Ship propeller air entrapment identification method based on evidence reasoning rules and self-adaptive lifting

• Main Authors: XIONG LIUQING, SHENG CHENXING, LIAO LINHAO, LIN ZHIGUO, XU XIAOBIN, XU XIAOJIAN, GAO HAIBO
• Format: Patent
• Language: Chinese; English
• Published: 05.11.2019
• Subjects: CALCULATING; COMPUTING; COUNTING; HANDLING RECORD CARRIERS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS

The invention relates to a ship propeller air entrapment identification method based on evidence reasoning rules and adaptive lifting, and the method comprises the steps: obtaining a three-phase current root-mean-square value and a torque characteristic value from a ship electric propulsion system frequency converter in real time, determining the degree of an air entrapment effect caused by a severe sea condition according to a propeller torque loss coefficient, and setting three levels; firstly, an input feature reference value of each evidence reasoning rule weak learner is given through a K-means clustering method; establishing a fault reliability distribution matrix, converting the input into diagnosis evidence by using the matrix, calculating a reliability factor of the diagnosis evidence, fusing the evidence according to the reliability factor, and estimating the propeller air entrapment effect grade from a fusion result; counting the precision of the current weak learner, and calculating the learning c