Implementation of ANFIS and FIS-ID3 in Transformer Oil-Paper Assessment

The influence of the periodicity of diagnostic measurements on the operational state of high-voltage transformers is considered. Examples of defects of switching devices of converter transformers and methods for their detection are given. The rationale for the importance of recognition of defects at an early stage of their occurrence is given. The influence of the multiplicity of overvoltages on the service life of converter transformers in the aluminum industry is investigated. Based on the analysis of the service life of converter transformers of one of the powerful aluminum plants, where 83% of converter transformers have exhausted their standard service life, it is shown that in 40% of cases it would be possible to avoid their failures, with timely detection and elimination of emerging defects. Examples of defects of OLR (on-load regulators) of converter transformers and methods for their detection are given. The importance of recognition of defects at an early stage of their occurrence is substantiated. A method for chromatographic analysis of dissolved gases in transformer oil has been developed for the qualitative determination of defects and ways to eliminate them. Examples of diagnostics of converter transformers at operating voltage and working load are given, providing the best quality operational characteristics of converter transformers. The periodicity of diagnostic measurements and the reduction of defects and failures has been substantiated. The question of diagnosing the state of the converter transformer TDNP-40000/10 at an enterprise of the aluminum industry is investigated. Currently, diagnostic methods are being developed based on chromatographic analysis of dissolved gases in transformer oil. The presented method of evaluating the operating parameters of transformers allows for the safe operation of high-voltage transformers and enables to increase the reliability of the power supply scheme of aluminum industry plants.

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Effect of Powder-Mixed Dielectric on EDM Process Performance

Engineering and Technology Journal ◽

10.30684/etj.v38i8a.554 ◽

2020 ◽

Vol 38 (8A) ◽

pp. 1226-1235

Author(s):

Safa R. Fadhil ◽

Shukry. H. Aghdeab

Keyword(s):

Silicon Carbide ◽

High Speed ◽

Electrical Discharge Machining ◽

Removal Rate ◽

High Speed Steel ◽

Transformer Oil ◽

Dielectric Fluid ◽

Peak Current ◽

Powder Concentration ◽

Pulse On Time

Electrical Discharge Machining (EDM) is extensively used to manufacture different conductive materials, including difficult to machine materials with intricate profiles. Powder Mixed Electro-Discharge Machining (PMEDM) is a modern innovation in promoting the capabilities of conventional EDM. In this process, suitable materials in fine powder form are mixed in the dielectric fluid. An equal percentage of graphite and silicon carbide powders have been mixed together with the transformer oil and used as the dielectric media in this work. The aim of this study is to investigate the effect of some process parameters such as peak current, pulse-on time, and powder concentration of machining High-speed steel (HSS)/(M2) on the material removal rate (MRR), tool wear rate (TWR) and the surface roughness (Ra). Experiments have been designed and analyzed using Response Surface Methodology (RSM) approach by adopting a face-centered central composite design (FCCD). It is found that added graphite-silicon carbide mixing powder to the dielectric fluid enhanced the MRR and Ra as well as reduced the TWR at various conditions. Maximum MRR was (0.492 g/min) obtained at a peak current of (24 A), pulse on (100 µs), and powder concentration (10 g/l), minimum TWR was (0.00126 g/min) at (10 A, 100 µs, and 10 g/l), and better Ra was (3.51 µm) at (10 A, 50 µs, and 10 g/l).

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Influence of g-Al2O3 nanoparticles on radiolysis of transformer oil containing polychlorobiphenyl impurities

Physics and Chemistry of Materials Treatment ◽

10.30791/0015-3214-2020-1-20-25 ◽

2020 ◽

pp. 20-25

Author(s):

Z.I. Iskenderova ◽

Keyword(s):

Transformer Oil ◽

Al2o3 Nanoparticles

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EFFECT OF METALLIC FUEL NATURE ON COMBUSTION CHARACTERISTICS OF AMMONIUM PERCHLORATE / BINDER / METAL COMPOSITE SOLID PROPELLANTS

NONEQUILIBRIUM PROCESSES: RECENT ACCOMPLISHMENTS ◽

10.30826/nepcap9a-30 ◽

2020 ◽

Author(s):

V. A. Poryazov ◽

◽

O. G. Glotov ◽

V. A. Arkhipov ◽

G. S. Surodin ◽

...

Keyword(s):

Ammonium Perchlorate ◽

Combustion Process ◽

Experimental Information ◽

Combustion Characteristics ◽

Transformer Oil ◽

Metal Composite ◽

Butadiene Rubber ◽

Solid Propellants ◽

Metallic Fuel ◽

Composite Solid Propellants

The goal of this research is to obtain experimental information about combustion characteristics of the composite propellant containing various metallic fuels. The propellant formulations contained two fractions of ammonium perchlorate (64.6%), inert binder (19.7%) - butadiene rubber SKD plastized with transformer oil, and metal fuel (15.7% of aluminum ASD-4, ASD-6, Alex; boron; aluminum diboride; aluminum dodecaboride; some mixtures of above listed ingredients). Experimental information will be used further as a background to develop the physical and mathematical model of combustion process.

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Impact of Concentration of Nanoparticles on Characteristics of Transformer Oil

Journal of Nano- and Electronic Physics ◽

10.21272/jnep.12(4).04019 ◽

2020 ◽

Vol 12 (4) ◽

pp. 04019-4-04019-4

Author(s):

Sumanta Kumar Tripathy ◽

◽

M. Madeen Kumar ◽

Keyword(s):

Transformer Oil

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FURTHER CONTRIBUTION FOR EVALUATING THE AGING OF TRANSFORMER OIL OF POWER TRANSFORMER

JES. Journal of Engineering Sciences ◽

10.21608/jesaun.2015.115168 ◽

2015 ◽

Vol 43 (2) ◽

pp. 211-226

Author(s):

Sobhy S. Dessouky ◽

Adel El Faraskoury ◽

Sherif Ghoneim ◽

Ahmed Haassan

Keyword(s):

Power Transformer ◽

Transformer Oil

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Feasibility of the novel utilization of modified Azadirachta Indica seed oil as transformer oil

10.21748/am20.79 ◽

2020 ◽

Author(s):

Chinedu Agu ◽

Matthew Menkiti ◽

Albert Agulanna ◽

Emeka Udokporo

Keyword(s):

Azadirachta Indica ◽

Seed Oil ◽

Transformer Oil ◽

The Novel

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Transformer Oil Quality Assessment Using Random Forest with Feature Engineering

Energies ◽

10.3390/en14071809 ◽

2021 ◽

Vol 14 (7) ◽

pp. 1809

Author(s):

Mohammed El Amine Senoussaoui ◽

Mostefa Brahami ◽

Issouf Fofana

Keyword(s):

Machine Learning ◽

Random Forest ◽

Oil Quality ◽

Principal Component ◽

Condition Assessment ◽

Classification Performance ◽

Transformer Oil ◽

Classification Model ◽

Insulation Degradation ◽

Transformer Oils

Machine learning is widely used as a panacea in many engineering applications including the condition assessment of power transformers. Most statistics attribute the main cause of transformer failure to insulation degradation. Thus, a new, simple, and effective machine-learning approach was proposed to monitor the condition of transformer oils based on some aging indicators. The proposed approach was used to compare the performance of two machine-learning classifiers: J48 decision tree and random forest. The service-aged transformer oils were classified into four groups: the oils that can be maintained in service, the oils that should be reconditioned or filtered, the oils that should be reclaimed, and the oils that must be discarded. From the two algorithms, random forest exhibited a better performance and high accuracy with only a small amount of data. Good performance was achieved through not only the application of the proposed algorithm but also the approach of data preprocessing. Before feeding the classification model, the available data were transformed using the simple k-means method. Subsequently, the obtained data were filtered through correlation-based feature selection (CFsSubset). The resulting features were again retransformed by conducting the principal component analysis and were passed through the CFsSubset filter. The transformation and filtration of the data improved the classification performance of the adopted algorithms, especially random forest. Another advantage of the proposed method is the decrease in the number of the datasets required for the condition assessment of transformer oils, which is valuable for transformer condition monitoring.

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Electrical Breakdown Mechanism of Transformer Oil with Water Impurity: Molecular Dynamics Simulations and First-Principles Calculations

Crystals ◽

10.3390/cryst11020123 ◽

2021 ◽

Vol 11 (2) ◽

pp. 123

Author(s):

Bin Cao ◽

Ji-Wei Dong ◽

Ming-He Chi

Keyword(s):

Molecular Dynamics ◽

Thermal Diffusion ◽

First Principles ◽

Electrical Breakdown ◽

Transformer Oil ◽

Water Molecules ◽

Conducting Channel ◽

Breakdown Mechanism ◽

Water Impurity ◽

Dynamics Simulations

Water impurity is the essential factor of reducing the insulation performance of transformer oil, which directly determines the operating safety and life of a transformer. Molecular dynamics simulations and first-principles electronic-structure calculations are employed to study the diffusion behavior of water molecules and the electrical breakdown mechanism of transformer oil containing water impurities. The molecular dynamics of an oil-water micro-system model demonstrates that the increase of aging acid concentration will exponentially expedite thermal diffusion of water molecules. Density of states (DOS) for a local region model of transformer oil containing water molecules indicates that water molecules can introduce unoccupied localized electron-states with energy levels close to the conduction band minimum of transformer oil, which makes water molecules capable of capturing electrons and transforming them into water ions during thermal diffusion. Subsequently, under a high electric field, water ions collide and impact on oil molecules to break the molecular chain of transformer oil, engendering carbonized components that introduce a conduction electronic-band in the band-gap of oil molecules as a manifestation of forming a conductive region in transformer oil. The conduction channel composed of carbonized components will be eventually formed, connecting two electrodes, with the carbonized components developing rapidly under the impact of water ions, based on which a large number of electron carriers will be produced similar to “avalanche” discharge, leading to an electrical breakdown of transformer oil insulation. The water impurity in oil, as the key factor for forming the carbonized conducting channel, initiates the electric breakdown process of transformer oil, which is dominated by thermal diffusion of water molecules. The increase of aging acid concentration will significantly promote the thermal diffusion of water impurities and the formation of an initial conducting channel, accounting for the degradation in dielectric strength of insulating oil containing water impurities after long-term operation of the transformer.

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