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Mechanical and Aerospace Engineering
UK
2026

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
82
Citations
33383
World Ranking
177
National Ranking
9

Research.com Recognitions

  • 2026 - Research.com Mechanical and Aerospace Engineering in United Kingdom Leader Award
  • 2025 - Research.com Mechanical and Aerospace Engineering in United Kingdom Leader Award

Overview

Keith Worden is affiliated with the University of Sheffield in the United Kingdom. Their research predominantly spans the fields of Engineering and Computer Science, with a particular focus on several subfields including Civil and Structural Engineering, Artificial Intelligence, Mechanical Engineering, Control and Systems Engineering, and Statistics, Probability, and Uncertainty.

The scientist's main topics of research include Structural Health Monitoring Techniques, Infrastructure Maintenance and Monitoring, Concrete Corrosion and Durability, Probabilistic and Robust Engineering Design, Non-Destructive Testing Techniques, Ultrasonics and Acoustic Wave Propagation, and Fault Detection and Control Systems.

Keith Worden has published extensively in several academic venues. The most frequent publication venues include:

  • Mechanical Systems and Signal Processing
  • arXiv (Cornell University)
  • Proceedings of the 13th International Workshop on Structural Health Monitoring
  • SSRN Electronic Journal
  • Data-Centric Engineering

Their recent papers illustrate ongoing work in engineering dynamics, structural health monitoring, and population-based SHM (Structural Health Monitoring):

  • Digital Twins: State-of-the-Art and Future Directions for Modeling and Simulation in Engineering Dynamics Applications (2020), ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical Engineering
  • On the application of domain adaptation in structural health monitoring (2020), Mechanical Systems and Signal Processing
  • Foundations of population-based SHM, Part III: Heterogeneous populations - Mapping and transfer (2020), Mechanical Systems and Signal Processing
  • Foundations of population-based SHM, Part I: Homogeneous populations and forms (2020), Mechanical Systems and Signal Processing
  • Foundations of Population-based SHM, Part II: Heterogeneous populations - Graphs, networks, and communities (2020), Mechanical Systems and Signal Processing

Keith Worden collaborates frequently with several co-authors. The regular collaborators include:

  • Nikolaos Dervilis
  • Elizabeth J. Cross
  • Lawrence A. Bull
  • Paul Gardner
  • Timothy J. Rogers

Best Publications

  • An introduction to structural health monitoring

    Charles R Farrar;Keith Worden

  • Structural Health Monitoring: A Machine Learning Perspective

    Charles R. Farrar;Keith Worden

  • Past, present and future of nonlinear system identification in structural dynamics

    Gaëtan Kerschen;Keith Worden;Alexander F. Vakakis;Alexander F. Vakakis;Jean Claude Golinval

  • Nonlinearity in Structural Dynamics: Detection, Identification and Modelling

    K Worden;G.R Tomlinson

  • Structural Health Monitoring

    Unknown

  • The fundamental axioms of structural health monitoring

    Keith Worden;Charles R Farrar;Graeme Manson;Gyuhae Park

  • DAMAGE DETECTION USING OUTLIER ANALYSIS

    K. Worden;G. Manson;N.R.J. Fieller

  • Structural Health Monitoring Using Statistical Pattern Recognition Techniques

    Hoon Sohn;Charles R. Farrar;Norman F. Hunter;Keith Worden

  • An Overview of Intelligent Fault Detection in Systems and Structures

    K. Worden;J. M. Dulieu-Barton

  • Nonlinearity in Structural Dynamics

    K Worden;G R Tomlinson

  • The application of machine learning to structural health monitoring

    Keith Worden;Graeme Manson

  • Machine learning algorithms for damage detection under operational and environmental variability

    Eloi Figueiredo;Gyuhae Park;Charles R Farrar;Keith Worden

  • TIME–FREQUENCY ANALYSIS IN GEARBOX FAULT DETECTION USING THE WIGNER–VILLE DISTRIBUTION AND PATTERN RECOGNITION

    W.J. Staszewski;K. Worden;G.R. Tomlinson

  • Optimal sensor placement for fault detection

    K Worden;A.P Burrows

  • Long-term monitoring and data analysis of the Tamar Bridge

    E.J. Cross;K.Y. Koo;J.M.W. Brownjohn;K. Worden

  • STRUCTURAL FAULT DETECTION USING A NOVELTY MEASURE

    K. Worden

  • Statistical Damage Classification Under Changing Environmental and Operational Conditions

    Hoon Sohn;Keith Worden;Charles R. Farrar

  • Natural computing for mechanical systems research: A tutorial overview

    Keith Worden;Wieslaw J. Staszewski;James J. Hensman

  • EXPERIMENTAL VALIDATION OF A STRUCTURAL HEALTH MONITORING METHODOLOGY: PART I. NOVELTY DETECTION ON A LABORATORY STRUCTURE

    K. Worden;G. Manson;D. Allman

  • Structural health monitoring algorithm comparisons using standard data sets

    Eloi Figueiredo;Gyuhae Park;Joaquim Figueiras;Charles Farrar

  • Multivariate statistics process control for dimensionality reduction in structural assessment

    L. E. Mujica;J. Vehi;M. Ruiz;Michel Verleysen

  • 13. Fundamental Axioms of Structural Health Monitoring

    Charles R. Farrar;Keith Worden

Frequent Co-Authors

Charles R. Farrar
Charles R. Farrar Los Alamos National Laboratory
Wieslaw J. Staszewski
Wieslaw J. Staszewski AGH University of Science and Technology
Hoon Sohn
Hoon Sohn Korea Advanced Institute of Science and Technology
David J. Wagg
David J. Wagg University of Sheffield
Gyuhae Park
Gyuhae Park Chonnam National University
Neil D. Sims
Neil D. Sims University of Sheffield
Brian Culshaw
Brian Culshaw University of Strathclyde
Mohamed Thariq Hameed Sultan
Mohamed Thariq Hameed Sultan Universiti Putra Malaysia
Faizal Mustapha
Faizal Mustapha Universiti Putra Malaysia
Gaëtan Kerschen
Gaëtan Kerschen University of Liège

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