Aug 26, 2020 · The experimental results with wheelset bearing data set show that the multitask learning can make full use of the feature information captured ...

Sep 2, 2020 · Therefore, this paper explores possibility of using speed identification and load identification tasks as two auxiliary tasks to improve ...

Nov 23, 2020 · The experimental results with wheelset bearing data set show that the multitask learning can make full use of the feature information captured ...

Multitask Learning Based on Lightweight 1DCNN for Fault Diagnosis of Wheelset Bearings-journal-article.

Mar 5, 2024 · Based on the excellent design of 1DCNN, SLS, and MTLS, the proposed DSMT-1DCNN could accurately detect faults in various loading and noisy ...

Duration: 0:34
Posted: Aug 24, 2021

Understanding and Learning Discriminant Features based on Multiattention 1DCNN for Wheelset Bearing Fault Diagnosis · Huan Wang, Zhiliang Liu, +1 author. Yong ...

May 11, 2024 · Based on two public bearing fault datasets, we conducted a series of experiments. The experimental results show that the learning tasks mutually ...

Sep 24, 2023 · This study researched the application of a convolutional neural network (CNN) to a bearing compound fault diagnosis.

Deep transfer learning algorithm is regarded as a promising method to address the issue of rolling bearing fault diagnosis with limited labeled data.