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Jiakai Ding - IEEE Xplore Author Profile
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Jiakai Ding

Publications
3
Citations
86
Publications by Year
20202024
Co-Authors:
Show All Co-Authors (6)
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Jiakai Ding

Affiliation

College of Mechanical and Vehicle Engineering
State Key Laboratory of Mechanical Transmission for Advanced Equipment
Chongqing University, Chongqing, China

Publication Topics

Biography

Jiakai Ding received the M.S. degree from Hunan University of Science and Technology, Xiangtan, China, in 2021. He is currently pursuing the Ph.D. degree in mechanical engineering with Chongqing University, Chongqing, China.,His research interests mainly include mechanical signal processing, time–frequency analysis, and rotating machinery fault diagnosis under nonstationary conditions.(Based on document published on 13 May 2024).
Publications
3
Citations
86
Publications by Year
20202024
Co-Authors:
Show All Co-Authors (6)
Author's Published Works

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Adaptive Global Noise Suppression Deep Deconvolution for Weak Fault Signature Mining of Aero-Engine Accessory Casing

Jiakai Ding;Yi Wang;Yi Qin;Baoping Tang

IEEE Transactions on Instrumentation and Measurement
Year: 2024 | Volume: 73 | Journal Article |
Cited by: Papers (1)
The vibration signals collected from aero-engine accessory casing suffer from serious background noise and strong harmonic interference caused by a combination of nonstationary operating conditions, complex transmission paths, and time-varying airflow environments, which ultimately lead to weak early fault signature information. In recent years, blind deconvolution is considered as a very powerful...Show More

Adaptive Global Noise Suppression Deep Deconvolution for Weak Fault Signature Mining of Aero-Engine Accessory Casing

Jiakai Ding;Yi Wang;Yi Qin;Baoping Tang

Year: 2024 | Volume: 73 | Journal Article |

Feature Extraction Of Acoustic Emission Signal Of Spatter Phenomenon In The SLM Process Based On Improved GA-VMD Algorithm

Hengwei Zhao;Jiakai Ding;Dongming Xiao

2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
Acoustic emission(AE) signals are generated during the SLM process, which contains much information about the spatter phenomenon. In this paper, an experimental platform from of SLM process is built. It is used acquisition the AE signals of the spatter phenomenon in the SLM process to realize the feature extraction of the spatter phenomenon. A method combining the improved Genetic Algorithm(GA) wi...Show More

Feature Extraction Of Acoustic Emission Signal Of Spatter Phenomenon In The SLM Process Based On Improved GA-VMD Algorithm

Hengwei Zhao;Jiakai Ding;Dongming Xiao

Year: 2022 | Conference Paper |

Gear Fault Diagnosis Based on Genetic Mutation Particle Swarm Optimization VMD and Probabilistic Neural Network Algorithm

Jiakai Ding;Dongming Xiao;Xuejun Li

IEEE Access
Year: 2020 | Volume: 8 | Journal Article |
Cited by: Papers (84)
The decomposition number K and penalty factor \alpha in the variational mode decomposition (VMD) algorithm have a great influence on the decomposition effect and the accuracy of subsequent fault diagnosis. Therefore, a gear fault diagnosis method based on genetic mutation particle swarm optimization VMD and probabilistic neural network (GMPSO-VMD-PNN) algorithm is proposed in this paper. Firs...Show More

Gear Fault Diagnosis Based on Genetic Mutation Particle Swarm Optimization VMD and Probabilistic Neural Network Algorithm

Jiakai Ding;Dongming Xiao;Xuejun Li

Year: 2020 | Volume: 8 | Journal Article |

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