Wavelet Neural Network-Based Diagnosis and Protection of Inverter Faults in Induction Motor Drives

نویسندگان

  • M. A. S. K. Khan
  • M. A. Rahman
چکیده

In this paper, a wavelet neural network (WNN) based diagnostic algorithm is developed and implemented in real-time for the identification and detection of inverter faults in the vector controlled induction motor drives. The phase currents of an induction motor (IM) drive of different faulted and unfaulted conditions are preprocessed by the wavelet packet transform (WPT) algorithm in order to minimize the structure and timing of the proposed diagnostic technique using the WNN algorithm. The WPT coefficients are used as the inputs of a three-layer WNN. The performance of the proposed diagnosis scheme is evaluated by simulation and experimental results. The proposed technique is evaluated and tested on-line for a laboratory 1-hp IM motor drive using the ds1102 digital signal processor (DSP) board. In all the tests carried out, the type of fault is identified promptly and properly, and the tripping action is initiated almost at the instant or within one cycle of the fault occurrence.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

AN INTELLIGENT FAULT DIAGNOSIS APPROACH FOR GEARS AND BEARINGS BASED ON WAVELET TRANSFORM AS A PREPROCESSOR AND ARTIFICIAL NEURAL NETWORKS

In this paper, a fault diagnosis system based on discrete wavelet transform (DWT) and artificial neural networks (ANNs) is designed to diagnose different types of fault in gears and bearings. DWT is an advanced signal-processing technique for fault detection and identification. Five features of wavelet transform RMS, crest factor, kurtosis, standard deviation and skewness of discrete wavelet co...

متن کامل

Comparison of MRAS Based Rotor Resistance Estimator Using Reactive Power and Flux Based Techniques for Space Vector PWM Inverter Fed Induction Motor Drives

The performance of Vector Controlled Induction Motor drive depends on the accuracy of rotor resistance which will vary with temperature and frequency. The MRAS approach using reactive power and flux as a state variable for rotor resistance estimation makes MRAS computationally simpler and easy to design. In this paper, Rotor Flux based MRAS (RF-MRAS) and Reactive Power based MRAS (RP-MRAS) for ...

متن کامل

Intelligent Diagnosis of Open and Short Circuit Faults in Electric Drive Inverters For Real-Time Applications

This paper presents a machine learning technique for fault diagnostics in induction motor drives. A normal model and an extensive range of faulted models for the inverter-motor combination were developed and implemented using a generic commercial simulation tool to generate voltages and current signals at a broad range of operating points selected by a machine learning algorithm. A structured n...

متن کامل

Stator Turn-to-Turn Fault Detection of Induction Motor by Non-Invasive Method Using Generalized Regression Neural Network

Condition monitoring and protection methods based on the analysis of the machine's current are widely used according to non-invasive characteristics of current transformers. It should be noted that, these sensors are installed by default in the machine control center. On the other hand, condition monitoring based on mathematical methods has been proposed in literature. However, they are model b...

متن کامل

A Study on Fault Diagnosis of Induction Motor using Neural-Wavelet

The induction motors effort to widely industrial fields. On the contrary, faults of the induction motors cause another faults of the whole system, because the faults of the induction motors often progress through long time. It is very important that diagnosis for diagnosis fault and extracted fault feature from the acquired signal using wavelet transform. Extracted features use the fault diagno...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007