Active FTC for hydraulic pitch system for an off-shore wind turbine

Chen, Lejun; Shi, Fengming; Patton, Ron J.

doi:10.1109/systol.2013.6693892

Cited by 25 publications

(19 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The hydraulic system suffers various faults, such as oil leakage and sliding valve blockage [48]. These faults can be diagnosed by using signals acquired from pressure and level sensors.…”

Section: E Hydraulic Systemmentioning

confidence: 99%

A Survey on Wind Turbine Condition Monitoring and Fault Diagnosis—Part I: Components and Subsystems

Wang

2015

IEEE Trans. Ind. Electron.

451

197

View full text Add to dashboard Cite

This paper provides a comprehensive survey on the state-of-the-art condition monitoring and fault diagnostic technologies for wind turbines. The Part I of this survey briefly reviews the existing literature surveys on the subject, discusses the common failure modes in the major wind turbine components and subsystems, briefly reviews the condition monitoring and fault diagnostic techniques for these components and subsystems, and specifically discusses the issues of condition monitoring and fault diagnosis for offshore wind turbines.

show abstract

“…The hydraulic system suffers various faults, such as oil leakage and sliding valve blockage [48]. These faults can be diagnosed by using signals acquired from pressure and level sensors.…”

Section: E Hydraulic Systemmentioning

confidence: 99%

A Survey on Wind Turbine Condition Monitoring and Fault Diagnosis—Part I: Components and Subsystems

Wang

2015

IEEE Trans. Ind. Electron.

451

197

View full text Add to dashboard Cite

show abstract

“…Faults in the pitch position measurement (pitch position sensor fault) are also considered. This is one of the most important failure modes found on actual systems [24,25]. The origin of these faults is either electrical or mechanical, and it can result in a fixed value (faults 6 and 7) on the measurements.…”

Section: Sensor Faultsmentioning

confidence: 99%

Wind Turbine Condition Monitoring Strategy through Multiway PCA and Multivariate Inference

2018

View full text Add to dashboard Cite

This article states a condition monitoring strategy for wind turbines using a statistical data-driven modeling approach by means of supervisory control and data acquisition (SCADA) data. Initially, a baseline data-based model is obtained from the healthy wind turbine by means of multiway principal component analysis (MPCA). Then, when the wind turbine is monitorized, new data is acquired and projected into the baseline MPCA model space. The acquired SCADA data are treated as a random process given the random nature of the turbulent wind. The objective is to decide if the multivariate distribution that is obtained from the wind turbine to be analyzed (healthy or not) is related to the baseline one. To achieve this goal, a test for the equality of population means is performed. Finally, the results of the test can determine that the hypothesis is rejected (and the wind turbine is faulty) or that there is no evidence to suggest that the two means are different, so the wind turbine can be considered as healthy. The methodology is evaluated on a wind turbine fault detection benchmark that uses a 5 MW high-fidelity wind turbine model and a set of eight realistic fault scenarios. It is noteworthy that the results, for the presented methodology, show that for a wide range of significance, α ∈ [1%, 13%], the percentage of correct decisions is kept at 100%; thus it is a promising tool for real-time wind turbine condition monitoring.

show abstract

“…Hence, the pitch system can be described according to the so-called fault effectiveness parameter ∈ [0 1], where = 0 corresponds to a faultfree actuator with = 0 and = 0 = 1 relates to a full fault on the actuator with = , = . Hence, the corresponding damping ratio and damping frequency can be obtained by inverse formula and and can be depicted by the pitch actuator fault [10,11]:…”

Section: Complexitymentioning

confidence: 99%

Active Fault-Tolerant Control for Wind Turbine with Simultaneous Actuator and Sensor Faults

et al. 2017

View full text Add to dashboard Cite

The purpose of this paper is to show a novel fault-tolerant tracking control (FTC) strategy with robust fault estimation and compensating for simultaneous actuator sensor faults. Based on the framework of fault-tolerant control, developing an FTC design method for wind turbines is a challenge and, thus, they can tolerate simultaneous pitch actuator and pitch sensor faults having bounded first time derivatives. The paper’s key contribution is proposing a descriptor sliding mode method, in which for establishing a novel augmented descriptor system, with which we can estimate the state of system and reconstruct fault by designing descriptor sliding mode observer, the paper introduces an auxiliary descriptor state vector composed by a system state vector, actuator fault vector, and sensor fault vector. By the optimized method of LMI, the conditions for stability that estimated error dynamics are set up to promote the determination of the parameters designed. With this estimation, and designing a fault-tolerant controller, the system’s stability can be maintained. The effectiveness of the design strategy is verified by implementing the controller in the National Renewable Energy Laboratory’s 5-MW nonlinear, high-fidelity wind turbine model (FAST) and simulating it in MATLAB/Simulink.

show abstract

Active FTC for hydraulic pitch system for an off-shore wind turbine

Cited by 25 publications

References 13 publications

A Survey on Wind Turbine Condition Monitoring and Fault Diagnosis—Part I: Components and Subsystems

A Survey on Wind Turbine Condition Monitoring and Fault Diagnosis—Part I: Components and Subsystems

Wind Turbine Condition Monitoring Strategy through Multiway PCA and Multivariate Inference

Active Fault-Tolerant Control for Wind Turbine with Simultaneous Actuator and Sensor Faults

Contact Info

Product

Resources

About