Contact Dr Suresh Perinpanayagam

Areas of expertise

Background

Dr Suresh Perinpanayagam graduated with a Master of Engineering from Imperial College London in 1996. He first started work at the Ford Motor Company Development Centres in Dunton, UK and Merknick, Germany to implement an integrated engineering platform for new vehicle development. This platform saved millions of pounds in cost for vehicle development and eventually established the company as an agile establishment. After 3 years, Suresh returned to Imperial College London to complete his PhD. This was done at the Rolls-Royce University Technology Centre at Imperial College, under the auspices of the FP7 programme. Suresh worked with major engine manufacturers in Europe (Rolls-Royce, UK; MTU, Germany; SNECMA, France).

After graduating in 2004, Suresh worked as a Associate Research Scientist at the Singapore Institute of Manufacturing Technology (SIMTech), which is an A*STAR (Agency for Science, Technology and Research) research institute in Singapore. Suresh was one of the pioneering researchers who was awarded $1 million project funded by Boeing, EADS and Singapore's Science and Engineering Research Council (SERC) under the auspices of the SERC Aerospace Research Programme. The project looked at developing novel sensors and signal-processing techniques for the detection of defects on composites of thickness of more than one inch, such as those on the Boeing 787 skins. Suresh jointly collaborated with Imperial College London, UK, Uppsala University, Sweden and Nanyang Technological University, Singapore. Suresh managed fifteen people in this project which involved developing existing staff to work on the project and recruiting new staff, training them on the research activities, industrial engagement and focusing them on the business deliverables.

Current activities

Dr Suresh Perinpanayagam is a Senior Lecturer in Intelligent Systems, in the Integrated Vehicle Health Management (IVHM) Centre at Cranfield University. He develops Adaptive Intelligent systems for providing health management capability for the aerospace, automotive, rail, infrastructure and energy sectors. Adaptive Intelligent systems coordinate perception, reasoning and action to pursue multiple goals while functioning autonomously in dynamic environments. Adaptive Intelligent systems for self-health awareness of assets are set to play an ever-increasing role in the above-mentioned industries, from design to manufacture, through- life engineering and end-of- life disposal of these assets. Suresh focuses on developing these capabilities for electrical, electronic and electro-mechanical systems and smart structures.

Suresh has rapidly established a research group with 5 current research grants as principal investigator worth £1.4M in total, including industrial projects, EPSRC, TSB and EU-FP7 projects. His research group consists of 2 research fellows, 5 full-time PhDs and a number of MSc students.

Suresh also manages a laboratory for Adaptive Intelligent system development with distributed (wired and wireless) sensor networks, data acquisition, data-mining, data management and energy harvesting capabilities for aerospace, rail, critical infrastructure and renewable energy systems. This laboratory develops data-mining techniques for anomaly detection, diagnostics, prognostics, information fusion, self-healing, predictive maintenance and logistical support for electro-mechanical systems from the above-mentioned sectors.

Suresh has published one book chapter on Sensors, Instrumentation and Signal Processing in the SAE International book on Integrated Vehicle Health Management and numerous research papers.

Dr Perinpanayagam has research expertise in the following key areas:

  • Sensor networks for system health monitoring
  • Technologies for Adaptive Intelligent systems: data-mining, artificial intelligence, diagnostics, prognostics, self-healing
  • Knowledge representation and reasoning: logic and probabilistic reasoning, reasoning for spatial-temporal phenomena and non-monotonic reasoning
  • Real-time hybrid (model-based and data-driven) prognostic models for system health management
  • Dealing with uncertainty: resilient approaches for recognising, dealing with, and learning from errors and inconsistent sensor data
  • Sensor fusion, data fusion and information fusion
  • Software, hardware and communication architecture for health management systems
  • Statistical techniques for reliability estimation for electrical machines, microelectronic and power electronic systems
  • Multi-domain (electrical, thermal, mechanical, etc) failure model simulation for electrical machines, microelectronic and power electronic systems
  • Highly-accelerated life test development for multi-domain failure model validation for electro-mechanical systems
  • High-temperature sensors and electronics Energy-efficient and reconfigurable systems
  • Multi-functional materials and additive manufacturing for integrated sensor-structure systems.

Suresh is part of the working group developing the IEEE Standard for Prognostics and Health Management. He is also the associate editor for IEEE Transactions on Power Electronics Special Issue on Robust Design and Reliability in Power Electronics.

Clients

  • Thales Group
  • Meggitt Systems
  • The Boeing Company
  • Network Rail
  • Embraer
  • BAE Systems
  • Rolls-Royce
  • EADS
  • MOD
  • DSTL
  • EPSRC
  • Lufthansa Technik AG
  • Central Networks
  • TSB.

Publications

Articles In Journals

Conference Papers

Books

  • Cubillo A & Perinpanayagam S (2016) Challenges of Redesigning a Planetary Transmission to Be Made by Additive Manufacturing. In: Advances in Manufacturing Technology XXX: Proceedings of the 14th International Conference on Manufacturing Research, incorporating the 31st National Conference on Manufacturing Research, September 6 – 8, 2016, Loughborough University, UK. Goh YM, Case K. (ed.), Amsterdam: IOS Press, p. 81-86.
  • Cubillo A, Perinpanayagam S., Rodriguez M, Collantes I & Vermeulen J. (2016) Prognostics Health Management System Based on Hybrid Model to Predict Failures of a Planetary Gear Transmission. In: Machine Learning for Cyber Physical Systems: Selected papers from the International Conference ML4CPS 2015. Niggemann, Oliver, Beyerer, Jürgen (ed.), Berlin: Springer- Verlag, p. 33-44.
  • Suresh Perinpanayagam (2013) Sensor, Instrumentation and Signal Processing. In: Integrated Vehicle Health Management: The Technology. Ian K. Jennions (ed.), SAE International, p. 5-25.
  • Walker R, Perinpanayagam S & Jennions I. (2012) Simulating Unbalance for Future IVHM Applications. In: Topics in Model Validation and Uncertainty Quantification, Volume 4 Proceedings of the 30th IMAC, A Conference on Structural Dynamics, 2012. T. Simmermacher, S. Cogan, L.G. Horta, R. Barthorpe (ed.), Springer, p. 141-148.