An adaptive inverse-QR recursive Levenberg-Marquardt algorithm

Nakornphanom, Kodchakorn Na; Sitjongsataporn, Suchada

doi:10.1109/iscit.2013.6645916

Cited by 1 publication

(2 citation statements)

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“…Referring to [17], [19], can be rewritten with the recursive algorithm as: (9) Now a general recursive algorithm to update the parameter vector , by comparing the offline algorithm described in [12], [17], [24] with the recursive version in Equations (5) and (9), can be defined by (10) where the matrix modifies the local search direction defined with the method of the gradient .…”

Section: Proposed Identification Methodsmentioning

confidence: 99%

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On -Line Stator Winding Inter -Turn Short -Circuits Detection in Induction Motors Using Recursive Levenberg -Marquardt Algorithm

Kouadri¹

2017

ijeei

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Within the framework of the diagnosis of the stator windings faults, the authors propose in this paper a recursive diagnosis method for on-line detection and location of an inter-turn short-circuit by parameters identification. This approach based on the Recursive Levenberg-Marquardt (RLM) algorithm is used for the minimization of the objective function represented by the quadratic criterion obtained by the difference between the real outputs and their estimations. Tests and validations of failure detection by parameter identification require a model suited for fault modelling. For this purpose, a faulty induction motor model is proposed. Electric parameters of this model as well as fault parameters are estimated by RLM adaptive algorithm through an output-error technique. Because the parameters values of this model present magnitude order very different, the normalization of these parameters is proposed in order to obtain the sensitivity functions with the same magnitude order. The estimation results, which used simulated data, are presented to show the effectiveness and the advantage of the proposed approach for use in real-time stator faults diagnosis.

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Section: Proposed Identification Methodsmentioning

confidence: 99%

“…The RLM method was proposed and successfully applied to various fields [17], [18], [19]. In [17], RLM algorithm has been presented for on-line training of neural nets for nonlinear adaptive filtering.…”

Section: Introductionmentioning

confidence: 99%

On -Line Stator Winding Inter -Turn Short -Circuits Detection in Induction Motors Using Recursive Levenberg -Marquardt Algorithm

Kouadri¹

2017

ijeei

View full text Add to dashboard Cite

show abstract

An adaptive inverse-QR recursive Levenberg-Marquardt algorithm

Cited by 1 publication

References 10 publications

On -Line Stator Winding Inter -Turn Short -Circuits Detection in Induction Motors Using Recursive Levenberg -Marquardt Algorithm

On -Line Stator Winding Inter -Turn Short -Circuits Detection in Induction Motors Using Recursive Levenberg -Marquardt Algorithm

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