scholarly journals An On-Line Monitoring Device for Dissolved Gas in Transformer Oil Based on Spectrum Technology

Author(s):  
Qiang Gao ◽  
Jicheng Dai ◽  
Feng Yuan ◽  
Fenghou Pan ◽  
Zailin Li
2021 ◽  
Vol 2125 (1) ◽  
pp. 012072
Author(s):  
Yanping Li ◽  
Yong Li

Abstract Measuring the content of dissolved gas components in transformer insulating oil by gas chromatography is an important means to judge the internal potential faults of oil filled electrical equipment in the process of operation supervision. The necessary work skills of power grid operators include the ability to detect the content of dissolved gas in transformer oil and judge the operation state of transformer. This paper introduces a preparation method and equipment of transformer standard oil. It can quickly prepare standard oils with various gas component contents. The standard oil quantity value is accurate, the data stability period is greater than 90 days, and the uncertainty is less than 5%. The equipment can be used for training and evaluation of transformer oil gas chromatographic analysis practitioners and calibration of transformer oil on-line gas chromatograph.


2011 ◽  
Vol 194-196 ◽  
pp. 2480-2486 ◽  
Author(s):  
Wei Gen Chen ◽  
Mai Hao

Power transformer on-line monitoring on dissolved gas in oil is one of the effective and technical means to achieve the transformer state detection and fault diagnosis, and oil-gas permeability is one of the core technologies to implement transformer on-line monitoring. The traditional methods of oil-gas separation such as vacuum method and mechanical oscillation method were unable to satisfy the requirements of transformer on-line monitoring; and the methods which were used commonly in recent years, like dynamic headspace separation, corrugated tube, carrier gas elution etc, have a high rate of gas-separation and have already been used in some on-line monitoring products. However, the problems still exist: easy formation of oil pollution, so the oil can not be recycled and the device structure is relatively complex. This paper based on the separation principle of polymer membrane, proposes mixed hollow fiber membrane made by polytetrafluoroethylene (PTFE) and polyhexafluoropropylene (PHFP), and designs an oil-gas separation test platform formed by the storage tank, oil-gas permeability tank, temperature controller and gas chromatographic analyzer etc, does laboratory research on the oil-gas permeability of the mixed hollow fiber membrane at different temperatures. The results show that, the permeability of the mixed hollow fiber membrane is obviously better than the commonly used single fluoride film or rubber film, seven fault gases H2, CO, CO2, CH4, C2H6, C2H4, and C2H2 can be separated efficiently form transformer oil within 24 hours. More to the point, the equilibrium time is short, the gas permeability is high and the test platform structure is simple, all of these advantages provide a strong guarantee for the development of on-line monitoring technology on dissolved gas in transformer oil.


2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Nitin K. Dhote ◽  
Jagdish B. Helonde

Dissolved gas analysis (DGA) of transformer oil has been one of the most reliable techniques to detect the incipient faults. Many conventional DGA methods have been developed to interpret DGA results obtained from gas chromatography. Although these methods are widely used in the world, they sometimes fail to diagnose, especially when DGA results fall outside conventional methods codes or when more than one fault exist in the transformer. To overcome these limitations, the fuzzy inference system (FIS) is proposed. Two hundred different cases are used to test the accuracy of various DGA methods in interpreting the transformer condition.


2014 ◽  
Vol 519-520 ◽  
pp. 98-101
Author(s):  
De Wen Wang ◽  
Zhi Wei Sun

Dissolved gas analysis (DGA) in oil is an important method for transformer fault diagnosis. This paper use random forest parallelization algorithm to analysis the dissolved gases in transformer oil. This method can achieve a fast parallel fault diagnosis for power equipment. Experimental results of the diagnosis of parallelization of random forest algorithm with DGA samples show that this algorithm not only can improve the accuracy of fault diagnosis, and more appropriate for dealing with huge amounts of data, but also can meet the smart grid requirements for fast fault diagnosis for power transformer. And this result also verifies the feasibility and effectiveness of the algorithm.


Sign in / Sign up

Export Citation Format

Share Document