Jing Lin

According to our database, Jing Lin authored at least 23 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Human-Centric and Integrative Lighting Asset Management in Public Libraries: Qualitative Insights and Challenges From a Swedish Field Study.

Jing Lin, Per Olof Hedekvist, Nina Mylly, Math Bollen, Jingchun Shen, Jiawei Xiong, Christofer Silfvenius

IEEE Access, 2024

2023

A nearly end-to-end deep learning approach to fault diagnosis of wind turbine gearboxes under nonstationary conditions.

Liangwei Zhang, Qi Fan, Jing Lin, Zhicong Zhang, Xiaohui Yan, Chuan Li

Eng. Appl. Artif. Intell., March, 2023

Intelligent fault diagnosis of bevel gearboxes using semi-supervised probability support matrix machine and infrared imaging.

Xin Li, Yong Li, Ke Yan, Haidong Shao, Janet (Jing) Lin

Reliab. Eng. Syst. Saf., 2023

2021

End-to-end unsupervised fault detection using a flow-based model.

Liangwei Zhang, Jing Lin, Haidong Shao, Zhicong Zhang, Xiaohui Yan, Jianyu Long

Reliab. Eng. Syst. Saf., 2021

Robustness of maintenance support service networks: attributes, evaluation and improvement.

Dongming Fan, Jing Lin, Baoping Cai, Bin Liu

Reliab. Eng. Syst. Saf., 2021

A novel approach of multisensory fusion to collaborative fault diagnosis in maintenance.

Haidong Shao, Jing Lin, Liangwei Zhang, Diego Galar, Uday Kumar

Inf. Fusion, 2021

2020

Deep transfer multi-wavelet auto-encoder for intelligent fault diagnosis of gearbox with few target training samples.

Zhiyi He, Haidong Shao, Ping Wang, Janet (Jing) Lin, Junsheng Cheng, Yu Yang

Knowl. Based Syst., 2020

2019

Application of Bayesian Networks in Reliability Evaluation.

Baoping Cai, Xiangdi Kong, Yonghong Liu, Jing Lin, Xiaobing Yuan, Hongqi Xu, Renjie Ji

IEEE Trans. Ind. Informatics, 2019

System availability assessment using a parametric Bayesian approach: a case study of balling drums.

Esi Saari, Jing Lin, Liangwei Zhang, Bin Liu

Int. J. Syst. Assur. Eng. Manag., 2019

A Review on Deep Learning Applications in Prognostics and Health Management.

Liangwei Zhang, Jing Lin, Bin Liu, Zhicong Zhang, Xiaohui Yan, Muheng Wei

IEEE Access, 2019

Deep Learning for Track Quality Evaluation of High-Speed Railway Based on Vehicle-Body Vibration Prediction.

Shuai Ma, Liang Gao, Xiubo Liu, Jing Lin

IEEE Access, 2019

A Dynamic Prescriptive Maintenance Model Considering System Aging and Degradation.

Bin Liu, Jing Lin, Liangwei Zhang, Uday Kumar

IEEE Access, 2019

An Active Learning Method Based on Uncertainty and Complexity for Gearbox Fault Diagnosis.

Jiayu Chen, Dong Zhou, Ziyue Guo, Jing Lin, Chuan Lyu, Chen Lu

IEEE Access, 2019

Bearing Fault Diagnosis Based on Subband Time-Frequency Texture Tensor.

Lin Bo, Guanji Xu, Xiaofeng Liu, Jing Lin

IEEE Access, 2019

Prognostics of polygonalization of high-speed railway train wheels using a generalized additive model smoothed by spline-backfitted kernel.

Zhexiang Chi, Lijian Yang, Jing Lin, Simin Huang

Proceedings of the 2019 IEEE International Conference on Prognostics and Health Management, 2019

2018

Adaptive kernel density-based anomaly detection for nonlinear systems.

Liangwei Zhang, Jing Lin, Ramin Karim

Knowl. Based Syst., 2018

A Dynamic Maintenance Strategy for Prognostics and Health Management of Degrading Systems: Application in Locomotive Wheel-sets.

Bin Liu, Jing Lin, Liangwei Zhang, Min Xie

Proceedings of the 2018 IEEE International Conference on Prognostics and Health Management, 2018

2017

Sliding Window-Based Fault Detection From High-Dimensional Data Streams.

Liangwei Zhang, Jing Lin, Ramin Karim

IEEE Trans. Syst. Man Cybern. Syst., 2017

Reliability evaluation of non-repairable phased-mission common bus systems with common cause failures.

Huan Yu, Jun Yang, Jing Lin, Yu Zhao

Comput. Ind. Eng., 2017

2015

An angle-based subspace anomaly detection approach to high-dimensional data: With an application to industrial fault detection.

Liangwei Zhang, Jing Lin, Ramin Karim

Reliab. Eng. Syst. Saf., 2015

Reliability analysis for preventive maintenance based on classical and Bayesian semi-parametric degradation approaches using locomotive wheel-sets as a case study.

Jing Lin, Julio Pulido, Matthias Asplund

Reliab. Eng. Syst. Saf., 2015

2014

Reliability Analysis for Degradation of Locomotive Wheels using Parametric Bayesian Approach.

Jing Lin, Matthias Asplund, Aditya Parida

Qual. Reliab. Eng. Int., 2014

2008

A Two-Stage Failure Model for Bayesian Change Point Analysis.

Jing Lin

IEEE Trans. Reliab., 2008