Work

Harnessing Bayesian Deep Learning to Tackle Unseen and Uncertain Scenarios in Diagnosis of Machinery Systems

Year: 2024

Type: article

Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical Engineering

DOI: 10.1115/1.4067001

Authors: Zhou Kai, Qianyu Zhou, Jiong Tang

Institutions: Hong Kong Polytechnic University, University of Connecticut

Language: English

Topic: Machine Fault Diagnosis Techniques

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: closed

OpenAlex ID: W4403731699

FWCI: 0.158

Cites: 53

Cited by: 1

Related to: 10