DC Fault Analysis and Transient Average Current Based Fault Detection for Radial MTDC System

This paper proposes a new method of motor fault detection. ML Estimation is proposed as a key technique for signal processing. The stator current is used data for motor fault analysis. ML Estimation is generally applied to estimate signals for nonlinear model. The expectation is that the method can provide information for fault analysis. The method is tested on 3 different motor conditions: healthy, stator fault, and rotor fault motor at full load condition. Based on experiments, the method can differentiate conditions clearly and be also able to measure fault severity levels.

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Recursive Least Squares Parameter Estimation for DC Fault Detection and Localization

2019 IEEE National Aerospace and Electronics Conference (NAECON) ◽

10.1109/naecon46414.2019.9057890 ◽

2019 ◽

Author(s):

Kellen O'Shea ◽

Bang-Hung Tsao ◽

Luis Herrera ◽

Chad Miller

Keyword(s):

Parameter Estimation ◽

Fault Detection ◽

Least Squares ◽

Recursive Least Squares ◽

Dc Fault ◽

Detection And Localization

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DC side line-to-line fault analysis of VSC-HVDC and DC-fault-clearing methods

2015 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT) ◽

10.1109/drpt.2015.7432647 ◽

2015 ◽

Cited By ~ 3

Author(s):

Danhua Liu ◽

Tongzhen Wei ◽

Qunhai Huo ◽

Lixin Wu

Keyword(s):

Fault Analysis ◽

Dc Fault

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Induction Motors Stator Fault Analysis based on Artificial Intelligence

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v2.i1.pp69-78 ◽

2016 ◽

Vol 2 (1) ◽

pp. 69 ◽

Cited By ~ 4

Author(s):

Hussein Taha Hussein ◽

Mohamed Ammar ◽

Mohamed Moustafa Hassan

Keyword(s):

Artificial Intelligence ◽

Fault Detection ◽

Short Circuit ◽

Fault Analysis ◽

Fault Detection And Diagnosis ◽

Neuro Fuzzy ◽

Detection Approach ◽

Three Phase ◽

Detection And Diagnosis ◽

Stator Fault

This article presents a method for fault detection and diagnosis of stator inter-turn short circuit in three phase induction machines. The technique is based on the stator current and modelling in the dq frame using an Adaptive Neuro-Fuzzy artificial intelligence approach. The developed fault analysis method is illustrated using MATLAB simulations. The obtained results are promising based on the new fault detection approach.

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