Twin Broad Learning System for Fault Diagnosis of Rotating Machinery - researchr publication related

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Le Yang 0007, Zelin Yang, Shiji Song, Fan Li 0003, C. L. Philip Chen. Twin Broad Learning System for Fault Diagnosis of Rotating Machinery. IEEE T. Instrumentation and Measurement, 72:1-12, 2023. [doi]

The following publications are possibly variants of this publication:

Fault Diagnosis of Rotating Machinery: A Highly Efficient and Lightweight Framework Based on a Temporal Convolutional Network and Broad Learning SystemHao Wei, Qinghua Zhang, Yu Gu 0003. sensors, 23(12):5642, 2023. [doi]

Broad zero-shot diagnosis for rotating machinery with untrained compound faultsChenyang Ma, Xianzhi Wang 0002, Yongbo Li, Zhiqiang Cai 0003. ress, 242:109704, February 2024. [doi]

Composite Fault Diagnosis of Rotating Machinery With Collaborative LearningM. P. Pavan Kumar, Cheng-Jyun Tang, Kun-Chih Jimmy Chen. vlsi-dat 2022: 1-4 [doi]

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