Gear Fault Diagnosis Method Based on Deep Transfer Learning

Autor: Liu Shihao, Wang Xiyang, Gong Tingkai

Publikováno v: Jixie chuandong, Vol 47, Pp 134-142 (2023)

Aiming at the problem of insufficient gear fault samples, a fault diagnosis method of transfer learning based on Hilbert-Huang spectrum and pre-trained VGG16 model is proposed. Firstly, the intrinsic mode function (IMF) is obtained by Empirical Mode

Externí odkaz: https://doaj.org/article/4b23e8951fd1481c989a57dc3ac84f01

Analog circuit diagnosis based on support vector machine with parameter optimization by improved NKCGWO.

Autor: Song, Ping, Chen, Lishun, Cai, Kailong, Xiong, Ying, Gong, Tingkai

Publikováno v: Analog Integrated Circuits & Signal Processing; Jun2024, Vol. 119 Issue 3, p497-510, 14p

Fault detection for rolling element bearing based on repeated single-scale morphology and simplified sensitive factor algorithm

Autor: Gong, Tingkai, Yuan, Xiaohui, Lei, Xiaohui, Yuan, Yanbin, Zhang, Binqiao

Publikováno v: In Measurement October 2018 127:348-355

Gear Fault Diagnosis Based on Deep Learning and Subdomain Adaptation. (English)

Autor: JIE Zhenguo, WANG Xiyang, GONG Tingkai

Publikováno v: China Mechanical Engineering; 11/25/2021, Vol. 32 Issue 22, p2716-2723, 8p

Fault diagnosis for rolling element bearing using variational mode decomposition and l1trend filtering

Autor: Gong, Tingkai, Yuan, Xiaohui, Wang, Xu, Yuan, Yanbin, Zhang, Binqiao

Publikováno v: Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability; November 2020, Vol. 234 Issue: 1 p116-128, 13p