Application of C
 6
 F
 12
 O/CO
 2
 mixture in 10 kV medium‐voltage switchgear

Tian, Shuangshuang; Zhang, Xiaoxing; Xiao, Song; Ji, Zhang; Chen, Qi; Li, Yi

doi:10.1049/iet-smt.2018.5482

Cited by 65 publications

(27 citation statements)

References 31 publications

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“…Given the working pressure and liquefaction temperature requirements (−5 • C) of MV switchgears [32], the total gas pressure and content of C 6 F 12 O in the experiment were fixed to 0.2 MPa and 5%, respectively. The breakdown voltage of 5% C 6 F 12 O-95% N 2 gas mixture at 0.2 MPa is about 1.05 times that of 10% SF 6 -90% N 2 [29].…”

Section: Experimental and Analytical Methodsmentioning

confidence: 99%

Compatibility between C6F12O–N2 Gas Mixture and Metal Used in Medium-Voltage Switchgears

et al. 2019

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C6F12O has been introduced as the potential alternative gas to SF6 because of its excellent insulation properties and great eco-friendly performance. Considering that C6F12O may react with the internal materials of switchgears in practical applications, its compatibility with metal materials must be tested to evaluate its long-term application possibilities. In this work, the compatibility of C6F12O–N2 gas mixtures with aluminum and copper was tested at different temperatures by setting up a heat-aging reaction platform between the gas and each metal. The metal surface morphology and gas composition before and after the reaction were compared and analyzed. The results show that the surface color of the copper sheet changed considerably, and the corrosion degree of the surface deepened with the increase of temperature. The decomposition of C6F12O was also promoted. In contrast, aluminum did not react severely with the gas mixture. The compatibility of the gas mixture with aluminum was generally better than that of copper.

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Section: Experimental and Analytical Methodsmentioning

confidence: 99%

Compatibility between C6F12O–N2 Gas Mixture and Metal Used in Medium-Voltage Switchgears

et al. 2019

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“…From Equation (25), the bilinear-parameter model is transformed into linear-parameter form and the number of parameter in * is n 2 −1. The parameters appear explicitly in * and can be estimated simultaneously.…”

Section: The Ps-lsi Algorithmmentioning

confidence: 99%

“…The proposed algorithms can be applied to finding the mathematical models of many engineering systems. 25,26 Briefly, the rest of this article is organized as follows. Section 2 describes the identification problem for nonlinear models with bilinear terms and the AM-LSI method is derived for comparison purpose.…”

Section: Introductionmentioning

confidence: 99%

Maximum likelihood least squares‐based iterative methods for output‐error bilinear‐parameter models with colored noises

Chen

Ding

Lin

et al. 2020

Intl J Robust & Nonlinear

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This article is concerned with the parameter identification of output-error bilinear-parameter models with colored noises from measurement data. An auxiliary model least squares-based iterative method is developed through the overparameterization model. It examines the difficulty of estimating the overparameterized vector, which usually presents a heavy computational burden in the identification process. To overcome this drawback, a parameter separation technique is introduced and the nonlinear model is reformulated as a refined identification model through eliminating the crossmultiplying terms. In this regard, a parameter separation least squares-based iterative (PS-LSI) algorithm is derived by avoiding estimating the redundant parameters. On the basis of the PS-LSI algorithm, we derive a maximum likelihood least squares-based iterative method to further improve the numerical accuracy. The identification is dependent on the formulation of a pseudolinear regression relationship, which contains two linear prefilters constructed from the system and noise models. The performance of this proposed method is confirmed by the numerical simulations as well as direct comparisons with other existing algorithms.

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“…Using the multi-innovation identification theory, a weighted multi-innovation stochastic gradient algorithm was derived for Hammerstein nonlinear systems. 26 Other techniques such as the particle filter 27 can be applied to model some practical systems 28,29 and to solve some engineering problems. 30,31 This article completely differs from Reference 32 which applied the decomposition to the linear models and presented a two-stage LS algorithm, while this article applies the decomposition to nonlinear ExpAR models and presents a new two-stage multi-innovation algorithm.…”

Section: Introductionmentioning

confidence: 99%

Two‐stage recursive identification algorithms for a class of nonlinear time series models with colored noise

Ding

Gan

et al. 2020

Intl J Robust & Nonlinear

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This article concentrates on the recursive identification algorithms for the exponential autoregressive model with moving average noise. Using the decomposition technique, we transform the original identification model into a linear and nonlinear subidentification model and derive a two-stage least squares (LS) extended stochastic gradient (ESG) algorithm. In order to improve the parameter estimation accuracy, we employ the multi-innovation identification theory and develop a two-stage LS multi-innovation ESG algorithm. A simulation example is provided to test the effectiveness of the proposed algorithms.

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Application of C ₆ F ₁₂ O/CO ₂ mixture in 10 kV medium‐voltage switchgear

Cited by 65 publications

References 31 publications

Compatibility between C6F12O–N2 Gas Mixture and Metal Used in Medium-Voltage Switchgears

Compatibility between C6F12O–N2 Gas Mixture and Metal Used in Medium-Voltage Switchgears

Maximum likelihood least squares‐based iterative methods for output‐error bilinear‐parameter models with colored noises

Two‐stage recursive identification algorithms for a class of nonlinear time series models with colored noise

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Application of C 6 F 12 O/CO 2 mixture in 10 kV medium‐voltage switchgear

Cited by 65 publications

References 31 publications

Compatibility between C6F12O–N2 Gas Mixture and Metal Used in Medium-Voltage Switchgears

Compatibility between C6F12O–N2 Gas Mixture and Metal Used in Medium-Voltage Switchgears

Maximum likelihood least squares‐based iterative methods for output‐error bilinear‐parameter models with colored noises

Two‐stage recursive identification algorithms for a class of nonlinear time series models with colored noise

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Product

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Application of C ₆ F ₁₂ O/CO ₂ mixture in 10 kV medium‐voltage switchgear