Natural vibration response based damage detection for an operating wind turbine via Random Coefficient Linear Parameter Varying AR modelling

11th International Conference on Damage Assessment of Structures

物理学;材料科学

Avendaño-Valencia, L.D.^1 ; Fassois, S.D.^1

Stochastic Mechanical Systems and Automation (SMSA) Laboratory, Department of Mechanical and Aeronautical Engineering, University of Patras, Greece^1

关键词: Auto regressive models;    Hypothesis testing;    Linear parameter varying;    Non-stationary random vibration;    Normal operating conditions;    Random coefficients;    Stochastic approach;    Vibration response;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/628/1/012073/pdf
DOI  :  10.1088/1742-6596/628/1/012073

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

The problem of damage detection in an operating wind turbine under normal operating conditions is addressed. This is characterized by difficulties associated with the lack of measurable excitation(s), the vibration response non-stationary nature, and its dependence on various types of uncertainties. To overcome these difficulties a stochastic approach based on Random Coefficient (RC) Linear Parameter Varying (LPV) AutoRegressive (AR) models is postulated. These models may effectively represent the non-stationary random vibration response under healthy conditions and subsequently used for damage detection through hypothesis testing. The performance of the method for damage and fault detection in an operating wind turbine is subsequently assessed via Monte Carlo simulations using the FAST simulation package.