scholarly journals Faults diagnosis and assessment of transformer insulation oil quality: intelligent methods based on dissolved gas analysis a-review

2015 ◽  
Vol 4 (1) ◽  
pp. 54 ◽  
Author(s):  
Ahmed Raisan ◽  
M.M Yaacob ◽  
Malik Abdulrazzaq Alsaedi
Keyword(s):  
Fuzzy Logic ◽  
Expert System ◽  
Oil Quality ◽  
Electrical Power ◽  
Gas Analysis ◽  
Economic Losses ◽  
Dissolved Gases ◽  
Insulating Oil ◽  
Intelligent Methods

The search for determining accurate faults and assessing the oil quality of high voltage electrical power transformers for life-long maintenance is ever-demanding. The durability of transformers function is significantly decided by the excellence of its insulation which deteriorates over time due to temperature fluctuations and moisture contents. The accurate diagnoses of faults in early stages and the efficient assessment of oil quality using an intelligent program is the key challenges in protecting transformers from potential failures occur during operation to avoid economic losses. The dissolved gases analysis in oil is a reliable method in the diagnosis of faults and assessing the quality of insulating oil in transformers. Recently, application of artificial intelligence (AI) has included fuzzy logic, expert system (EPS), and artificial neural network (ANN), Expert system and fuzzy logic can take DGA standards. This paper represents the review most of the methods used to diagnose faults and assessment of insulating oil for transformers through the dissolved gases analysis DGA.

scholarly journals DGA Method-Based ANFIS Expert System for Diagnosing Faults and Assessing Quality of Power Transformer Insulation Oil

2015 ◽  
Vol 10 (1) ◽  
pp. 13 ◽  
Author(s):  
Mohd Muhridza Bin Yaacob ◽  
Ahmed Raisan Hussein ◽  
Mohd Fauzi Bin Othman
Keyword(s):  
Expert System ◽  
Power Transformer ◽  
Oil Quality ◽  
Gas Analysis ◽  
Ratio Method ◽  
Economic Losses ◽  
Intelligent Software ◽  
Transformer Insulation ◽  
Insulation Oil

<p class="zhengwen"><span lang="EN-GB">Accurate fault diagnostics and assessment of electrical power transformer insulation oil for lifelong endurance are the key issues addressed in this research. The durability of a transformer is significantly determined by the quality of its insulation oil, which deteriorates over time due to temperature fluctuations and moisture content. Protecting transformers from potential failure through early and precise diagnosis of faults and through efficient assessment of oil quality during the actual conduct of the operation can avoid sizeable economic losses. The ANFIS Expert System that uses intelligent software plays an important role in this regard. The dissolved gas analysis (DGA) in oil is a reliable method for diagnosing faults and assessing insulation oil quality in transformers. The safeguarding teams of transformer power stations often suffer from the occurrence of sudden faults, which result in severe damages and heavy monetary loss. The oil in transformers must be appropriately treated to circumvent such failures. In this research, an ANFIS Expert System was used to diagnose faults and to assess the status and quality of insulation oil in power transformers. A suitable treatment was identified using the Rogers ratio method depending on the DGA in oil. The graphical user interface from the MATLAB environment was used and proven effective for fault diagnosis and oil quality evaluation. The training algorithm is capable of assessing oil quality according to the specifications of the IEEE standard C57-104 and the IEC standard 60599.</span></p>

scholarly journals Towards Precise Interpretation of Oil Transformers via Novel Combined Techniques Based on DGA and Partial Discharge Sensors

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2223 ◽  
Author(s):  
Sayed A. Ward ◽  
Adel El-Faraskoury ◽  
Mohamed Badawi ◽  
Shimaa A. Ibrahim ◽  
Karar Mahmoud ◽  
...  
Keyword(s):  
Power Transformer ◽  
Partial Discharge ◽  
Electrical Power ◽  
Diagnostic Techniques ◽  
Gas Analysis ◽  
Economic Losses ◽  
Dissolved Gas ◽  
Electricity Transmission ◽  
Dissolved Gas Analysis ◽  
Precise Interpretation

Power transformers are considered important and expensive items in electrical power networks. In this regard, the early discovery of potential faults in transformers considering datasets collected from diverse sensors can guarantee the continuous operation of electrical systems. Indeed, the discontinuity of these transformers is expensive and can lead to excessive economic losses for the power utilities. Dissolved gas analysis (DGA), as well as partial discharge (PD) tests considering different intelligent sensors for the measurement process, are used as diagnostic techniques for detecting the oil insulation level. This paper includes two parts; the first part is about the integration among the diagnosis results of recognized dissolved gas analysis techniques, in this part, the proposed techniques are classified into four techniques. The integration between the different DGA techniques not only improves the oil fault condition monitoring but also overcomes the individual weakness, and this positive feature is proved by using 532 samples from the Egyptian Electricity Transmission Company (EETC). The second part overview the experimental setup for (66/11.86 kV–40 MVA) power transformer which exists in the Egyptian Electricity Transmission Company (EETC), the first section in this part analyzes the dissolved gases concentricity for many samples, and the second section illustrates the measurement of PD particularly in this case study. The results demonstrate that precise interpretation of oil transformers can be provided to system operators, thanks to the combination of the most appropriate techniques.

An Intelligent Design for Foot Orthoses

2008 ◽  
Vol 381-382 ◽  
pp. 607-610
Author(s):  
Sherif El-Sayed Hussein
Keyword(s):  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Expert System ◽  
Diabetic Foot ◽  
Intelligent Design ◽  
Normal Load ◽  
Foot Orthoses ◽  
Functional Impairments ◽  
Similar Nature ◽  
Intelligent Methods

Foot disorders may arise from different functional impairments. In all cases the resulting problem relates to a disturbance of the normal load bearing mechanisms of the foot, frequently with associated pain. Devices used to assist the patient are usually designed relying on the talent and expertise of well trained clinicians. The number of experienced clinicians in such field is few compared to the needs of the society. In this research, expert system techniques are used to design foot orthoses using intelligent methods which are based on fuzzy logic and Genetic Algorithms. The design is assessed using a specified design problem namely a diabetic foot with an ulcer risk. The proposed design can achieve better pressure distribution. Further, such a design can be applied to other comparable problems of a similar nature.

scholarly journals Perancangan Alat Pendeteksi Kualitas Minyak Goreng Dengan Parameter Viskositas Dan Densitas Mengggunakan Metode Fuzzy Logic

2021 ◽  
Vol 11 (1) ◽  
pp. 22-28
Author(s):  
Alex Surapati ◽  
Azam Zyaputra ◽  
Reza Satria Rinaldi
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Oil Quality ◽  
Test Results ◽  
Inference System ◽  
The Public ◽  
Cooking Oil ◽  
Market Needs

AbstrakThe quality of cooking oil sold in the market needs to be checked to ensure its health. cooking oil quality detector is designed to make it easier for the public to know the quality of the cooking oil. The research method is to make tools and conduct testing. The test is carried out by measuring the viscosity and density using the tool made. When the viscosity of 985 fuzzification was "good", and the density was 542.93 Kg/mL of "good" fuzzification, the fuzzification was processed by a fuzzy inference system, then defuzzification occurred in the form of oil quality results. fried "good". When the viscosity of 932 fuzzification is "sufficient", and the density is 618.69 Kg/mL of "moderate" fuzzification, a fuzzy inference system occurs, a defuzzification process is "moderate", when the viscosity of 926 fuzzification is "bad", and a density of 631.31 Kg/mL fuzzification "bad", fuzzy inference system occurs, defuzzification process occurs with "bad" results. To ensure that the results are accurate, the sample is taken to the BPOM which measures free fatty acids. From the BPOM test results converted to viscosity and density. In order to obtain an accurate conversion value between viscosity and density, it is recommended that a large number of samples be tested..Keywords: viscosity, density, fuzzy logic

scholarly journals Sistem Pakar Diagnosa Pulmonary TB Menggunakan Metode Fuzzy Logic

2018 ◽  
Vol 5 (2) ◽  
pp. 228-236
Author(s):  
Nita Novianti ◽  
Denny Pribadi ◽  
Rizal Amegia Saputra
Keyword(s):  
Quality Of Life ◽  
Infectious Disease ◽  
Fuzzy Logic ◽  
Expert System ◽  
Web Applications ◽  
Control Program ◽  
Web Based ◽  
Pulmonary Tb ◽  
Fuzzy Logic Expert System

AbstrakTuberkulosis paru merupakan salah satu penyakit menular kronis. Di Indonesia penyakit ini termasuk satu prioritas nasional untuk program pengendalian penyakit karena berdampak luas terhadap kualitas hidup dan ekonomi, serta sering mengakibatkan kematian. Untuk itu, dalam penelitian ini akan dilakukan analisa terhadap penyakit tb paru menggunakan logika fuzzy (fuzzy logic). Dalam penelitian ini informasi tentang tb_paru didapat dari para pakar dengan melakukan wawancara dengan pakar. Berdasarkan uraian diatas maka dibuat sebuah aplikasi sistem pakar untuk mendiagnosa tb_paru menggunakan fuzzy logic. Aplikasi sistem pakar berbasis web untuk mendiagnosa penyakit tb paru merupakan kebutuhan dari asisten dokter dan masyarakat umum. Oleh karena itu agar mendapatkan nilai informasi yang tepat dan cepat aplikasi sistem pakar ini akan dalam bentuk website. Dari 7 gejala yang ditimbulkan oleh penyakit tb paru ini dalam perhitungan fuzzy logic di dapat sebanyak 128 rule dan untuk perhitungan persentase keakuratannya sendiri sebesar 70,33%. Pembuatan aplikasi ini akan sangat membantu dalam melakukan diagnosa terhadap penderita tb paru. Kata Kunci: Sistem Pakar, Fuzzy Logic,  Penyakit TB Paru,  Aplikasi Web AbstractPulmonary Tuberculosis is one of an infectious disease chronic. In indonesia this disease including one national priorities to control program disease due affect widely to the quality of life and economic , and often resulting in death. For it , in this research will analysis to a disease pulmonary TB use fuzzy logic. Based on the description above will be made an application expert system to diagnose pulmonary TB use fuzzy logic. Expert system application with web based for disease diagnose is the needs of an assistant docter and the general public. Therefore To make gain the value of the most appropriate information and rapid application expert system this is going to in the form of websites .Of 7 symptoms that were brought about by disease pulmonary tuberculosis this in the calculation of fuzzy logic in be some 128 rule and for percentage accurate of 70,33%. The making of the application it would be very helpful in doing the diagnosis against patients pulmonary tuberculosis.Keywords : Expert System, Fuzzy Logic, Pulmonary Tb, Web Applications

scholarly journals Sistem Pakar Diagnosa Pulmonary TB Menggunakan Metode Fuzzy Logic

2018 ◽  
Vol 5 (2) ◽  
pp. 228-236
Author(s):  
Nita Novianti ◽  
Denny Pribadi ◽  
Rizal Amegia Saputra
Keyword(s):  
Quality Of Life ◽  
Infectious Disease ◽  
Fuzzy Logic ◽  
Expert System ◽  
Web Applications ◽  
Control Program ◽  
Web Based ◽  
Pulmonary Tb ◽  
Fuzzy Logic Expert System

AbstrakTuberkulosis paru merupakan salah satu penyakit menular kronis. Di Indonesia penyakit ini termasuk satu prioritas nasional untuk program pengendalian penyakit karena berdampak luas terhadap kualitas hidup dan ekonomi, serta sering mengakibatkan kematian. Untuk itu, dalam penelitian ini akan dilakukan analisa terhadap penyakit tb paru menggunakan logika fuzzy (fuzzy logic). Dalam penelitian ini informasi tentang tb_paru didapat dari para pakar dengan melakukan wawancara dengan pakar. Berdasarkan uraian diatas maka dibuat sebuah aplikasi sistem pakar untuk mendiagnosa tb_paru menggunakan fuzzy logic. Aplikasi sistem pakar berbasis web untuk mendiagnosa penyakit tb paru merupakan kebutuhan dari asisten dokter dan masyarakat umum. Oleh karena itu agar mendapatkan nilai informasi yang tepat dan cepat aplikasi sistem pakar ini akan dalam bentuk website. Dari 7 gejala yang ditimbulkan oleh penyakit tb paru ini dalam perhitungan fuzzy logic di dapat sebanyak 128 rule dan untuk perhitungan persentase keakuratannya sendiri sebesar 70,33%. Pembuatan aplikasi ini akan sangat membantu dalam melakukan diagnosa terhadap penderita tb paru. Kata Kunci: Sistem Pakar, Fuzzy Logic,  Penyakit TB Paru,  Aplikasi Web AbstractPulmonary Tuberculosis is one of an infectious disease chronic. In indonesia this disease including one national priorities to control program disease due affect widely to the quality of life and economic , and often resulting in death. For it , in this research will analysis to a disease pulmonary TB use fuzzy logic. Based on the description above will be made an application expert system to diagnose pulmonary TB use fuzzy logic. Expert system application with web based for disease diagnose is the needs of an assistant docter and the general public. Therefore To make gain the value of the most appropriate information and rapid application expert system this is going to in the form of websites .Of 7 symptoms that were brought about by disease pulmonary tuberculosis this in the calculation of fuzzy logic in be some 128 rule and for percentage accurate of 70,33%. The making of the application it would be very helpful in doing the diagnosis against patients pulmonary tuberculosis.Keywords : Expert System, Fuzzy Logic, Pulmonary Tb, Web Applications

Fuzzy Logic-Based Expert System for Evaluating Cake Quality of Freeze-Dried Formulations

2013 ◽  
Vol 102 (12) ◽  
pp. 4364-4374 ◽  
Author(s):  
Hjalte Trnka ◽  
Jian X. Wu ◽  
Marco Van De Weert ◽  
Holger Grohganz ◽  
Jukka Rantanen
Keyword(s):  
Fuzzy Logic ◽  
Expert System ◽  
Freeze Dried ◽  
Cake Quality

EXPERT SYSTEMS FUZZY DETERMINE COW’S SPERMATOZOAQUALITY WITH MAMDANI FIS METHOD IN BALAI INSEMINASI BUATAN DAERAH (BIBD) TUAH SAKATO PAYAKUMBUH

2017 ◽  
Vol 2 (2) ◽  
pp. 025
Author(s):  
Syopan Irawan ◽  
Devia Kartika ◽  
Dhio Saputra
Keyword(s):  
Fuzzy Logic ◽  
Expert System ◽  
Expert Systems ◽  
Microscopic Examination ◽  
Calculation Method ◽  
Sperm Quality ◽  
Suitable Method ◽  
Macroscopic Examination

Sperm in cattle also known as cement/sperma. In cattle semen decomposition comprises several types and descriptions of the determination of the quality of spermatozoa in cattle. Cattle sperm quality is decisive in determining the quality of the next generation of cows. During an investigation of cement macroscopic and microscopic examination. Macroscopic examination is the examination outline cement without the need for complex tools, while the microscopic examination aims to see the condition of the cement deeper and requires a fairly complete tools. To determine the quality of cement needed a suitable method is using fuzzy logic with mamdani method that will be implemented in an expert system fuzzy. From the example calculations have been done, with the example of a 600 kg cow, age 30, feed 60, and motion 2. Calculation method Mamdani system produces quality output by 72, that its quality is good.

scholarly journals Rationalization of servicing reefer containers in sea port area with taking into account risk influence

2014 ◽  
Vol 21 (2) ◽  
pp. 76-85 ◽  
Author(s):  
Ludmiła Filina-Dawidowicz
Keyword(s):  
Risk Factors ◽  
Fuzzy Logic ◽  
Expert System ◽  
Container Terminals ◽  
Risk Level ◽  
Port Area ◽  
Sea Ports ◽  
Fuzzy Logic Theory ◽  
Level Of Risk

Abstract This paper is aimed at presentation of a set of methods for rationalization of servicing containerized refrigerated cargoes in sea ports. During servicing reefer containers in port container terminals, take place various combinations of risk factors which can lead to loss of quality merits of cargoes contained in them. In the paper the risk factors capable of influencing quality of cargoes during their servicing in sea port, are identified, and the elaborated model for assessing risk level with the use of assumptions of fuzzy logic theory, is presented. Also, a simulation of servicing reefer containers in port, was performed. Moreover a prototype of an expert system which makes it possible to take correct decisions on servicing reefer containers in sea port, depending on impact level of risk factors, was proposed

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