scholarly journals Intelligent Fault Diagnosis Techniques Applied to an Offshore Wind Turbine System

2019 ◽  
Vol 9 (4) ◽  
pp. 783 ◽  
Author(s):  
Silvio Simani ◽  
Paolo Castaldi
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Operating Conditions ◽  
Fault Detection And Isolation ◽  
Offshore Wind ◽  
Data Driven ◽  
Offshore Wind Turbine ◽  
Wind Turbine System ◽  
High Degree ◽  
Offshore Plants

Fault diagnosis of wind turbine systems is a challenging process, especially for offshore plants, and the search for solutions motivates the research discussed in this paper. In fact, these systems must have a high degree of reliability and availability to remain functional in specified operating conditions without needing expensive maintenance works. Especially for offshore plants, a clear conflict exists between ensuring a high degree of availability and reducing costly maintenance. Therefore, this paper presents viable fault detection and isolation techniques applied to a wind turbine system. The design of the so-called fault indicator relies on an estimate of the fault using data-driven methods and effective tools for managing partial knowledge of system dynamics, as well as noise and disturbance effects. In particular, the suggested data-driven strategies exploit fuzzy systems and neural networks that are used to determine nonlinear links between measurements and faults. The selected architectures are based on nonlinear autoregressive with exogenous input prototypes, which approximate dynamic relations with arbitrary accuracy. The designed fault diagnosis schemes were verified and validated using a high-fidelity simulator that describes the normal and faulty behavior of a realistic offshore wind turbine plant. Finally, by accounting for the uncertainty and disturbance in the wind turbine simulator, a hardware-in-the-loop test rig was used to assess the proposed methods for robustness and reliability. These aspects are fundamental when the developed fault diagnosis methods are applied to real offshore wind turbines.

scholarly journals Intelligent Fault Diagnosis Techniques Applied to an Offshore Wind Turbine System **

2018 ◽  
Author(s):  
Silvio Simani ◽  
Paolo Castaldi
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Fault Detection And Isolation ◽  
Offshore Wind ◽  
Data Driven ◽  
Offshore Wind Turbine ◽  
Isolation Techniques ◽  
Wind Turbine System ◽  
Offshore Installations ◽  
Fault Indicator

The fault diagnosis of wind turbine systems represent a challenging issue, especially for offshore installations, thus justifying the research topics developed in this work. Therefore, this paper addresses the problem of the fault diagnosis of wind turbines, and it present viable solutions of fault detection and isolation techniques. The design of the so--called fault indicator consists of its estimate, which involves data--driven methods, as they result effective tools for managing partial analytical knowledge of the system dynamics, together with noise and disturbance effects. In particular, the suggested data--driven strategies exploit fuzzy systems and neural networks that are employed to determine nonlinear links between measurements and faults. The selected architectures are based on nonlinear autoregressive with exogenous input prototypes, as they approximate the dynamic evolution of the system along time. The designed fault diagnosis schemes are verified via a high--fidelity simulator, which describes the normal and the faulty behaviour of an offshore wind turbine plant. Finally, by taking into account the presence of uncertainty and disturbance implemented in the wind turbine simulator, the robustness and the reliability features of the proposed methods are also assessed. This aspect is fundamental when the proposed fault diagnosis methods have to be applied to offshore installations.

scholarly journals Improving the Strategy of Maintaining Offshore Wind Turbines through Petri Net Modelling

2021 ◽  
Vol 11 (2) ◽  
pp. 574
Author(s):  
Rundong Yan ◽  
Sarah Dunnett
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Petri Net ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Maintenance Costs ◽  
Offshore Wind Turbines ◽  
Major Repair ◽  
Wind Turbine System ◽  
Periodic Maintenance

In order to improve the operation and maintenance (O&M) of offshore wind turbines, a new Petri net (PN)-based offshore wind turbine maintenance model is developed in this paper to simulate the O&M activities in an offshore wind farm. With the aid of the PN model developed, three new potential wind turbine maintenance strategies are studied. They are (1) carrying out periodic maintenance of the wind turbine components at different frequencies according to their specific reliability features; (2) conducting a full inspection of the entire wind turbine system following a major repair; and (3) equipping the wind turbine with a condition monitoring system (CMS) that has powerful fault detection capability. From the research results, it is found that periodic maintenance is essential, but in order to ensure that the turbine is operated economically, this maintenance needs to be carried out at an optimal frequency. Conducting a full inspection of the entire wind turbine system following a major repair enables efficient utilisation of the maintenance resources. If periodic maintenance is performed infrequently, this measure leads to less unexpected shutdowns, lower downtime, and lower maintenance costs. It has been shown that to install the wind turbine with a CMS is helpful to relieve the burden of periodic maintenance. Moreover, the higher the quality of the CMS, the more the downtime and maintenance costs can be reduced. However, the cost of the CMS needs to be considered, as a high cost may make the operation of the offshore wind turbine uneconomical.

Study on the Dynamic Response for Floating Foundation of Offshore Wind Turbine

2011 ◽  
Author(s):  
Yougang Tang ◽  
Jun Hu ◽  
Liqin Liu
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Dynamic Responses ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Wave Load ◽  
Mooring Lines ◽  
Floating Foundation ◽  
Wind Turbine System ◽  
Sea Area

The wind resources for ocean power generation are mostly distributed in sea areas with the distance of 5–50km from coastline, whose water depth are generally over 20m. To improve ocean power output and economic benefit of offshore wind farm, it is necessary to choose floating foundation for offshore wind turbine. According to the basic data of a 600kW wind turbine with a horizontal shaft, the tower, semi-submersible foundation and mooring system are designed in the 60-meter-deep sea area. Precise finite element models of the floating wind turbine system are established, including mooring lines, floating foundation, tower and wind turbine. Dynamic responses for the floating foundation of offshore wind turbine are investigated under wave load in frequency domain.

scholarly journals Support condition monitoring of offshore wind turbines using model updating techniques

2019 ◽  
Vol 19 (4) ◽  
pp. 1017-1031 ◽  
Author(s):  
Ying Xu ◽  
George Nikitas ◽  
Tong Zhang ◽  
Qinghua Han ◽  
Marios Chryssanthopoulos ◽  
...  
Keyword(s):  
Finite Element ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Model Updating ◽  
Element Model ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Support Condition ◽  
Offshore Wind Turbines ◽  
Wind Turbine System

The offshore wind turbines are dynamically sensitive, whose fundamental frequency can be very close to the forcing frequencies activated by the environmental and turbine loads. Minor changes of support conditions may lead to the shift of natural frequencies, and this could be disastrous if resonance happens. To monitor the support conditions and thus to enhance the safety of offshore wind turbines, a model updating method is developed in this study. A hybrid sensing system was fabricated and set up in the laboratory to investigate the long-term dynamic behaviour of the offshore wind turbine system with monopile foundation in sandy deposits. A finite element model was constructed to simulate structural behaviours of the offshore wind turbine system. Distributed nonlinear springs and a roller boundary condition are used to model the soil–structure interaction properties. The finite element model and the test results were used to analyse the variation of the support condition of the monopile, through an finite element model updating process using estimation of distribution algorithms. The results show that the fundamental frequency of the test model increases after a period under cyclic loading, which is attributed to the compaction of the surrounding sand instead of local damage of the structure. The hybrid sensing system is reliable to detect both the acceleration and strain responses of the offshore wind turbine model and can be potentially applied to the remote monitoring of real offshore wind turbines. The estimation of distribution algorithm–based model updating technique is demonstrated to be successful for the support condition monitoring of the offshore wind turbine system, which is potentially useful for other model updating and condition monitoring applications.

scholarly journals Spoke Dimension on the Motion Performance of a Floating Wind Turbine with Tension-Leg Platform

2016 ◽  
Vol 2016 ◽  
pp. 1-16
Author(s):  
H. F. Wang ◽  
Y. H. Fan
Keyword(s):  
Wind Turbine ◽  
Good Choice ◽  
Offshore Wind ◽  
Experimental Result ◽  
Offshore Wind Turbine ◽  
Tension Leg Platform ◽  
Irregular Wave ◽  
Wind Turbine System ◽  
Floating Offshore Wind Turbines ◽  
Tower Structure

The tension-leg platform (TLP) supporting structure is a good choice for floating offshore wind turbines because TLP has superior motion dynamics. This study investigates the effects of TLP spoke dimensions on the motion of a floating offshore wind turbine system (FOWT). Spoke dimension and offshore floating TLP were subjected to irregular wave and wind excitation to evaluate the motion of the FOWT. This research has been divided into two parts: (1) Five models were designed based on different spoke dimensions, and aerohydroservo-elastic coupled analyses were conducted on the models using the finite element method. (2) Considering the coupled effects of the dynamic response of a top wind turbine, a supporting-tower structure, a mooring system, and two models on a reduced scale of 1 : 80 were constructed and experimentally tested under different conditions. Numerical and experimental results demonstrate that the spoke dimensions have a significant effect on the motion of FOWT and the experimental result that spoke dimension can reduce surge platform movement to improve turbine performance.

Research on the Dynamic Response of Floating Foundation of a Tri-Floater Offshore Wind Turbine

2013 ◽  
Vol 275-277 ◽  
pp. 852-855 ◽  
Author(s):  
Zhuang Le Yao ◽  
Chao He Chen ◽  
Yuan Ming Chen
Keyword(s):  
Wind Turbine ◽  
Transfer Functions ◽  
Reference Value ◽  
Element Model ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Wave Load ◽  
Floating Foundation ◽  
Wind Turbine System ◽  
Offshore Wind Industry

In this paper, the overall finite element model is established, to analyze the small-sized floating foundation of a tri-floater and to make a local optimization on the stress concentration area. The transfer functions and the response spectrums of wave load and motion of floating wind turbine system are calculated by AQWA. Besides the concept of the floating foundation group is put forward in this paper. It is small in structure, easy to assemble, and it can be developed for any power of wind field.This concept has a certain reference value for the development of offshore wind industry in China.

scholarly journals Data–Driven Techniques for the Fault Diagnosis of a Wind Turbine Benchmark

2018 ◽  
Vol 28 (2) ◽  
pp. 247-268 ◽  
Author(s):  
Silvio Simani ◽  
Saverio Farsoni ◽  
Paolo Castaldi
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Monte Carlo Analysis ◽  
Fault Detection And Isolation ◽  
Data Driven ◽  
Parameter Uncertainties ◽  
Strongly Nonlinear ◽  
Fault Indicator ◽  
Typical Parameter ◽  
Nonlinear Autoregressive

Abstract This paper deals with the fault diagnosis of wind turbines and investigates viable solutions to the problem of earlier fault detection and isolation. The design of the fault indicator, i.e., the fault estimate, involves data-driven approaches, as they can represent effective tools for coping with poor analytical knowledge of the system dynamics, together with noise and disturbances. In particular, the proposed data-driven solutions rely on fuzzy systems and neural networks that are used to describe the strongly nonlinear relationships between measurement and faults. The chosen architectures rely on nonlinear autoregressive models with exogenous input, as they can represent the dynamic evolution of the system along time. The developed fault diagnosis schemes are tested by means of a high-fidelity benchmark model that simulates the normal and the faulty behaviour of a wind turbine. The achieved performances are also compared with those of other model-based strategies from the related literature. Finally, a Monte-Carlo analysis validates the robustness and the reliability of the proposed solutions against typical parameter uncertainties and disturbances.

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