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4th International Conference on Electric Power Equipment-Switching Technology (ICEPE-ST)

作者： Hou Chunguang Fan Weidong Han Ying Cao Yundong Shenyang Univ Technol Inst Elect Apparat Technol & Applicat Shenyang Liaoning Peoples R China

ISBN: (纸本)9781538616512

In this paper, a new pulse separation technique based on fuzzy logic algorithm is proposed. An equivalent Time-Frequency diagram (TF map) is obtained from the feature extraction and clustering of both PD pulse signal and ambient noise signal. Since different kinds of PD types derived from different PD sources, they will form specific clusters in the TF map. It provides a possibility to classify the millivolt voltage PD pulse signals from the ambient noise signals, enhances the anti-interference ability of the PD detection system, classifies partial discharge patterns and locates PD sources. This paper provides a new idea for the accurate extraction and processing of the PD pulse signal of the 12kV switchgear, which is also helpful to improve the detection sensitivity and locate PD sources.

关键词： switchgear partial discharge fuzzy logic algorithm pulse separation

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Estimation of the Ageing Condition of Oil-Filled Transformers Based on the Oil Parameters Using a Novel fuzzy logic algorithm 21st

Estimation of the Ageing Condition of Oil-Filled Transformer...

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21st International Symposium on High Voltage Engineering (ISH)

作者： Kinkeldey, Tobias Muenster, Tobias Werle, Peter Suwarno Haemel, Kai Preusel, Joerg Leibniz Univ Hannover Inst Elect Power Syst Schering Inst Div High Voltage Engn & Asset Management Hannover Germany Inst Technol Sch Elect Engn & Informat Bandung Indonesia GRIDINSPECT GmbH Feldatal Germany

ISBN: (纸本)9783030316761;9783030316754

The condition of the transformer insulation determines the remaining life of the transformer. Over the transformer service life, both liquid and solid insulation undergoes a continuous aging process under electrical, chemical, mechanical and thermal stresses. The insulating liquid of a transformer can be reconditioned or replaced;however, this is not the case for the cellulose insulation. Therefore, the condition of the paper insulation is the major factor for determining the aging status of a transformer. To assess the paper condition, the common method is to measure the degree of polymerization (DP) of the paper insulation as a significant parameter. This method is destructive as it requires a sample of paper from inside of the transformer. Therefore, it could not be applied for transformers in operation. There are several approaches to approximate the DP value without direct measurements of paper samples. This research presents an improved method based on a fuzzy logic system for the estimation of the DP based on dissolved gases and chemical parameters of the liquid insulation. The algorithm is developed to create the rules for the use of fuzzy sets based on the information gain extracted by the entropy of the laboratory measurement data. This algorithm employs entropy to examine the sample homogeneity. Entropy is a measure of information theory that can determine the dataset characteristics concerning impurity and homogeneity. The algorithm uses fuzzy sets of oil parameters like Acidity, Interfacial Tension (IFT), Carbon Dioxide (CO2) and Carbon Monoxide (CO) and the breakdown voltage (BDV) for determination of the DP value.

关键词： fuzzy logic algorithm DP value Paper ageing

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SUGPO: A White Spot Disease Detection in Shrimps Using Hybrid Neural Networks with fuzzy logic algorithm 2018

SUGPO: A White Spot Disease Detection in Shrimps Using Hybri...

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6th International Conference on Information Technology - IoT and Smart City (ICIT)

作者： Fabregas, Aleta C. Cruz, Debrelie Marmeto, Mark Daniel Polytech Univ Philippines A Mabini CampusAnonas St Manila 1016 Philippines

ISBN: (纸本)9781450366298

Shrimp is a high-value commodity and one of the major aquaculture species not only in the Philippines but in the world. White Spot Syndrome Virus (WSSV) is a virus that has been infecting shrimp farms and affecting the shrimp productions across the globe. Manual disease inspection among the shrimps is a time consuming process in the management of shrimp farms. Thus, the researchers conducted this study in able to provide a fast disease inspection tool in order to early detect the infection before the disease results to an outbreak. The researchers developed a system that detects the white spot disease among the shrimps. Image processing techniques was utilized in the system as well as Artificial Intelligence algorithms such as Artificial Neural Network (ANN) and fuzzy logic. ANN has the ability to learn and classify an input base on its learnings, whereas fuzzy logic is known for dealing with uncertainties. The main objective of this study is to determine the accuracy and reliability rate of the tool in detecting the WSSV using the hybrid algorithm of ANN and fuzzy logic considering the color of the spot, location of the white spots and the discoloration in the body of the shrimp. For the testing of the system, 50 samples of shrimps were used. The system assessed each samples by analyzing the images of the shrimps. In evaluating a set of Shrimp samples, the system's diagnosis and the expert's diagnosis were compared and analyzed. The researchers used the confusion matrix and the accuracy rate formula for the computation of the accuracy rate and the Test-Retest Reliability equation for the computation of the reliability rate. The result of the tool produced a system performance with 90% accuracy rate and a reliability rate of 0.8 which is equivalent to Good Reliability. Thus, the result of this study shows that ANN and fuzzy logic are effective algorithms to utilize in automated disease diagnostics like the white spot disease detection.

关键词： Hybrid neural networks fuzzy logic algorithm image processing white spot syndrome white spot syndrome virus

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Analysis of fuzzy logic algorithm for Load Balancing in SDN 4

Analysis of Fuzzy Logic Algorithm for Load Balancing in SDN

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4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Prakoso, Ian Agung Hertiana, Sofia Naning Dewanta, Favian Telkom Univ Sch Elect Engn Bandung Indonesia

ISBN: (纸本)9781665401517

Server Resource limitations are generally an obstacle affecting the quality of service (QoS) due to increased traffic levels. Therefore, Load Balancing is needed to manage service requests to the optimal application server. Software-Defined Network (SDN) has advantages in controlling the network which can be exploited with various load balancing strategies that are used to distribute traffic loads to improve overall system performance. The Performance for load balancing can be improved by selecting the server with minimum load using the fuzzy logic algorithm. Traditional load balancing lacked the usage of device state data. In this study, an SDN-based Server Load Balancing method using fuzzy logic methods has been performed. fuzzy algorithm successfully delivers HTTP requests to lowest load server based on Distribution Server Index. In the testing, the server load must be directed at the lowest server weight so that each server should not be overloaded. In testing with a request load ranging from 100 - 500, the fuzzy algorithm imposes more traffic distribution on the 3rd Server with the lowest server load. In the CPU usage test, the fuzzy logic algorithm has the lowest average value namely 39%. In the RAM usage test, the fuzzy logic algorithm has the lowest average value namely 54%. In the throughput test, the fuzzy logic algorithm has the highest average value namely 2KBps. The Fairness Index of fuzzy logic is 0.45 while Round Robin's fairness index is 0.99. Round Robin algorithm can outperform other algorithms in terms of Fairness Index, as the fairest algorithm.

关键词： Software Defined Network (SDN) Load Balancing fuzzy logic algorithm

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Design and Implementation of Fire Detection System Using fuzzy logic algorithm 5

Design and Implementation of Fire Detection System Using Fuz...

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IEEE Asia Pacific Conference on Wireless and Mobile (APWiMob)

作者： Devi, Anak Agung Putu Bunga Surya Istikmal Karna, Nyoman Telkom Univ Multimedia Big Data & Cybersecur Lab Fac Elect Enginering Bandung Indonesia

ISBN: (纸本)9781728148656

One of the features of a smart home is fire detection. There have been many developments in previous studies, but not many have implemented a detection system with the fuzzy logic method. Therefore, in this research we have developed a fire detection system that applies fuzzy logic methods and algorithms. We used Raspberry pi 3 as the embedded system, DHT-11 and MQ-2 sensors to detect fires. Detection results will be processed using a fuzzy system and the results will be notified through the WhatsApp application and monitored through the web. The test results show that the system that has been developed is running well and can be used as a fire detection system in smart homes.

关键词： Fire detection Raspberry pi 3 fuzzy logic algorithm DHT-11 MQ-2

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eRheumatologist: Mobile-based Expert System for Rheumatology Utilizing fuzzy logic algorithm 2017

eRheumatologist: Mobile-based Expert System for Rheumatology...

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International Conference on Computer Science and Artificial Intelligence (CSAI)

作者： Corpuz, Mark Jade S. Avestro, Junnel Calanda, Fredilyn B. Morco, Roselia C. Angeles, Jean M. Alcala, Carl Matthew S. 938 Aurora Blvd Cubao Quezon City 1109 Philippines

ISBN: (纸本)9781450353922

Rheumatic or musculoskeletal conditions comprise over 150 diseases and syndromes, which are usually progressive and associated with pain. They can broadly be categorized as joint diseases, physical disability, spinal disorders, and conditions resulting from trauma. Musculoskeletal conditions are leading causes of morbidity and disability, giving rise to enormous healthcare expenditures and loss of work. [1] The annual mortality rate per 100,000 people from rheumatoid arthritis in Philippines has increased by 17.6% since 1990, an average of 0.8% a year.[2] Likewise, we developed a mobile-based expert system focusing on rheumatic disease which allows users to diagnose their current rheumatic condition. It allows user to identify the possible cause of their joints and muscle pain. It will benefit the user since the system will enhance their knowledge of rheumatic diseases aside from the basic information they have The system applies the concept of fuzzy logic algorithm to be able to get the possible result of diagnostic testing. This algorithm will allow the system to determine and categorize possible symptoms and evaluated by the different rules as part of the inference engine and validated by the knowledge-based database. The system also includes additional feature in providing information of different rheumatic disease and possible remedies. The system was evaluated by different users such as Rheumatologist, mobile developer and possible user of different ages to ensure that the system achieve its goals and objectives. As a result of the evaluation, users agreed that the application performed its functions as a diagnostic tool, can provide a good interface for ease of access and able to provide a clear and concise information.

关键词： Mobile Expert System fuzzy logic algorithm Prevalence

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An Improved Droop Control for DC Microgrid Based on fuzzy logic algorithm 9

An Improved Droop Control for DC Microgrid Based on Fuzzy Lo...

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IEEE 9th International Conference on Power Electronics Systems and Applications (PESA)

作者： Xie, Hongbiao Cai, Fenghuang Jiang, Jiahui Chen, Weidong Fuzhou Univ Coll Elect Engn & Automat Fuzhou Peoples R China Qingdao Univ Coll Elect Engn Qingdao Peoples R China

ISBN: (纸本)9781665486682

To solve the problem of traditional droop control in a DC microgrid cannot meet both current equalization and voltage regulation requirements in load distribution due to the presence of line impedance. This work proposes a fuzzy logic-based improved droop control scheme and designs two fuzzy controllers for the current compensation and bus voltage compensation, respectively. To improve current equalization accuracy and DC bus voltage stability, voltage compensator and current compensator based on fuzzy logic algorithm are designed. Finally, a simulation platform of the DC microgrid with three phase-shifted full-bridge DC/DC converters as the main circuit topology is built in MATLAB/Simulink to verify the feasibility and effectiveness of the proposed control scheme.

关键词： DC microgrid droop control fuzzy logic algorithm

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Estimation of the Degree of Polymerization (DP) in Oil-Paper Insulation System Based on Dielectric and DGA Data Using fuzzy logic algorithm 4

Estimation of the Degree of Polymerization (DP) in Oil-Paper...

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4th IEEE Conference on Power Engineering and Renewable Energy (ICPERE)

作者： Nasution, Eldi F. Prasojo, Rahman A. Suwarno Kinkeldey, T. Werle, P. Inst Teknol Bandung Sch Elect Engn & Informat Bandung Indonesia PT PLN Persero Jakarta Indonesia Leibniz Univ Hannover Inst Elect Power Syst Div High Voltage Engn & Asset Management Schering Inst Callinstr 25A D-30167 Hannover Germany

ISBN: (纸本)9781538674567

The power plant system produces energy to be transmitted to load center through transmission system and distribution system. The transformer connects these three systems by converting the voltage level of each system. Fault on the transformer will disrupt the power supply to the load center. To maintain the availability of the transformer, the asset owner must be able to manage the transformer assets optimally. The condition of the transformer should be monitored for appropriate maintenance with the component fault. The condition of the transformer is determined by the condition of the paper insulation. The condition of paper insulation is difficult to measure directly since it requires high cost and potentially damage the transformer components. This paper shows the attempt to determine paper insulation condition without direct measurement on paper insulation. Calculation of the prediction of paper insulation condition is based on dielectric characteristics and DGA data in oil insulation of transformer. This calculation will use the fuzzy logic algorithm.

关键词： fuzzy logic algorithm degree of polymerization insulation transformer oil paper acidity interfacial tension carbonmonoxide carbondioxide

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Developing Shinta's Early Deterioration Detection by using fuzzy logic algorithm in Indonesia

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ENFERMERIA CLINICA 2019年第Sup2期29卷 905-909页

作者： Silaswati, Shintha Sahar, Junaiti Sari, Nina Kemala Bardosono, Saptawati Christanto, Bino Univ Indonesia Fac Nursing Depok West Java Indonesia Bani Saleh Hlth Sci Inst Bekasi West Java Indonesia Dr Ciptomangunkusumo Hosp Jakarta Indonesia

Objective: To design an application that detects health deterioration in elderly (System for Health Aging Instrument Automation) Shinta's Early Deterioration Detection (SEDD) by using fuzzy logic algorithm (FLA) for smartphone and android. Method: The study design was experimental with simple random sampling method involving 130 data. Fuzzification, inference, and defuzzification are a process to formulate a mapping of independent variables processed into a groundwork, which decides dependent variables (output) by using fuzzy logic. Results: Prototype or android-based Shinta's Early Deterioration Detection model facilitates detection of health deterioration in older people who are admitted in hospital in Indonesia with accuracy value alpha 96.85% and effectiveness value beta 36.5 s. Conclusion: SEDD is able to evaluate health deterioration in elderly patient at the moment of admission in ward. Nurse may make a clinical decision immediately. It may reduce the risk for disability and mortality as well. (C) 2019 Elsevier Espana, S.L.U. All rights reserved.

关键词： Elderly deterioration detection fuzzy logic algorithm Indonesia's instrument

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Determining Average Error of Flank Wear in Turning Duplex Stainless Steel Using Canny's Edge Detection algorithm in Comparison with fuzzy logic algorithm 6

Determining Average Error of Flank Wear in Turning Duplex St...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Vignesh, S. Senthil Pon Bommi, R.M. Saveetha School of Engineering SIMATS Department of ECE Chennai India

ISBN: (纸本)9798350304480

To obtain the average error of flank wear in turning Duplex Stainless Steel (DSS) using Canny's Edge Detection algorithm and compare it with fuzzy logic algorithm. The average error accuracy of flank wear is computed for Canny's Edge Detection algorithm and fuzzy logic algorithm separately and are categorized into Group 1 and Group 2 respectively, each consisting of 27 samples, providing a total sample size of 54. It was computed using *** with an enrollment ratio of one, an alpha error of 0.05, a G-power of 80%, and a confidence interval of 95%. The average error accuracy determined using the Novel Canny's Edge Detection algorithm (92.78%) is more accurate and statistically significant than the fuzzy logic algorithm (88.91 %) and the significance value obtained is p = 0.000 (p © 2023 IEEE.

关键词： Average Error Duplex Stainless Steel Flank Wear fuzzy logic algorithm Novel Canny's Edge Detection algorithm Quality of Life Turning

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