Fault Diagnosis of Analog Circuit Using DC Approach and Neural Networks
نویسندگان
چکیده
Several approaches for the diagnosis of faults in analog circuits have reasonably accuracy which comes at the cost of heavier processing requirements and lowered efficiencies. In this paper, we propose a time domain based technique for fault diagnosis using specifications extracted from the step response of a circuit. With the help of neural network we have to go for back propagation learning phase, and all the simulated results from multisim simulation i.e. node voltages of the circuit. We have implemented this on back propagation algorithm and after training network must have proper performance target. In neural-network based fault diagnosis, network works as a fault dictionary.
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 کاملOnline Monitoring and Fault Diagnosis of Multivariate-attribute Process Mean Using Neural Networks and Discriminant Analysis Technique
In some statistical process control applications, the process data are not Normally distributed and characterized by the combination of both variable and attributes quality characteristics. Despite different methods which are proposed separately for monitoring multivariate and multi-attribute processes, only few methods are available in the literature for monitoring multivariate-attribute proce...
متن کاملA Neural-Network-Based Fault Diagnosis Approach for Analog Circuits by Using Wavelet Transformation and Fractal Dimension as a Preprocessor
This paper presents a new method of analog fault diagnosis based on back-propagation neural networks (BPNNs) using wavelet decomposition and fractal dimension as preprocessors. The proposed method has the capability to detect and identify faulty components in an analog electronic circuit with tolerance by analyzing its impulse response. Using wavelet decomposition to preprocess the impulse resp...
متن کاملUse of Neural Networks in Testing Analog to Digital Converters
In the past two decades, the techniques of artificial neural networks are growing mature, as a datadriven method, which provides a totally new perspective to fault diagnosis. Testing issues are becoming more and more important with the quick development of both digital and analog circuit industry. Analog-to-digital converters (ADCs) are becoming more and more widespread owing to their fundament...
متن کاملA Network Theoretical Approach to Analog DC-Fault Diagnosis
This paper presents a network theoretical approach to analog DC-fault diagnosis. The developed approach efficiently localizes the fault and identifies the corresponding fault characteristic with standard circuit simulators. Furthermore, the theoretical foundation of our method offers a deep understanding for DC-fault diagnosis and clearly shows the limits for fault diagnosis techniques.
متن کامل