A Multy Layer Perceptron Neural Network able to recognize inter-turn short-circuits in the stator of induction machines is presented. The network is inserted in an on-line diagnostic system which utilizes the machine voltages and currents as input signals. The current computed by a faulted machine models are analyzed with the aim to evidence the variables more suitable to characterize the short circuit's effects. These variables, properly normalized, are the input data sets for the learning process of the network, which is therefore applicable to a class of induction machines
This paper presents a fault diagnosis and classification scheme for induction machines by using moto...
This paper presents a fault diagnosis and classification scheme for induction machin...
Electrical winding faults, namely stator short-circuits and rotor bar damage, in total constitute ar...
A Multy Layer Perceptron Neural Network able to recognize inter-turn short-circuits in the stator of...
A Multy Layer Perceptron Neural Network able to recognize inter-turn short-circuits in the stator of...
An improvement of induction machine rotor fault diagnosis based on a neural network approach is pres...
Fault detection and diagnosis is currently a very important problem in induction machine management....
Fault detection and diagnosis is currently a very important problem in induction machine management....
The paper deals with the analysis of an Artificial Neural Network (ANN) approach suitable for on - l...
The paper presents the possibility of using neural networks in the detection of stator and rotor ele...
The benefits of machine condition monitoring have been widely recognized as superior with respect to...
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...
This paper presents a neural network that is able to give, together with the rotor fault diagnosis, ...
Due to the fact that inter-turn short-circuits are the ones of the most common causes of damage to s...
This paper presents a fault diagnosis and classification scheme for induction machines by using moto...
This paper presents a fault diagnosis and classification scheme for induction machin...
Electrical winding faults, namely stator short-circuits and rotor bar damage, in total constitute ar...
A Multy Layer Perceptron Neural Network able to recognize inter-turn short-circuits in the stator of...
A Multy Layer Perceptron Neural Network able to recognize inter-turn short-circuits in the stator of...
An improvement of induction machine rotor fault diagnosis based on a neural network approach is pres...
Fault detection and diagnosis is currently a very important problem in induction machine management....
Fault detection and diagnosis is currently a very important problem in induction machine management....
The paper deals with the analysis of an Artificial Neural Network (ANN) approach suitable for on - l...
The paper presents the possibility of using neural networks in the detection of stator and rotor ele...
The benefits of machine condition monitoring have been widely recognized as superior with respect to...
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...
This paper presents a neural network that is able to give, together with the rotor fault diagnosis, ...
Due to the fact that inter-turn short-circuits are the ones of the most common causes of damage to s...
This paper presents a fault diagnosis and classification scheme for induction machines by using moto...
This paper presents a fault diagnosis and classification scheme for induction machin...
Electrical winding faults, namely stator short-circuits and rotor bar damage, in total constitute ar...