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Jiacheng Sun

Publications
2
Citations
1
Publications by Year
20232025
Co-Authors:
Show All Co-Authors (10)
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Jiacheng Sun

Affiliation

Shanxi Key Laboratory of Fully Mechanized Coal Mining Equipment
College of Mechanical and Vehicle Engineering
Taiyuan University of Technology, Taiyuan, China

Publication Topics

Biography

Jiacheng Sun received the B.S. degree in mechanical design, manufacturing and automation from Shandong University of Science and Technology, in 2022. He is currently pursuing the M.S. degree in mechanical engineering with the Taiyuan University of Technology.,His research interests include deep learning and fault diagnosis.(Based on document published on 14 March 2025).
Publications
2
Citations
1
Publications by Year
20232025
Co-Authors:
Show All Co-Authors (10)
Author's Published Works

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Intelligent Fault Diagnosis Method for Shearer Rocker Gear Based on Swin Transformer and Multiscale Convolution Parallel Integration

Xiaochun Sun;Hua Ding;Ning Li;Xiaoxin Dong;Jiacheng Sun;Guangyu Zheng

IEEE Transactions on Instrumentation and Measurement
Year: 2025 | Volume: 74 | Journal Article |
In the harsh underground environment, the transmission gear in the rocker arm of the shearer is susceptible to impact load, frequently leading to failures that result in economic losses or casualties. Therefore, real-time and accurate gear fault diagnosis is crucial. Existing diagnostic models struggle with insufficient feature extraction and low diagnostic accuracy when addressing nonlinear, nons...Show More

Intelligent Fault Diagnosis Method for Shearer Rocker Gear Based on Swin Transformer and Multiscale Convolution Parallel Integration

Xiaochun Sun;Hua Ding;Ning Li;Xiaoxin Dong;Jiacheng Sun;Guangyu Zheng

Year: 2025 | Volume: 74 | Journal Article |

Comparison Study on Parametric Fault Diagnosis Using BPNN, SVM and SDAE for DC-DC Converters in Aircraft

Ting Wang;Jiacheng Sun;Wenli Yao;Xiaobin Zhang;Weilin Li;Yufeng Wang

2023 25th European Conference on Power Electronics and Applications (EPE'23 ECCE Europe)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Effective fault diagnosis for mission-critical and safety-critical systems, such as aircraft electric power system, has been an essential and mandatory technique to reduce failure rate and prevent unscheduled shutdown. This paper aims to compare the performance of three efficient fault classifiers, BPNN, SVM and SDAE, in parametric fault diagnosis for the boost DC-DC converter in aircraft. The tra...Show More

Comparison Study on Parametric Fault Diagnosis Using BPNN, SVM and SDAE for DC-DC Converters in Aircraft

Ting Wang;Jiacheng Sun;Wenli Yao;Xiaobin Zhang;Weilin Li;Yufeng Wang

Year: 2023 | Conference Paper |

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