Mooring Damage Identification of Floating Wind Turbine Using a Non-Probabilistic Approach Under Different Environmental Conditions  

采用非概率方法对不同环境条件下的漂浮式风力机进行系泊损伤识别

作　　者：Pooya Hajinezhad Dehkharghani Mir Mohammad Ettefagh Reza Hassannejad 

机构地区：[1]Faculty of Mechanical Engineering,University of Tabriz,Tabriz 5166616471,Iran

出　　处：《Journal of Marine Science and Application》2021年第1期156-169,共14页船舶与海洋工程学报（英文版）

摘　　要：This paper discusses the damage identification in the mooring line system of a floating wind turbine(FWT)exposed to various environmental loads.The proposed method incorporates a non-probabilistic method into artificial neural networks(ANNs).The non-probabilistic method is used to overcome the problem of uncertainties.For this purpose,the interval analysis method is used to calculate the lower and upper bounds of ANNs input data.This data contains some of the natural frequencies utilized to train two different ANNs and predict the output data which is the interval bounds of mooring line stiffness.Additionally,in order to reduce computational time and more importantly,identify damage in various conditions,the proposed method is trained using constant loads(CL)case(deterministic loads,including constant wind speed and airy wave model)and is tested using random loads(RL)case(including Kaimal wind model and JONSWAP wave theory).The superiority of this method is assessed by applying the deterministic method for damage identification.The results demonstrate that the proposed non-probabilistic method identifies the location and severity of damage more accurately compared to a deterministic one.This superiority is getting more remarkable as the difference in uncertainty levels between training and testing data is increasing.

关 键 词：Damage identification Floating wind turbine Artificial neural networks Non-probabilistic method UNCERTAINTIES 

分 类 号：TM315[电气工程—电机]