Sliding Mode Observer-Based Fault Detection and Isolation Approach for a Wind Turbine Benchmark

Borja-Jaimes, Vicente; Medina, Manuel Adam; López-Zapata, B.; Valdés, Luis Gerardo Vela; Pachecano, Luisana Claudio; Coronado, Eduardo Mael Sánchez

doi:10.3390/pr10010054

Cited by 13 publications

(13 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…LsLr is the Blondel coefficient, and the relationship γ = 3 2 p J Lm σLsLr is used to simplify the writing of the equation (33). The transmission ratio that exists between the gearbox and the spur gears connecting the wind turbine blades i g = i gp i gs .…”

Section: A Pitch System Modelmentioning

confidence: 99%

Fault Diagnosis for Takagi-Sugeno Model Wind Turbine Pitch System

Rodríguez,

Hernández-De-León,

Marín

et al. 2024

IEEE Access

Self Cite

View full text Add to dashboard Cite

This paper presents a fault diagnosis (FDD) approach based on a Takagi-Sugeno Unknown Input Observer (TS-UIO) that allows for estimation of the states of an active pitch system for a studied wind turbine even in the presence of unknown interference factors. A scheme for FDD is proposed based on the residuals evaluation between the non-linear model of the active pitch system and the Takagi-Sugeno unknown input observer proposed for the detection and isolation of faults in sensors with measurable premise variables. The proposed TS-UIO State Observer is resilient to disturbances and measurement noise due to its unique feature of decoupling unknown inputs, interruptions or undefined factors that affect the behavior of the system under study. This study investigates the effect of load-induced stress on the mechanical blades of a wind turbine, caused by the wind force considered as an unknown disturbance or input to the system given its dependence on weather conditions. The proposed FDD algorithm includes Linear Matrix Inequalities (LMI) ensuring the estimation error dynamics approximates to zero. Successful implementation tests are demonstrated in an active pitch system with reference parameters based on a wind turbine model. The review outlines traditional FDD approaches, including those based on nonlinear models, as well as relatively new methods based on linear sector conditions. Special attention is given to Takagi-Sugeno (TS) methods.

show abstract

Section: A Pitch System Modelmentioning

confidence: 99%

Fault Diagnosis for Takagi-Sugeno Model Wind Turbine Pitch System

Rodríguez,

Hernández-De-León,

Marín

et al. 2024

IEEE Access

Self Cite

View full text Add to dashboard Cite

show abstract

“…The proposed scheme uses an adaptive SMO to accurately estimate both system states and disturbances as part of an active FTC system. An FDI scheme using SMOs is designed in [28]. The SMOs are combined with a residual signal generator for detecting sensor faults in both the pitch and drive train systems in a wind turbine benchmark model.…”

Section: Introductionmentioning

confidence: 99%

Actuator FDI Scheme for a Wind Turbine Benchmark Using Sliding Mode Observers

Borja-Jaimes,

Adam-Medina,

García-Morales

et al. 2023

Processes

Self Cite

View full text Add to dashboard Cite

This paper proposes a fault detection and isolation (FDI) scheme for a wind turbines subject to actuator faults in both the pitch system and the drive train system. The proposed scheme addresses fault detection and isolation problems using a fault estimation approach. The proposed approach considers the use of a particular class of sliding mode observers (SMOs) designed to maintain the sliding motion even in the presence of actuator faults. The fault detection problem is solved by reconstructing the actuator faults through an appropriate analysis of the nonlinear output error injection signal, which is required to keep the SMO in a sliding motion. To ensure accurate fault reconstruction, only two conditions are required, namely that the faults are bounded and they meet the matching condition. A scheme based on a bank of SMOs is proposed to solve the fault detection and isolation problem in the pitch system. For the drive train system, a scheme using only one SMO is proposed. The performance of the proposed FDI scheme is validated by using a wind turbine benchmark model subjected to several actuator faults. Normalized root mean square error (NRMSE) analysis is performed to evaluate the accuracy of the actuator fault estimations.

show abstract

“…Different researches and studies have been proposed to deal with the diagnosis task of wind turbines using several approaches [3,[5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. These proposed methodologies adopt distinctive design of schemes, resulting in different properties according to the used techniques.…”

Section: Introductionmentioning

confidence: 99%

“…Then a crisp logic technique is used to classify actuator and sensor faults. Authors in [13], have presented a fault detection and isolation strategy for WT benchmark using a sliding mode observer for different faults. In the paper [14], an SVM method is combined with model-based observer for detecting sensors and actuators faults in a wind turbine benchmark.…”

Section: Introductionmentioning

confidence: 99%

Fault diagnosis-based observers using Kalman filters and Luenberger estimators: Application to the pitch system fault actuators

Zemali¹,

Cherroun²,

Hadroug³

et al. 2023

Diagnostyka

View full text Add to dashboard Cite

This paper aims to present a robust fault diagnosis structure-based observers for actuator faults in the pitch part system of the wind turbine benchmark. In this work, two linear estimators have been proposed and investigated: the Kalman filter and the Luenberger estimator for observing the output states of the pitch system in order to generate the appropriate residual between the measured positions of blades and the estimated values. An inference step as a decision block is employed to decide the existence of faults in the process, and to classify the detected faults using a predetermined threshold defined by upper and lower limits. All actuator faults in the pitch system of the horizontal wind turbine benchmark are studied and investigated. The obtained simulation results show the ability of the proposed diagnosis system to determine effectively the occurred faults in the pitch system. Estimation of the output variables is effectively realized in both situations: without and with the occurrence of faults in the studied process. A comparison between the two used observers is demonstrated.

show abstract

Sliding Mode Observer-Based Fault Detection and Isolation Approach for a Wind Turbine Benchmark

Cited by 13 publications

References 31 publications

Fault Diagnosis for Takagi-Sugeno Model Wind Turbine Pitch System

Fault Diagnosis for Takagi-Sugeno Model Wind Turbine Pitch System

Actuator FDI Scheme for a Wind Turbine Benchmark Using Sliding Mode Observers

Fault diagnosis-based observers using Kalman filters and Luenberger estimators: Application to the pitch system fault actuators

Contact Info

Product

Resources

About