Presentation on theme: "Where Non-Smooth Systems Appear in Structural Dynamics"— Presentation transcript:
1Where Non-Smooth Systems Appear in Structural Dynamics Keith WordenDynamics Research GroupDepartment of Mechanical EngineeringUniversity of Sheffield
2Nonlinearity Nonlinearity is present in many engineering problems: Demountable structures with clearances and friction.Flexible structures – large amplitude motions.Aeroelasticity – limit cycles.Automobiles: squeaks and rattles, brake squeal, dampers.Vibration isolation: viscoelastics, hysteresis.Sensor/actuator nonlinearity: piezoelectrics…In many cases, the nonlinearity is non-smooth.2
3So, where are the problems in Structural Dynamics? System IdentificationStructural Health MonitoringActive/passive control of vibrationsControl…
4System Identification Automotive damper (shock absorber)Designed to be nonlinear.Physical model prohibitively complicated.Bilinear.
5System ID Standard SDOF system, If nonlinearities are ‘linear in the parameters’ there are many powerful techniques available.Even the most basic piecewise-linear system presents a problem.
6Everything OK if we know d – linear in the parameters. Otherwise need nonlinear least-squares.Iterative - need good initial estimates.Can use Genetic Algorithm.
7Genetic AlgorithmEncode parameters as binary bit-string – Individuals.Work with population of solutions.Combine solutions via genetic operators:SelectionCrossoverMutationMinimise cost function:
8Excellent solution:Derivative-free.‘Avoids local minima’.No need to differentiate/integrate time data.Directly optimises on ‘Model Predicted Output’ as opposed to ‘One-step-ahead’ predictions.
9Hysteresis Systems with ‘memory’: Bouc-Wen model is versatile. Nonlinear in the parameters.Unmeasured state z.Can use GA again – or Differential Evolution.
23Nonlinearity AgainOften, the occurrence of damage will change the structure of interest from a linear system to a nonlinear system e.g. a ‘breathing’ crack.This observation can be exploited in terms of selection of features, e.g. one can work with features like Liapunov exponents of time-series; if chaos is observed, system must be nonlinear. But…
24Tests for Nonlinearity HomogeneityReciprocityCoherenceFRF distortionHilbert transformCorrelation functions
29Problem is that system bifurcates and shifts in and out of chaos; features like liapunov exponents, correlation dimension etc. will not always work and are not monotonically increasing with damage severity.Figure shows dependence on frequency, but same picture appears with ‘crack depth’ as independent variableAre there better features?
33What needs to be done?Development of signal processing tools like estimator of Holder exponent.Better friction models (white/grey/black).Parameter estimation/optimisation methods (as a side-issue, convergence results for GAs etc.)Control methods for non-smooth systems.Versatile hysteresis models.Understanding of high-dimensional nonlinear models (e.g. FE).
34Quantities that increase monotonically with ‘severity of nonlinearity’? Engineers like random excitation - tools for stochastic DEs and PDEs with non-smooth nonlinearities.Contact/friction models for DEM.Sensitivity analysis/uncertainty propagation methods for systems that bifurcate.
35Acknowledgements Lawrie Virgin (Duke University) Chuck Farrar, Gyuhae Park (Los Alamos National Laboratory)Farid Al Bender (KUL, Leuven)Jem Rongong, Chian Wong, Brian Deacon, Jonny Haywood (University of Sheffield)Andreas Kyprianou (University of Cyprus)