Response statistics of rotating shaft with non-linear elastic restoring forces by path integration

Abstract Extreme statistics of random vibrations is studied for a Jeffcott rotor under uniaxial white noise excitation. Restoring force is modelled as elastic non-linear; comparison is done with linearized restoring force to see the force non-linearity effect on the response statistics. While for the linear model analytical solutions and stability conditions are available, it is not generally the case for non-linear system except for some special cases. The statistics of non-linear case is studied by applying path integration (PI) method, which is based on the Markov property of the coupled dynamic system. The Jeffcott rotor response statistics can be obtained by solving the Fokker–Planck (FP) equation of the 4D dynamic system. An efficient implementation of PI algorithm is applied, namely fast Fourier transform (FFT) is used to simulate dynamic system additive noise. The latter allows significantly reduce computational time, compared to the classical PI. Excitation is modelled as Gaussian white noise, however any kind distributed white noise can be implemented with the same PI technique. Also multidirectional Markov noise can be modelled with PI in the same way as unidirectional. PI is accelerated by using Monte Carlo (MC) estimated joint probability density function (PDF) as initial input. Symmetry of dynamic system was utilized to afford higher mesh resolution. Both internal (rotating) and external damping are included in mechanical model of the rotor. The main advantage of using PI rather than MC is that PI offers high accuracy in the probability distribution tail. The latter is of critical importance for e.g. extreme value statistics, system reliability, and first passage probability.

[1]  Torgeir Moan,et al.  Stochastic Dynamics of Marine Structures: Index , 2012 .

[2]  Arvid Naess,et al.  Response of a Rotating Shaft to Uniaxial Random Excitation , 2012 .

[3]  高田 毅士,et al.  Applications of statistics and probability in civil engineering : proceedings of the 10th international conference on applications of statistics and probability in civil engineering, ICASP10, Tokyo, Japan, 31 July - 3 August 2007 , 2007 .

[4]  A. Naess,et al.  Efficient path integration methods for nonlinear dynamic systems , 2000 .

[5]  B. Ryzhik,et al.  Random vibrations of a damped rotating shaft , 2005 .

[6]  A. Jazwinski.  Stochastic Processes and Filtering Theory , 1970 .

[7]  Chong-Won Lee,et al.  Vibration Analysis of Rotors , 1994 .

[8]  Arvid Naess,et al.  Pendulum's rotational motion governed by a stochastic Mathieu equation , 2013 .

[9]  A. Naess,et al.  Response probability density functions of strongly non-linear systems by the path integration method , 2006 .

[10]  Panagiotis Alevras,et al.  GPU computing for accelerating the numerical Path Integration approach , 2016 .

[11]  Bernt J. Leira,et al.  Stochastic Dynamic Analysis and Reliability of a Vessel Rolling in Random Beam Seas , 2015 .

[12]  P. Spanos,et al.  An analytical Wiener path integral technique for non-stationary response determination of nonlinear oscillators , 2012 .

[13]  Cesare Rossi,et al.  Non-periodic motions of a Jeffcott rotor with non-linear elastic restoring forces , 1996 .

[14]  Giampiero Mastinu,et al.  Multi-objective stochastic optimisation of the suspension system of road vehicles , 2006 .