Jing Lin

Orcid: 0000-0002-7458-6820

Affiliations:
  • Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Sweden


According to our database1, Jing Lin authored at least 25 papers between 2008 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
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PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2024
Wave-ConvNeXt: An Efficient and Precise Fault Diagnosis Method for IIoT Leveraging Tailored ConvNeXt and Wavelet Transform.
IEEE Internet Things J., July, 2024

A Novel Context driven Critical Integrative Levels (CIL) Approach: Advancing Human-Centric and Integrative Lighting Asset Management in Public Libraries with Practical Thresholds.
CoRR, 2024

Human-Centric and Integrative Lighting Asset Management in Public Libraries: Qualitative Insights and Challenges From a Swedish Field Study.
IEEE Access, 2024

2023
A nearly end-to-end deep learning approach to fault diagnosis of wind turbine gearboxes under nonstationary conditions.
Eng. Appl. Artif. Intell., March, 2023

Intelligent fault diagnosis of bevel gearboxes using semi-supervised probability support matrix machine and infrared imaging.
Reliab. Eng. Syst. Saf., 2023

2021
End-to-end unsupervised fault detection using a flow-based model.
Reliab. Eng. Syst. Saf., 2021

Robustness of maintenance support service networks: attributes, evaluation and improvement.
Reliab. Eng. Syst. Saf., 2021

A novel approach of multisensory fusion to collaborative fault diagnosis in maintenance.
Inf. Fusion, 2021

2020
Deep transfer multi-wavelet auto-encoder for intelligent fault diagnosis of gearbox with few target training samples.
Knowl. Based Syst., 2020

2019
Application of Bayesian Networks in Reliability Evaluation.
IEEE Trans. Ind. Informatics, 2019

System availability assessment using a parametric Bayesian approach: a case study of balling drums.
Int. J. Syst. Assur. Eng. Manag., 2019

A Review on Deep Learning Applications in Prognostics and Health Management.
IEEE Access, 2019

Deep Learning for Track Quality Evaluation of High-Speed Railway Based on Vehicle-Body Vibration Prediction.
IEEE Access, 2019

A Dynamic Prescriptive Maintenance Model Considering System Aging and Degradation.
IEEE Access, 2019

An Active Learning Method Based on Uncertainty and Complexity for Gearbox Fault Diagnosis.
IEEE Access, 2019

Bearing Fault Diagnosis Based on Subband Time-Frequency Texture Tensor.
IEEE Access, 2019

Prognostics of polygonalization of high-speed railway train wheels using a generalized additive model smoothed by spline-backfitted kernel.
Proceedings of the 2019 IEEE International Conference on Prognostics and Health Management, 2019

2018
Adaptive kernel density-based anomaly detection for nonlinear systems.
Knowl. Based Syst., 2018

A Dynamic Maintenance Strategy for Prognostics and Health Management of Degrading Systems: Application in Locomotive Wheel-sets.
Proceedings of the 2018 IEEE International Conference on Prognostics and Health Management, 2018

2017
Sliding Window-Based Fault Detection From High-Dimensional Data Streams.
IEEE Trans. Syst. Man Cybern. Syst., 2017

Reliability evaluation of non-repairable phased-mission common bus systems with common cause failures.
Comput. Ind. Eng., 2017

2015
An angle-based subspace anomaly detection approach to high-dimensional data: With an application to industrial fault detection.
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.
Reliab. Eng. Syst. Saf., 2015

2014
Reliability Analysis for Degradation of Locomotive Wheels using Parametric Bayesian Approach.
Qual. Reliab. Eng. Int., 2014

2008
A Two-Stage Failure Model for Bayesian Change Point Analysis.
IEEE Trans. Reliab., 2008


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