Add to ORKGArtificial intellegence (AI) techniques have proved their ability in detection of incipient faults in electrical machines. in this project, the fault diagnosis of three phase induction motors is studied detailed in unbalance voltage and stator inter turn fault using simulation models and neural networks have been used to train the data using Radial Basis Function Neural Network (RBFNN) in MATLAB with Graphical USer Interface Development Environment (GUIDE) structured
This paper presents a review of the most recent developments in the field of diagnosis of electrical...
This work studied the use of neural networks for model based fault diagnostics of induction motors. ...
Abstract: Faults in induction motors may cause a system to fail. Hence it is necessary to detect and...
Artificial intelligence (AI) techniques have proved their ability in detection of incipient faults i...
This article presents a method for fault detection and diagnosis of stator inter-turn short circuit ...
Induction motor is one of the most important motors used in industrial applications. The operating c...
This paper describes an Artificial Neural Network (ANN) based fault diagnosis methodology for Induct...
In induction machine a number of faults occur namely bearing and insulation related faults, stator w...
Induction motors constitute the largest proportion of motors in industry. This type of motor experie...
The intention of fault detection is to detect the fault at the beginning stage and shut off the mach...
Motivated by the superior performances of neural networks and neuro-fuzzy approaches to fault detect...
This project creates and develops an artificial neural network that is capable to determine the cond...
The paper deals with the analysis of an Artificial Neural Network (ANN) approach suitable for on - l...
This paper proposes the possibility of developing incipient fault diagnosis and remedial operating s...
This paper presents a high accuracy detection of Broken Rotor Bar (BRB) fault by Artificial Neural N...
This paper presents a review of the most recent developments in the field of diagnosis of electrical...
This work studied the use of neural networks for model based fault diagnostics of induction motors. ...
Abstract: Faults in induction motors may cause a system to fail. Hence it is necessary to detect and...
Artificial intelligence (AI) techniques have proved their ability in detection of incipient faults i...
This article presents a method for fault detection and diagnosis of stator inter-turn short circuit ...
Induction motor is one of the most important motors used in industrial applications. The operating c...
This paper describes an Artificial Neural Network (ANN) based fault diagnosis methodology for Induct...
In induction machine a number of faults occur namely bearing and insulation related faults, stator w...
Induction motors constitute the largest proportion of motors in industry. This type of motor experie...
The intention of fault detection is to detect the fault at the beginning stage and shut off the mach...
Motivated by the superior performances of neural networks and neuro-fuzzy approaches to fault detect...
This project creates and develops an artificial neural network that is capable to determine the cond...
The paper deals with the analysis of an Artificial Neural Network (ANN) approach suitable for on - l...
This paper proposes the possibility of developing incipient fault diagnosis and remedial operating s...
This paper presents a high accuracy detection of Broken Rotor Bar (BRB) fault by Artificial Neural N...
This paper presents a review of the most recent developments in the field of diagnosis of electrical...
This work studied the use of neural networks for model based fault diagnostics of induction motors. ...
Abstract: Faults in induction motors may cause a system to fail. Hence it is necessary to detect and...