World's Best Scientists 2026 revealed!

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
51
Citations
10586
World Ranking
1107
National Ranking
76

Electronics and Electrical Engineering

D-Index
50
Citations
10494
World Ranking
2789
National Ranking
155

Overview

Fengshou Gu is a researcher affiliated with the University of Huddersfield in the United Kingdom, focusing primarily on the field of engineering. Their scholarly work encompasses over a thousand publications, with significant contributions across several subfields including mechanical engineering, control and systems engineering, electrical and electronic engineering, mechanics of materials, and civil and structural engineering.

The main topics of Fengshou Gu's research broadly cover:

  • Machine Fault Diagnosis Techniques
  • Gear and Bearing Dynamics Analysis
  • Fault Detection and Control Systems
  • Tribology and Lubrication Engineering
  • Advanced Machining Processes and Optimization
  • Structural Health Monitoring Techniques
  • Engineering Diagnostics and Reliability

Throughout their career, Fengshou Gu has published extensively in several academic journals. The most frequent venues include:

  • Mechanical Systems and Signal Processing
  • SSRN Electronic Journal
  • Measurement
  • Structural Health Monitoring
  • Measurement Science and Technology

Fengshou Gu has authored contributions to book publications as well, notably a work published by Springer Nature (Netherlands) titled Proceedings of IncoME-VI and TEPEN 2021 in 2022.

Among the recent papers associated with Fengshou Gu are:

  • A review on online state of charge and state of health estimation for lithium-ion batteries in electric vehicles, 2021, Energy Reports
  • Digital twin-driven partial domain adaptation network for intelligent fault diagnosis of rolling bearing, 2023, Reliability Engineering & System Safety
  • Attention-based deep meta-transfer learning for few-shot fine-grained fault diagnosis, 2023, Knowledge-Based Systems
  • Product envelope spectrum optimization-gram: An enhanced envelope analysis for rolling bearing fault diagnosis, 2023, Mechanical Systems and Signal Processing
  • Vibration characteristics and condition monitoring of internal radial clearance within a ball bearing in a gear-shaft-bearing system, 2021, Mechanical Systems and Signal Processing

The researcher has collaborated frequently with a number of colleagues, with co-authorship counts indicating ongoing partnerships with:

  • Andrew D. Ball
  • Andrew Ball
  • Dong Zhen
  • Guojin Feng
  • Zhanqun Shi

Best Publications

  • A review of numerical analysis of friction stir welding

    Xiaocong He;Fengshou Gu;Andrew Ball

  • A review on online state of charge and state of health estimation for lithium-ion batteries in electric vehicles

    Zuolu Wang;Guojin Feng;Dong Zhen;Fengshou Gu

  • Prediction Models for Density and Viscosity of Biodiesel and their Effects on Fuel Supply System in CI Engines

    Belachew Tesfa;Rakesh Mishra;Fengshou Gu;Nicholas Powles

  • Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review.

    Xiaoli Tang;Xianghong Wang;Robert Cattley;Fengshou Gu

  • The measurement of instantaneous angular speed

    Yuhua Li;Fengshou Gu;Georgina Harris;Andrew Ball

  • Detecting the crankshaft torsional vibration of diesel engines for combustion related diagnosis

    Peter Charles;Jyoti K. Sinha;Fengshou Gu;Liam Lidstone

  • Numerical simulation and experimental study of a two-stage reciprocating compressor for condition monitoring

    M. Elhaj;Fengshou Gu;Andrew Ball;A. Albarbar

  • Combustion and performance characteristics of CI (compression ignition) engine running with biodiesel

    B. Tesfa;R. Mishra;C. Zhang;F. Gu

  • A STUDY OF THE NOISE FROM DIESEL ENGINES USING THE INDEPENDENT COMPONENT ANALYSIS

    W Li;Fengshou Gu;Andrew Ball;A Y T Leung

  • Water injection effects on the performance and emission characteristics of a CI engine operating with biodiesel

    Belachew Tesfa;Rakesh Mishra;Fengshou Gu;Andrew Ball

  • Electrical motor current signal analysis using a modified bispectrum for fault diagnosis of downstream mechanical equipment

    F. Gu;Y. Shao;N. Hu;A. Naid

  • Diesel engine fuel injection monitoring using acoustic measurements and independent component analysis

    A. Albarbar;Fengshou Gu;Andrew Ball

  • The development of an adaptive threshold for model-based fault detection of a nonlinear electro-hydraulic system

    Zhanqun Shi;Fengshou Gu;Barry Lennox;Andrew Ball

  • Modern techniques for condition monitoring of railway vehicle dynamics

    R. W. Ngigi;Crinela Pislaru;Andrew Ball;Fengshou Gu

  • Gear tooth stiffness reduction measurement using modal analysis and its use in wear fault severity assessment of spur gears

    Isa Yesilyurt;Fengshou Gu;Andrew D. Ball

  • Thermal image enhancement using bi-dimensional empirical mode decomposition in combination with relevance vector machine for rotating machinery fault diagnosis

    Van Tung Tran;Bo Suk Yang;Fengshou Gu;Andrew Ball

  • Modelling acoustic emissions generated by sliding friction

    Yibo Fan;Fengshou Gu;Andrew Ball

  • A new method of accurate broken rotor bar diagnosis based on modulation signal bispectrum analysis of motor current signals

    Fengshou Gu;Fengshou Gu;T. Wang;Ahmed Alwodai;Xiange Tian

  • Investigations of strength and energy absorption of clinched joints

    Xiaocong He;Lun Zhao;Huiyan Yang;Baoying Xing

  • An Investigation of the Effects of Measurement Noise in the Use of Instantaneous Angular Speed for Machine Diagnosis

    Fengshou Gu;Iisa Yesilyurt;Yuhua Li;Georgina Harris

Frequent Co-Authors

Andrew Ball
Andrew Ball University of Huddersfield
Yimin Shao
Yimin Shao Chongqing University
Fulei Chu
Fulei Chu Tsinghua University
Uwe Kruger
Uwe Kruger Rensselaer Polytechnic Institute
Ning Hu
Ning Hu Hebei University of Technology
Qingbo He
Qingbo He Shanghai Jiao Tong University
Zaigang Chen
Zaigang Chen Southwest Jiaotong University
Simon Iwnicki
Simon Iwnicki University of Huddersfield

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