Detection and classification of power quality events by expert system using analytic hierarchy method

2018 ◽  
Vol 52 ◽  
pp. 729-740 ◽  
Author(s):  
S. Rajeshbabu ◽  
B.V. Manikandan
Keyword(s):  
Expert System ◽  
Power Quality ◽  
Analytic Hierarchy

A Fuzzy–Expert System For Classification Of Short Duration Voltage Disturbances

2012 ◽  
Author(s):  
Ghafour Amouzad Mahdiraji ◽  
Azah Mohamed
Keyword(s):  
Expert System ◽  
Power Quality ◽  
Short Duration ◽  
Automated Detection ◽  
Voltage Sag ◽  
Fuzzy Expert System ◽  
Correct Classification Rate ◽  
Classification Rate ◽  
Fast Fourier Transform Analysis

Satu aspek penting dalam penilaian kualiti kuasa adalah pengesanan dan pengkelasan gangguan kualiti kuasa secara automatik yang memerlukan penggunaan teknik kepintaran buatan. Kertas kerja ini membentangkan penggunaan sistem pakar-kabur untuk pengkelasan gangguan voltan jangka masa pendek yang termasuk lendut voltan, ampul dan sampukan. Untuk memperolehi sifat unik bagi gangguan voltan, analisis jelmaan Fourier pantas dan teknik purataan punca min kuasa dua digunakan untuk menentukan parameter gangguan seperti tempoh masa, magnitud voltan pmk maksimum dan minimum. Berasaskan pada parameter ini, sebuah sistem pakar–kabur telah dibangunkan dengan mengset aturan kabur yang menimbangkan lima masukan dan tiga keluaran. Sistem ini direka bentuk untuk mengesan dan mengkelaskan tiga jenis gangguan voltan tempoh masa pendek dengan menentukan sama ada gangguan adalah gangguan ketika, gangguan seketika dan bukan gangguan lendut, ampul dan sampukan. Untuk mengesahkan kejituan sistem yang dicadangkan, ia telah diuji dengan gangguan voltan yang diperolehi dari pengawasan. Keputusan ujian menunjukkan bahawa sistem pakar–kabur yang dibangunkan telah memberikan kadar pengkelasan yang betul sebanyak 98.4 %. Kata kunci: Kualiti kuasa, sistem pakar–kabur, lendut, ampul dan sampukan One of the important aspects in power quality assessment is automated detection and classification of power quality disturbances which requires the use of artificial intelligent techniques. This paper presents the application of fuzzy–expert system for classification of short duration voltage disturbances which include voltage sag, swell and interruption. To obtain unique features of the voltage disturbances, fast Fourier transform analysis and root mean square averaging technique are utilized so as to determine the disturbance parameters such as duration, maximum and minimum rms voltage magnitudes. Based on these parameters, a fuzzy-expert system has been developed to set the fuzzy rules incorporating five inputs and three outputs. The system is designed for detecting and classifying the three types of short duration voltage disturbances, so as to determine whether the disturbance is instantaneous, momentary and non sag, swell and interruption. To verify the accuracy of the proposed system, it has been tested with recorded voltage disturbances obtained from monitoring. Tests results showed that the developed fuzzy–expert system gives a correct classification rate of 98.4 %. Key words: Power quality, fuzzy–expert system, sag, swell and interruption.

Classification of Power Quality Problems by Wavelet Fuzzy Expert System

2012 ◽  
Vol 463-464 ◽  
pp. 1573-1578
Author(s):  
N. Karthik ◽  
Shaik Abdul Gafoor ◽  
M. Surya Kalavathi
Keyword(s):  
Expert System ◽  
Power Quality ◽  
Intelligent System ◽  
Fuzzy Expert System ◽  
Quality Problem ◽  
Electric Power Quality ◽  
Transient Disturbances ◽  
Key Issues ◽  
Power Utilities

Electric power quality, which is a current interest to several power utilities all over the world, is often severely affected by harmonics and transient disturbances. There is no unique model which can assess the power quality problem and to identify and classify them properly. Existing automatic recognition methods need improvement in terms of their versatility, reliability, and accuracy. The FUZZY LOGIC based tools have been applied for the PQ classification. This paper addresses Power quality problem classification by wavelet and fuzzy expert system. Major Key issues and challenges related to these advanced techniques in automatic classification of PQ problems are highlighted. New intelligent system technologies using DSP, expert systems, AI and machine learning provide some unique advantages in intelligent classification of PQ distortions

Index of suicide risk in Mexico using Twitter

2019 ◽  
pp. 1-13
Author(s):  
Luz Judith Rodríguez-Esparza ◽  
Diana Barraza-Barraza ◽  
Jesús Salazar-Ibarra ◽  
Rafael Gerardo Vargas-Pasaye
Keyword(s):  
Social Networks ◽  
Analytic Hierarchy Process ◽  
Suicide Risk ◽  
Opinion Mining ◽  
Real Data ◽  
Analytic Hierarchy ◽  
Specialized Care ◽  
The Analytic Hierarchy Process ◽  
Hierarchy Process

Objectives: To identify early suicide risk signs on depressive subjects, so that specialized care can be provided. Various studies have focused on studying expressions on social networks, where users pour their emotions, to determine if they show signs of depression or not. However, they have neglected the quantification of the risk of committing suicide. Therefore, this article proposes a new index for identifying suicide risk in Mexico. Methodology: The proposal index is constructed through opinion mining using Twitter and the Analytic Hierarchy Process. Contribution: Using R statistical package, a study is presented considering real data, making a classification of people according to the obtained index and using information from psychologists. The proposed methodology represents an innovative prevention alternative for suicide.

Automatic Classification of Power Quality Events Using Balanced Neural Tree

2014 ◽  
Vol 61 (1) ◽  
pp. 521-530 ◽  
Author(s):  
B. Biswal ◽  
M. Biswal ◽  
S. Mishra ◽  
R. Jalaja
Keyword(s):  
Power Quality ◽  
Automatic Classification
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