data-driven-random-fuzzy-evidence-acquisition-and-dempstershafer-evidenc.
BibTeX @misc{4ortxyz_rolling-bearing-fault-diagnosis-method-based-on-data-driven-random-fuzzy-evidence-acquisition-and-dempstershafer-evidenc_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Rolling bearing fault diagnosis method based on data-driven random fuzzy evidence acquisition and Dempster–Shafer evidence theory}}, year = {2026}, url = {https://4ort.xyz/entity/rolling-bearing-fault-diagnosis-method-based-on-data-driven-random-fuzzy-evidence-acquisition-and-dempstershafer-evidenc}, note = {Accessed: 2026-05-24}}
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