Details

Autor(en) / Beteiligte

• Tang, Ju
• Zeng, Fuping
• Pan, Jianyu
• Zhang, Xiaoxing
• Yao, Qiang
• He, Jianjun
• Hou, Xingzhe

Titel

Correlation analysis between formation process of SF6 decomposed components and partial discharge qualities

Ist Teil von

• IEEE transactions on dielectrics and electrical insulation, 2013-06, Vol.20 (3), p.864-875

Ort / Verlag

New York: IEEE

Erscheinungsjahr

2013

Quelle

IEEE Xplore

Beschreibungen/Notizen

• To obtain relationship between concentration of SF 6 decomposed characteristic components (or their concentration ratio) during the formation process and partial discharge qualities and pulse repetition rate, this paper used needle-plate electrode to simulate outthrust insulation fault and conducted a serial of experiments. First, the SF 6 decomposition characteristic under different PD strengths is obtained. Then this paper defines average discharge qualities per second as Q SEC . It considers both apparent discharge qualities and discharge pulse repetition rate, and analyzes the relation feature between SF 6 decomposition characteristic (both concentration of component and their effective formation rates RRMS) and Q SEC . Besides, it proposes C(SO 2 F 2 )/C(SOF 2 ) as the energy characteristic ratio (ER) to represent PD energy, and defines the effective energy characteristic ratio as (ER RMS ). Moreover, it achieves the inner correlation feature between Q SEC and all the characteristic component concentration, the RRMS of each characteristic component and ERRMS. The results show that: since number of C atoms from stainless steel surface and content of trace H 2 O and O 2 in gas chamber were limited, both decomposed component concentration and component concentration ratio accords with the famous "Logistic Population Model" growth trend in ecology, which means they present "S"-curve increase with Q SEC . The proposed ER can effectively indicate the amount of PD energy and the defined ER RMS can objectively reveal the variance regularity of PD energy with Q SEC . Hence, the correlation mathematic formula between ER RMS and Q SEC is obtained and ER RMS can be used as the new characteristic parameter to represent PD energy. It establishes the foundation for the further fault diagnosis research.