Dr Rob Barthorpe

MEng, CEng, PhD

Dr Rob Barthorpe

Lecturer

Year in Industry Tutor

Department of Mechanical Engineering
Sir Frederick Mappin Building
Mappin Street
Sheffield
S1 3JD
UK

Telephone: +44 (0) 114 222 7762
Fax: +44 (0) 114 222 7890

Profile

Rob Barthorpe is a lecturer in the Dynamics Research Group in the Department of Mechanical Engineering. He has a first degree in Mechanical Engineering with a Modern Language from the University of Sheffield and was awarded his PhD from the same university in 2010. Rob's research is in the areas of structural health monitoring, uncertainty analysis and the verification and validation of numerical models.

Areas of Research

Dr Barthorpe's research covers a range of problems in the field of structural dynamics and beyond, with an underlying theme being the integration of numerical modelling and experimental data. Structural health monitoring is one of his major research themes. The broad aim of an SHM system is to be able to identify, at an early stage, occurrences of damage that may ultimately lead to the failure of the component or system being monitored.

Established approaches to this task typically fall into one of two categories: they are either based entirely on experimental data, or make use of a numerical model that is periodically updated as new data becomes available. Both of these approaches have distinct drawbacks: for the former, lack of appropriate experimental data is the major issue; for the latter, model-form uncertainty is among the challenges faced.

Part of Rob's work is in investigating ways to circumvent the lack of data problem through novel experimental and data-modelling techniques. A larger part is in developing new methods for integrating experimental and numerical methods, such that uncertainty in both the experimental measurements and the numerical model may be accounted for.

These methods are being developed for application to aerospace structures, wind turbines and civil infrastructure. However, the domain of applicability is much broader as the issues of handling uncertainty, solving inverse problems and overcoming test-model discrepancy are pervasive in many branches of science and engineering. Applications being investigated include the energy performance of buildings and the modelling of human bones.

Teaching

Dr Barthorpe currently teaches Signal Processing and Instrumentation (MEC409) to fourth year undergraduates and MSc students

Current Research Grants

ESPRC/Wellcome Trust fellowship, 2010-11, £44k (PI)

Journal articles

Papatheou E, Manson G, Barthorpe RJ & Worden K (2010) The use of pseudo-faults for novelty detection in SHM. J SOUND VIB, 329(12), 2349-2366.
Deraemaeker A, Preumont A, Reynders E, De Roeck G, Kullaa J, Lamsa V, Worden K, Manson G, Barthorpe R, Papatheou E, Kudela P, Malinowski P, Ostachowicz W & Wandowski T (2010) Vibration-based structural health monitoring using large sensor networks. SMART STRUCTURES AND SYSTEMS, 6(3), 335-347.
Manson G & Barthorpe RJ (2010) Advanced feature selection for simplified pattern recognition within the damage identification framework. SHOCK AND VIBRATION, 17(4-5), 589-599.
Hensman JJ & Barthorpe RJ (2009) Feature extraction from spectral data using the bayesian evidence framework. Key Engineering Materials, 413-414, 151-158.

Chapters

Barthorpe RJ & Worden K (2009) Sensor placement optimisation for structural health monitoring In Boller C, Chang F & Fujino YZ (Ed.), Encyclopedia of structural health monitoring (pp. 1239-1250). Chichester: Wiley.

Conferences

Dervilis N, Choi M, Antoniadou I, Farinholt KM, Taylor SG, Barthorpe RJ, Park G, Worden K, Farrar CR & IOP (2012) Novelty detection applied to vibration data from a CX-100 wind turbine blade under fatigue loading.. MODERN PRACTICE IN STRESS AND VIBRATION ANALYSIS 2012 (MPSVA 2012), 382
Barthorpe RJ, Cross EJ, Papatheou E & Worden K (2012) Some recent developments in structural health monitoring. Key Engineering Materials, 518, 298-318.
Dervilis N, Barthorpe R, Worden K & Staszewski WJ (2012) Structural Health Monitoring of composite material typical of wind turbine blades by novelty detection on vibration response. Key Engineering Materials, 518, 319-327.
Worden K, Barthorpe RJ & Hensman JJ (2012) Identification of hysteretic systems using NARX models, part II: A Bayesian approach. Conference Proceedings of the Society for Experimental Mechanics Series, 4, 57-65.
Worden K & Barthorpe RJ (2012) Identification of hysteretic systems using NARX models, part I: Evolutionary identification. Conference Proceedings of the Society for Experimental Mechanics Series, 4, 49-56.
Dervilis N, Barthorpe R, Antoniadou I, Worden K & Staszewski WJ (2012) Damage detection in carbon composite material typical of wind turbine blades using auto-associative neural networks. Proceedings of SPIE - The International Society for Optical Engineering, 8348
Barthorpe RJ (2011) Bayesian sensitivity analysis of numerical models for structural health monitoring. Structural Health Monitoring 2011: Condition-Based Maintenance and Intelligent Structures - Proceedings of the 8th International Workshop on Structural Health Monitoring, 1, 1300-1308.
Barthorpe RJ & Worden K (2011) Classification of multi-site damage using support vector machines. Journal of Physics: Conference Series, 305(1)
Barthorpe RJ, Manson G & Worden K (2011) Classification of Multi-Site Damage using Support Vector Machines
Barthorpe RJ & Worden K (2011) Multiple-site damage location using single-site training data. Conference Proceedings of the Society for Experimental Mechanics Series, 1, 195-201.
Papatheou E, Manson G, Barthorpe RJ & Worden K (2010) Damage location using added masses in a Piper Tomahawk aircraft wing
Barthorpe RJ, Worden K, Surace C & Demarie G (2009) A comparative study of approaches to damage detection
Barthorpe RJ, Manson G & Worden K (2009) A forward approach to model-based structural health monitoring
Barthorpe RJ, Worden K & Manson G (2009) Finite Element Model-based Feature Generation for Structural Health Monitoring
Barthorpe RJ (2009) Identification of robust damage-sensitive features for model-based structural health monitoring: an effect screening approach
Manson G & Barthorpe RJ (2009) Selecting Features for Damage Identification without Damaging the Structure
Barthorpe RJ, Worden K & Manson G (2008) An Investigation into the Necessary Model Fidelity for SHM Feature Selection. PROCEEDINGS OF THE FOURTH EUROPEAN WORKSHOP ON STRUCTURAL HEALTH MONITORING 2008, 980-989.
Papatheou E, Barthorpe R, Worden K & Manson G (2008) Fault induction using added masses for structural damage identification. PROCEEDINGS OF ISMA 2008: INTERNATIONAL CONFERENCE ON NOISE AND VIBRATION ENGINEERING, VOLS. 1-8, 3333-3344.
Papatheou E, Manson G, Worden K & Barthorpe R (2008) The Use of Pseudo-Faults for SHM Feature Selection and Pattern Recognition. PROCEEDINGS OF THE FOURTH EUROPEAN WORKSHOP ON STRUCTURAL HEALTH MONITORING 2008, 1104-1112.

Other

Simmermacher T, Cogan S, Horta LG & Barthorpe R (2012) Conference Proceedings of the Society for Experimental Mechanics Series: Preface. Conference Proceedings of the Society for Experimental Mechanics Series, 4.