Smart Sensing for Structural Health Monitoring (S3HM)

Lead Research Organisation: University of Sheffield
Department Name: Mechanical Engineering


The cost of unplanned maintenance for structures and systems is a significant issue in a number of fields of Engineering. For example, aircraft are critical structures which fall within the domain of Mechanical Engineering, bridges fall within the remit of Civil Engineering. A potential approach to reducing maintenance costs is to convert all unplanned maintenance to planned maintenance. In order to do this, one needs a means of assessing the health of a structure on a continuous basis. This is the domain of Structural Health Monitoring (SHM). The current project aims to develop SHM technologies based on the consideration of measured vibration data from structures. The idea is that the measured data will inform the Engineer of the current state of health. The approach taken will be based on advanced concepts of pattern recognition and machine learning. Algorithms will be developed which can learn the patterns in data which signal damage. A major problem in SHM is concerned with false indications of damage caused by the environmental conditions (e.g. the temperature) of the structure changing. A major part of this project will be concerned with the development of algorithms which can deal with the issues of environmental uncertainty.Another advantage of the availability of effective SHM is that one can adopt a damage tolerant approach to the design of the structure, this will give potential reductions in the design safety factors which will be passed on as reductions in manufacture cost.


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A Deraemaeker (2010) Vibration-based structural health monitoring using large sensor networks in Smart Structures and Systems

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Barthorpe R (2017) On multi-site damage identification using single-site training data in Journal of Sound and Vibration

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Papatheou E (2010) The use of pseudo-faults for novelty detection in SHM in Journal of Sound and Vibration

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Worden K (2007) The fundamental axioms of structural health monitoring in Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences

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Worden K (2009) An evidence-based approach to damage location on an aircraft structure in Mechanical Systems and Signal Processing