Neural Network Expert System in the Application of the EMC Design

2015 ◽  
Vol 742 ◽  
pp. 355-359
Author(s):  
Ji Ling Tang ◽  
Nian Feng Li ◽  
Hong Liang Liu
Keyword(s):  
Neural Network ◽  
Expert System ◽  
Electromagnetic Interference ◽  
Optimization Design ◽  
Electromagnetic Coupling ◽  
Electronic Equipment ◽  
Inference Mechanism ◽  
The Common ◽  
Emc Design ◽  
Test Verification

According to the characteristics of the large equipment, electromagnetic interference, using neural network method is put forward a set of for large electronic equipment electromagnetic coupling and interference, the analysis of the expert system based on the large electronic equipment as analysis object, the common interference on the interference classification and coding, the BP neural network is constructed, using neural network, the inference mechanism of expert system for the optimization design, and test verification.

scholarly journals High Dimensional Electromagnetic Interference Signal Clustering Based On SOM Neural Network

2016 ◽  
Vol 20 (1) ◽  
pp. 27
Author(s):  
Hongyi Li ◽  
Di Zhao ◽  
Shaofeng Xu ◽  
Pidong Wang ◽  
Jiaxin Chen
Keyword(s):  
Neural Network ◽  
Electromagnetic Interference ◽  
Large Scale ◽  
Spectral Characteristics ◽  
Simulation Models ◽  
Integrated System ◽  
Interference Signal ◽  
Global Features ◽  
Strongly Nonlinear ◽  
Emc Design

In this paper, we study the spectral characteristics and global representations of strongly nonlinear, non-stationary electromagnetic interferences (EMI), which is of great significance in analysing the mathematical modelling of electromagnetic capability (EMC) for a large scale integrated system. We firstly propose to use Self-Organizing Feature Map Neural Network (SOM) to cluster EMI signals. To tackle with the high dimensionality of EMI signals, we combine the dimension reduction and clustering approaches, and find out the global features of different interference factors, in order to finally provide precise mathematical simulation models for EMC design, analysis, forecasting and evaluation. Experimental results have demonstrated the validity and effectiveness of the proposed method.

Fault Diagnosis Expert System for Special Electronic Equipment Based on the Fuzzy Neural Network

2012 ◽  
Vol 241-244 ◽  
pp. 401-404
Author(s):  
Xue Zhong Yin ◽  
Jie Gui Wang
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Expert System ◽  
Fuzzy Neural Network ◽  
Electronic System ◽  
Electronic Equipment ◽  
Diagnostic Model ◽  
Model Based ◽  
Proposed Model ◽  
Fuzzy Neural

In order to improve the efficiency and reliability of fault diagnosis for the special electronic equipment, an intelligent fault diagnostic model based on Fuzzy Neural Network (FNN) is proposed. Firstly, the fault diagnosis model based on the FNN Expert System (ES) is built. Secondly, the fault diagnosis expert system of the special electronic equipment based on this model is introduced. Finally, experiments show that the proposed model is correct and the FD system is effective. Moreover, the given method provides a new way of fault diagnosis for other modern electronic system.

Rancang Bangun Sistem Pakar Prediksi Stres Belajar Dengan Neural Network Algoritma Backpropagation

2016 ◽  
Vol 7 (2) ◽  
pp. 105-112
Author(s):  
Adhi Kusnadi ◽  
Idul Putra
Keyword(s):  
Neural Network ◽  
Expert System ◽  
Stress Level ◽  
Network Structure ◽  
Human Being ◽  
Accuracy Rate ◽  
Backpropagation Algorithm ◽  
Stress Prediction ◽  
Index Terms ◽  
Hidden Nodes

Stress will definitely be experienced by every human being and the level of stress experienced by each individual is different. Stress experienced by students certainly will disturb their study if it is not handled quickly and appropriately. Therefore we have created an expert system using a neural network backpropagation algorithm to help counselors to predict the stress level of students. The network structure of the experiment consists of 26 input nodes, 5 hidden nodes, and 2 the output nodes, learning rate of 0.1, momentum of 0.1, and epoch of 5000, with a 100% accuracy rate. Index Terms - Stress on study, expert system, neural network, Stress Prediction

scholarly journals Opposite Triangle Carrier with SVPWM for Common-Mode Voltage Reduction in Dual Three Phase Motor Drives

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 282
Author(s):  
Seon-Ik Hwang ◽  
Jang-Mok Kim
Keyword(s):  
Electromagnetic Interference ◽  
Pulse Width Modulation ◽  
Motor Drives ◽  
Common Mode ◽  
Pwm Inverter ◽  
Common Mode Voltage ◽  
Voltage Vector ◽  
Three Phase ◽  
The Common ◽  
Zero Voltage

The common-mode voltage (CMV) generated by the switching operation of the pulse width modulation (PWM) inverter leads to bearing failure and electromagnetic interference (EMI) noises. To reduce the CMV, it is necessary to reduce the magnitude of dv/dt and change the frequency of the CMV. In this paper, the range of the CMV is reduced by using opposite triangle carrier for ABC and XYZ winding group, and the change in frequency in the CMV is reduced by equalizing the dwell time of the zero voltage vector on ABC and XYZ winding group of dual three phase motor.

scholarly journals Emulation with Organic Memristive Devices of Impairment of LTP Mechanism in Neurodegenerative Disease Pathology

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Silvia Battistoni ◽  
Victor Erokhin ◽  
Salvatore Iannotta
Keyword(s):  
Neural Network ◽  
Information Transmission ◽  
Common Sense ◽  
Artificial Neuron ◽  
Cell Network ◽  
Neuron Networks ◽  
A Cell ◽  
The Common ◽  
Major Progress ◽  
Single Synapse

We explore and demonstrate the extension of the synapse-mimicking properties of memristive devices to a dysfunctional synapse as it occurs in the Alzheimer’s disease (AD) pathology. The ability of memristive devices to reproduce synapse properties such as LTP, LTD, and STDP has been already widely demonstrated, and moreover, they were used for developing artificial neuron networks (perceptrons) able to simulate the information transmission in a cell network. However, a major progress would be to extend the common sense of neuromorphic device even to the case of dysfunction of natural synapses. Can memristors efficiently simulate them? We provide here evidences of the ability of emulating the dysfunctional synaptic behavior typical of the AD pathology with organic memristive devices considering the effect of the disease not only on a single synapse but also in the case of a neural network, composed by numerous synapses.

Predicting Electromagnetic Interference to a Terminated Wire Using Characteristic Mode Analysis

2021 ◽  
Vol 35 (11) ◽  
pp. 1318-1319
Author(s):  
Mohamed Hamdalla ◽  
Anthony Caruso ◽  
Ahmed Hassan
Keyword(s):  
Electromagnetic Interference ◽  
Incident Angle ◽  
Electromagnetic Coupling ◽  
Ground Plane ◽  
Mode Analysis ◽  
Characteristic Mode ◽  
Work Characteristic

Electromagnetic coupling to realistic wire configurations exhibit large variations with respect to the frequency, incident angle, and polarization of the interfering signal. In this work, Characteristic Mode Analysis (CMA) is used to calculate the fundamental modes of a terminated wire above an infinite ground plane. Using the properties of the modes, the coupled currents to the wire’s loads are predicted for different incident excitations. Using this simple but practical wire configuration, we show the versatility of CMA in practical electromagnetic interference and coupling applications.

Sign in / Sign up

Export Citation Format

Share Document