Data-Driven Multimode Fault Detection for Wind Energy Conversion Systems

Haghani, Adel; Krueger, Minjia; Jeinsch, Torsten; Ding, Steven X.; Engel, Peter

doi:10.1016/j.ifacol.2015.09.597

Cited by 14 publications

(8 citation statements)

References 24 publications

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“…The residual is of the form r 6 (t) = Y 6 (t)v (6), where v(6) ∈ ker(P 6 (t)). It can be shown that Equation (13) for the second fault has not a solution. The third fault yields the following model:…”

Section: Practical Examplementioning

confidence: 99%

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Nonparametric methods for fault diagnosis in dynamic systems

Zhirabok

Shumsky

Scherbatyuk

2018

Intl J Robust & Nonlinear

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Summary The problem of fault diagnosis in engineering systems with uncertainties described by nonlinear discrete‐time models is studied within the scope of analytical redundancy concept. Solution of the problem assumes the checking redundancy relations existing among system inputs and outputs measured over a finite time window. The nonparametric method is used to construct redundancy relations involving transformation of the initial system model into canonical form with special properties. The obtained results are illustrated by the general electric servoactuator of manipulation robots.

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Section: Practical Examplementioning

confidence: 99%

“…12 Among the active approaches, there exists the method considered in other works. 7,10,13,14 The feature of this method is that knowledge of some system parameters is not required for redundancy relations checking. Therefore, this method can be called as the nonparametric one.…”

Section: Introductionmentioning

confidence: 99%

Nonparametric methods for fault diagnosis in dynamic systems

Zhirabok

Shumsky

Scherbatyuk

2018

Intl J Robust & Nonlinear

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show abstract

“…In the literature, FD methodologies can be classified as model‐based and data‐driven approaches. Data‐driven methods rely on the availability of a large amount of historical data with full fault scenarios . This latter is then transformed and presented as a priori knowledge to a diagnostic system using different approaches such as statistical analysis and Hilbert spectral analysis …”

Section: Introductionmentioning

confidence: 99%

Fractional‐order fault‐tolerant pitch control design for a 2.5 MW wind turbine subject to actuator faults

Noshirvani

Askari

Fekih

2019

Struct Control Health Monit

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Summary This paper proposes an active fault‐tolerant pitch control design for a 2.5 MW wind turbine. The proposed scheme combines the robustness properties of fractional‐order terminal sliding mode control with the accurate estimation of virtual actuators. Its main objective is to enable the wind turbine to retain its nominal pitching performance under faulty conditions whereas simultaneously attenuating chattering. The fault detection scheme implements a bank of modified unscented Kalman filters. The proposed approach was implemented to a 2.5‐MW wind turbine subject to pitch actuator faults and sensor noise. Its performance was compared with that of an integer‐order terminal sliding mode approach. Guaranteeing the finite time stability of the pitching system under faulty conditions whereas alleviating the chattering phenomena are among the positive features of the proposed fractional‐order fault‐tolerant pitch control design.

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“…It is common practice to distinguish active and passive approaches to solve this problem. Among the active approaches, there exists the method considered in [8][9][10][11][12]. The feature of this method is that knowledge of some system parameters values is not required for redundancy relations checking.…”

Section: Introductionmentioning

confidence: 99%

“…The feature of the solution obtained in [8][9][10] is that to check the redundancy relations, it is necessary to find a kernel of some matrix of functionals which is constructed on-line by processing the system inputs and outputs measured over a finite time window.…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis in Circuits and Systems by Nonparametric Methods

Zhirabok¹,

Shumsky²

2018

World Congress on Electrical Engineering and Computer Systems and Science

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The problem of fault diagnosis in engineering systems with uncertainties described by nonlinear discrete-time models is studied within the scope of analytical redundancy concept. Solution of the problem assumes the checking redundancy relations existing among system inputs and outputs measured over a finite time window. The nonparametric method is used to construct redundancy relations involving transformation of the initial system model into canonical form with special properties. The obtained results are illustrated by the general electric servoactuator of manipulation robots.

show abstract

Data-Driven Multimode Fault Detection for Wind Energy Conversion Systems

Cited by 14 publications

References 24 publications

Nonparametric methods for fault diagnosis in dynamic systems

Nonparametric methods for fault diagnosis in dynamic systems

Fractional‐order fault‐tolerant pitch control design for a 2.5 MW wind turbine subject to actuator faults

Fault Diagnosis in Circuits and Systems by Nonparametric Methods

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