Work

Classification of Distributed Bearing Faults Using a Novel Sensory Board and Deep Learning Networks With Hybrid Inputs

Year: 2023

Type: article

Source: IEEE Transactions on Energy Conversion

DOI: 10.1109/tec.2023.3338447

Authors: Ramin Rajabioun, Mojtaba Afshar, Özkan Atan, Mutlu Mete, Bilal Akin

Institutions: Van Yüzüncü Yıl Üniversitesi, The University of Texas at Dallas, East Texas A&M University, Texas A&M University

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: W4389252605

FWCI: 1.611

Cites: 28

Cited by: 15

Related to: 10