Peter L Green
Peter L Green
Senior Lecturer, University of Liverpool
Verified email at liverpool.ac.uk - Homepage
Title
Cited by
Cited by
Year
The benefits of Duffing-type nonlinearities and electrical optimisation of a mono-stable energy harvester under white Gaussian excitations
PL Green, K Worden, K Atallah, ND Sims
Journal of Sound and Vibration 331 (20), 4504-4517, 2012
1282012
Energy harvesting from human motion and bridge vibrations: An evaluation of current nonlinear energy harvesting solutions
PL Green, E Papatheou, ND Sims
Journal of Intelligent Material Systems and Structures 24 (12), 1494-1505, 2013
1102013
Bayesian and Markov chain Monte Carlo methods for identifying nonlinear systems in the presence of uncertainty
PL Green, K Worden
Philosophical Transactions of the Royal Society A: Mathematical, Physical …, 2015
622015
Bayesian system identification of a nonlinear dynamical system using a novel variant of simulated annealing
PL Green
Mechanical Systems and Signal Processing 52, 133-146, 2015
622015
Bayesian system identification of dynamical systems using highly informative training data
PL Green, EJ Cross, K Worden
Mechanical systems and signal processing 56, 109-122, 2015
362015
On the identification and modelling of friction in a randomly excited energy harvester
PL Green, K Worden, ND Sims
Journal of Sound and Vibration 332 (19), 4696-4708, 2013
292013
Fast Bayesian identification of a class of elastic weakly nonlinear systems using backbone curves
TL Hill, PL Green, A Cammarano, SA Neild
Journal of sound and vibration 360, 156-170, 2016
282016
The effect of duffing-type non-linearities and coulomb damping on the response of an energy harvester to random excitations
PL Green, K Worden, K Atallah, ND Sims
Journal of Intelligent Material Systems and Structures 23 (18), 2039-2054, 2012
272012
Automatic fault detection for laser powder-bed fusion using semi-supervised machine learning
IA Okaro, S Jayasinghe, C Sutcliffe, K Black, P Paoletti, PL Green
Additive Manufacturing 27, 42-53, 2019
242019
Bayesian system identification of dynamical systems using large sets of training data: A MCMC solution
PL Green
Probabilistic Engineering Mechanics 42, 54-63, 2015
162015
A machine learning approach to nonlinear modal analysis
K Worden, PL Green
Mechanical Systems and Signal Processing 84, 34-53, 2017
152017
Estimating the parameters of dynamical systems from Big Data using Sequential Monte Carlo samplers
PL Green, S Maskell
Mechanical Systems and Signal Processing 93, 379-396, 2017
132017
A machine learning approach to nonlinear modal analysis
K Worden, PL Green
Dynamics of Civil Structures, Volume 4, 521-528, 2014
102014
Predicting fatigue performance of hot mix asphalt using artificial neural networks
TM Ahmed, PL Green, HA Khalid
Road Materials and Pavement Design 18 (sup2), 141-154, 2017
82017
Probabilistic modelling of a rotational energy harvester
PL Green, M Hendijanizadeh, L Simeone, SJ Elliott
Journal of Intelligent Material Systems and Structures 27 (4), 528-536, 2016
82016
Modelling friction in a nonlinear dynamic system via bayesian inference
PL Green, K Worden
Special Topics in Structural Dynamics, Volume 6, 543-553, 2013
82013
Bayesian system identification of nonlinear dynamical systems using a fast MCMC algorithm
PL Green
Proceedings of ENOC 2014, European Nonlinear Dynamics Conference, 2014
72014
Bayesian system identification of dynamical systems using reversible jump Markov Chain Monte Carlo
D Tiboaca, PL Green, RJ Barthorpe, K Worden
Topics in Modal Analysis II, Volume 8, 277-284, 2014
72014
Friction estimation in wind turbine blade bearings
N Stevanović, PL Green, K Worden, PH Kirkegaard
Structural Control and Health Monitoring 23 (1), 103-122, 2016
62016
Fast Bayesian identification of multi-mode systems using backbone curves
TL Hill, PL Green, A Cammarano, SA Neild
Journal of Sound and Vibration, 2015
62015
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