World's Best Scientists 2026 revealed!

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
51
Citations
8983
World Ranking
1123
National Ranking
138

Overview

Minping Jia is affiliated with Southeast University in China and has a significant body of work in the field of Engineering. Their research spans several specialized subfields including Control and Systems Engineering, Mechanical Engineering, Mechanics of Materials, Artificial Intelligence, and Radiological and Ultrasound Technology.

The scientist has contributed extensively to topics related to machine fault diagnosis and mechanical system reliability. The main research themes covered in their publications include:

  • Machine Fault Diagnosis Techniques
  • Gear and Bearing Dynamics Analysis
  • Engineering Diagnostics and Reliability
  • Fault Detection and Control Systems
  • Non-Destructive Testing Techniques
  • Occupational Health and Safety Research
  • Mechanical Failure Analysis and Simulation

Frequent publication venues for Minping Jia's work include:

  • Reliability Engineering & System Safety
  • IEEE Transactions on Instrumentation and Measurement
  • Measurement
  • Mechanical Systems and Signal Processing
  • IEEE/ASME Transactions on Mechatronics

They have authored several notable papers, including:

  • "A novel time-frequency Transformer based on self-attention mechanism and its application in fault diagnosis of rolling bearings" (2021) in Mechanical Systems and Signal Processing
  • "A novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings" (2021) in Reliability Engineering & System Safety
  • "Self-supervised pretraining via contrast learning for intelligent incipient fault detection of bearings" (2021) in Reliability Engineering & System Safety
  • "A BiGRU method for remaining useful life prediction of machinery" (2020) in Measurement
  • "Intelligent Fault Diagnosis of Gearbox Under Variable Working Conditions With Adaptive Intraclass and Interclass Convolutional Neural Network" (2022) in IEEE Transactions on Neural Networks and Learning Systems

Minping Jia has collaborated extensively with several co-authors, with multiple joint publications alongside:

  • Yifei Ding
  • Xiaoan Yan
  • Yudong Cao
  • Peng Ding
  • Xiaoli Zhao

Best Publications

  • A novel time–frequency Transformer based on self–attention mechanism and its application in fault diagnosis of rolling bearings

    Unknown

  • A novel optimized SVM classification algorithm with multi-domain feature and its application to fault diagnosis of rolling bearing

    Xiaoan Yan;Minping Jia

  • Intelligent fault diagnosis of rotating machinery using improved multiscale dispersion entropy and mRMR feature selection

    Unknown

  • A novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings

    Yudong Cao;Yifei Ding;Minping Jia;Rushuai Tian

  • Intelligent Fault Diagnosis of Gearbox Under Variable Working Conditions With Adaptive Intraclass and Interclass Convolutional Neural Network

    Unknown

  • Application of CSA-VMD and optimal scale morphological slice bispectrum in enhancing outer race fault detection of rolling element bearings

    Unknown

  • Self-supervised pretraining via contrast learning for intelligent incipient fault detection of bearings

    Yifei Ding;Jichao Zhuang;Peng Ding;Minping Jia

  • A BiGRU method for remaining useful life prediction of machinery

    Daoming She;Daoming She;Minping Jia

  • Engineering Applications of Intelligent Monitoring and Control 2014

    Qingsong Xu;Pak-Kin Wong;Minping Jia;Chengjin Zhang

  • DCC-CenterNet: A rapid detection method for steel surface defects

    Rushuai Tian;Minping Jia

  • Transfer learning for remaining useful life prediction of multi-conditions bearings based on bidirectional-GRU network

    Yudong Cao;Minping Jia;Peng Ding;Yifei Ding

  • Compound fault diagnosis of rotating machinery based on OVMD and a 1.5-dimension envelope spectrum

    Xiaoan Yan;Minping Jia;Ling Xiang

  • Semisupervised Graph Convolution Deep Belief Network for Fault Diagnosis of Electormechanical System With Limited Labeled Data

    Xiaoli Zhao;Minping Jia;Zheng Liu

  • Multiscale cascading deep belief network for fault identification of rotating machinery under various working conditions

    Xiaoan Yan;Xiaoan Yan;Ying Liu;Minping Jia

  • A convolutional neural network-based method for workpiece surface defect detection

    Junjie Xing;Minping Jia

  • Normalized Conditional Variational Auto-Encoder with adaptive Focal loss for imbalanced fault diagnosis of Bearing-Rotor system

    Unknown

  • Rolling Bearing Fault Diagnosis Based on VMD-MPE and PSO-SVM

    Unknown

  • Deep Laplacian Auto-encoder and its application into imbalanced fault diagnosis of rotating machinery

    Xiaoli Zhao;Minping Jia;Mingyao Lin

  • Remaining useful life estimation using deep metric transfer learning for kernel regression

    Yifei Ding;Minping Jia;Qiuhua Miao;Peng Huang

  • Multistep forecasting for diurnal wind speed based on hybrid deep learning model with improved singular spectrum decomposition

    Xiaoan Yan;Ying Liu;Yadong Xu;Minping Jia

  • Deep regularized variational autoencoder for intelligent fault diagnosis of rotor–bearing system within entire life-cycle process

    Xiaoan Yan;Daoming She;Yadong Xu;Minping Jia

  • Model Reference Adaptive Control With Perturbation Estimation for a Micropositioning System

    Qingsong Xu;Minping Jia

  • Multichannel fault diagnosis of wind turbine driving system using multivariate singular spectrum decomposition and improved Kolmogorov complexity

    Xiaoan Yan;Ying Liu;Yadong Xu;Minping Jia

  • A novel unsupervised deep learning network for intelligent fault diagnosis of rotating machinery

    Xiaoli Zhao;Minping Jia

  • Remaining Useful Life Estimation Under Multiple Operating Conditions via Deep Subdomain Adaptation

    Yifei Ding;Minping Jia;Yudong Cao

  • Intelligent Fault Diagnosis of Multichannel Motor–Rotor System Based on Multimanifold Deep Extreme Learning Machine

    Xiaoli Zhao;Minping Jia;Peng Ding;Chen Yang

  • Meta deep learning based rotating machinery health prognostics toward few-shot prognostics

    Peng Ding;Minping Jia;Xiaoli Zhao

Frequent Co-Authors

Xiaoli Zhao
Xiaoli Zhao Tongji University
Michael Pecht
Michael Pecht University of Maryland, College Park

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