scholarly journals Pengembangan Nominal Aturan Fuzzy pada Metode Fuzzy Mamdani untuk Menyeimbangkan Beban Tiga Phasa pada Saluran Distribusi Tegangan Menengah

Rekayasa ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 431-442
Author(s):  
Martinus W Djagolado ◽  
Amirullah Amirullah ◽  
Saidah Saidah
Keyword(s):  
Fuzzy Logic ◽  
Low Voltage ◽  
Fuzzy Rules ◽  
Voltage Distribution ◽  
Voltage Transformer ◽  
Load Current ◽  
Inference System ◽  
Medium Voltage ◽  
Fuzzy Logic Method ◽  
Logic Method

The use of electrical equipment on the customer side with low voltage absorbs unbalanced power. The load unbalances in each phase will result in an unbalanced current, resulting in a phase voltage shift in the secondary coil of the 20 kV/380 V medium voltage transformer. Shifting the voltage in the distribution transformer phase, then causes the flow of current in the transformer neutral wire causing losses. This paper proposes a fuzzy logic method with the Mamdani fuzzy inference system (FIS) to balance three-phase load currents at seven feeders of 20 kV medium voltage distribution at PLN Rayon Taman Jawa-Timur. The feeders are Ngelom, Tawang Sari, Geluran, Bringin, Masangan Kulon, Palm Residence, and Pasar Sepanjang. There are three input variables used, namely the load current in phase R, phase S, and phase T respectively. There are three output variables in one FIS block, namely changes in load current in phase R, phase S, and phase T respectively. With the number of fuzzy rules as many as 509 rules, the proposed method is able to produce the lowest load current unbalance value of 1.6% at Palm Residence Feeders. The development of a nominal (number) of fuzzy rules in the Fuzzy Logic Method with FIS Mamdani is able to reduce the value of unbalance load current at the 20 kV medium voltage distribution feeder better than the method proposed by previous researchers.

scholarly journals The Design of Directions and Shot Sound Distance Using Fuzzy Logic Method Based on Raspberry Pi

2021 ◽  
Vol 2 (Oktober) ◽  
pp. 32-41
Author(s):  
Rian Arbianto Prayogo ◽  
Dekki Widiatmoko ◽  
Budi Harijanto
Keyword(s):  
Fuzzy Logic ◽  
Detection System ◽  
Raspberry Pi ◽  
Rule Base ◽  
Inference System ◽  
Input Quantity ◽  
Technological Developments ◽  
Fuzzy Logic Method ◽  
The Republic ◽  
Logic Method

Abstract - The rise of a shooting incident that occurred in the border areas of the Republic of Indonesia is a big loss for the state in terms of personnel. Technological developments can be used as an alternative in the military world to help the role of soldiers so as to reduce personnel losses. This study aims to create a system for detecting the direction and distance of gunshots. This study uses an experimental method. This gunshot detection system also applies the Fuzzy Logic Method which is applied to the Raspberry Pi 4 and Microphone Max 4466 which is expected to detect the direction and distance of gunshots. This Fuzzy Logic method is used as an inference system or decision maker according to the input given. Fuzzy Logic broadly consists of fuzzification, rule base, and defuzzification. Fuzzification is useful for input normalization, so that the input quantity is in accordance with the fuzzy magnitude, namely the value in the range 0 to 1. After that, enter the rule base where in this step, the input set is compared with the rules or provisions of sound decibels so that it can be classified whether the distance and the direction of the captured sound is in the data range that has been programmed, in this step the signal is analyzed how much decibel sound SS2-V1 is by the MAX 4466 sensor. The conclusion is done by defuzzification, so the final result is that the closest distance to a gunshot at 1 meter is 250 Decibels.

Reduction of the Low Voltage Substation Constraints by Inserting Photovoltaic Systems in Underserved Areas

2019 ◽  
Vol 12 (2) ◽  
pp. 105-112
Author(s):  
Benbouza Naima ◽  
Benfarhi Louiza ◽  
Azoui Boubekeur
Keyword(s):  
Low Voltage ◽  
Voltage Drop ◽  
Electrical Energy ◽  
Utilization Rate ◽  
Photovoltaic Systems ◽  
Voltage Distribution ◽  
Medium Voltage ◽  
Pv Systems ◽  
Transformer Substation ◽  
Load Pattern

Background: The improvement of the voltage in power lines and the respect of the low voltage distribution transformer substations constraints (Transformer utilization rate and Voltage drop) are possible by several means: reinforcement of conductor sections, installation of new MV / LV substations (Medium Voltage (MV), Low Voltage (LV)), etc. Methods: Connection of mini-photovoltaic systems (PV) to the network, or to consumers in underserved areas, is a well-adopted solution to solve the problem of voltage drop and lighten the substation transformer, and at the same time provide clean electrical energy. PV systems can therefore contribute to this solution since they produce energy at the deficit site. Results: This paper presents the improvement of transformer substation constraints, supplying an end of low voltage electrical line, by inserting photovoltaic systems at underserved subscribers. Conclusion: This study is applied to a typical load pattern, specified to the consumers region.

scholarly journals Using WSR-88D Polarimetric Data to Identify Bird-Contaminated Doppler Velocities

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Yuan Jiang ◽  
Qin Xu ◽  
Pengfei Zhang ◽  
Kang Nai ◽  
Liping Liu
Keyword(s):  
Fuzzy Logic ◽  
Real Data ◽  
Radar Data ◽  
Second Step ◽  
Doppler Velocity ◽  
Data Quality Control ◽  
Fuzzy Logic Method ◽  
Automated Technique ◽  
Migrating Birds ◽  
Logic Method

As an important part of Doppler velocity data quality control for radar data assimilation and other quantitative applications, an automated technique is developed to identify and remove contaminated velocities by birds, especially migrating birds. This technique builds upon the existing hydrometeor classification algorithm (HCA) for dual-polarimetric WSR-88D radars developed at the National Severe Storms Laboratory, and it performs two steps. In the first step, the fuzzy-logic method in the HCA is simplified and used to identify biological echoes (mainly from birds and insects). In the second step, another simple fuzzy logic method is developed to detect bird echoes among the biological echoes identified in the first step and thus remove bird-contaminated velocities. The membership functions used by the fuzzy logic method in the second step are extracted from normalized histograms of differential reflectivity and differential phase for birds and insects, respectively, while the normalized histograms are constructed by polarimetric data collected during the 2012 fall migrating season and sorted for bird and insects, respectively. The performance and effectiveness of the technique are demonstrated by real-data examples.

scholarly journals Aplikasi Pengambilan Keputusan dengan Metode Tsukamoto pada Penentuan Tingkat Kepuasan pelanggan

CAUCHY ◽  
2015 ◽  
Vol 4 (1) ◽  
pp. 10 ◽  
Author(s):  
Venny Riana Riana Agustin ◽  
Wahyu Henky Irawan
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Fuzzy Inference ◽  
Weighted Average ◽  
Fuzzy Rules ◽  
Quality Of Services ◽  
Inference System ◽  
A Value ◽  
Fuzzy Logic Analysis

Tsukamoto method is one method of fuzzy inference system on fuzzy logic for decision making. Steps of the decision making in this method, namely fuzzyfication (process changing the input into kabur), the establishment of fuzzy rules, fuzzy logic analysis, defuzzyfication (affirmation), as well as the conclusion and interpretation of the results. The results from this research are steps of the decision making in Tsukamoto method, namely fuzzyfication (process changing the input into kabur), the establishment of fuzzy rules by the general form IF a is A THEN B is B, fuzzy logic analysis to get alpha in every rule, defuzzyfication (affirmation) by weighted average method, as well as the conclusion and interpretation of the results. On customers at the case, in value of 16 the quality of services, the value of 17 the quality of goods, and value of 16 a price, a value of the results is 45,29063 and the level is low satisfaction

scholarly journals Feature Extraction in Six Blocks to Detect and Recognize English Numbers

2021 ◽  
pp. 3790-3803
Author(s):  
Heba Kh. Abbas ◽  
Haidar J. Mohamad
Keyword(s):  
Fuzzy Logic ◽  
Feature Extraction ◽  
Computational Cost ◽  
Absolute Error ◽  
Suggested Method ◽  
Support Vector ◽  
Horizontal Line ◽  
Svm Algorithm ◽  
Fuzzy Logic Method ◽  
Logic Method

    The Fuzzy Logic method was implemented to detect and recognize English numbers in this paper. The extracted features within this method make the detection easy and accurate. These features depend on the crossing point of two vertical lines with one horizontal line to be used from the Fuzzy logic method, as shown by the Matlab code in this study. The font types are Times New Roman, Arial, Calabria, Arabic, and Andalus with different font sizes of 10, 16, 22, 28, 36, 42, 50 and 72. These numbers are isolated automatically with the designed algorithm, for which the code is also presented. The number’s image is tested with the Fuzzy algorithm depending on six-block properties only. Groups of regions (High, Medium, and Low) for each number showed unique behavior to recognize any number. Normalized Absolute Error (NAE) equation was used to evaluate the error percentage for the suggested algorithm. The lowest error was 0.001% compared with the real number. The data were checked by the support vector machine (SVM) algorithm to confirm the quality and the efficiency of the suggested method, where the matching was found to be 100% between the data of the suggested method and SVM. The six properties offer a new method to build a rule-based feature extraction technique in different applications and detect any text recognition with a low computational cost.

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