Estimation of Probability Density Functions of Damage Parameter for Valve Leakage Detection in Reciprocating Pump Used in Nuclear Power Plants

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• 作者：Jong Kyeom Lee ; Tae Yun Kim ; Hyun Su Kim ; Jang-Bom Chai ; Jin Woo Lee ; ^{jinwoolee@ajou.ac.kr" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Damage Parameter ; Diagnosis ; Mathematical Model ; Probability Density Function ; Reciprocating Pump ; Valve Leakage
• 刊名：Nuclear Engineering and Technology
• 出版年：2016
• 出版时间：October 2016
• 年：2016
• 卷：48
• 期：5
• 页码：1280-1290
• 全文大小：1949 K

文摘

This paper presents an advanced estimation method for obtaining the probability density functions of a damage parameter for valve leakage detection in a reciprocating pump. The estimation method is based on a comparison of model data which are simulated by using a mathematical model, and experimental data which are measured on the inside and outside of the reciprocating pump in operation. The mathematical model, which is simplified and extended on the basis of previous models, describes not only the normal state of the pump, but also its abnormal state caused by valve leakage. The pressure in the cylinder is expressed as a function of the crankshaft angle, and an additional volume flow rate due to the valve leakage is quantified by a damage parameter in the mathematical model. The change in the cylinder pressure profiles due to the suction valve leakage is noticeable in the compression and expansion modes of the pump. The damage parameter value over 300 cycles is calculated in two ways, considering advance or delay in the opening and closing angles of the discharge valves. The probability density functions of the damage parameter are compared for diagnosis and prognosis on the basis of the probabilistic features of valve leakage.