The aim of this paper is to optimize the performance of the aircraft landing gear system’s test point layout. To achieve this, we propose a method that combines the use of a Multi-Signal Flow Graph and the Harmony Search Algorithm. First, a multi-signal flow graph model is built using the object's structure as a basis. Then a dependency matrix of tests and failure modes is generated. The harmony search algorithm is combined with the matrix to find the best test point layout according to the flexible demands of fault detection rate (FDR), fault isolation rate (FIR), and number of test points. Based on the traditional harmony search algorithm, a new control parameter, improvisation probability (IR), is introduced for the “improvisation” part to generate new harmonies. When this algorithm is used to solve binary combinatorial optimization problems, its global optimization-seeking ability and solving speed are enhanced by varying the pitch adjusting rate (PAR) according to the number of generations. To further show how successful this technology is, it is also applied to an actual airplane landing gear system.

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Test Point Layout Optimization Based on Multi-Signal Flow Graph and Harmony Search Algorithm

  • Xin Luo,
  • Zixuan You,
  • Hongrui Xiong,
  • Zhanbao Gao

摘要

The aim of this paper is to optimize the performance of the aircraft landing gear system’s test point layout. To achieve this, we propose a method that combines the use of a Multi-Signal Flow Graph and the Harmony Search Algorithm. First, a multi-signal flow graph model is built using the object's structure as a basis. Then a dependency matrix of tests and failure modes is generated. The harmony search algorithm is combined with the matrix to find the best test point layout according to the flexible demands of fault detection rate (FDR), fault isolation rate (FIR), and number of test points. Based on the traditional harmony search algorithm, a new control parameter, improvisation probability (IR), is introduced for the “improvisation” part to generate new harmonies. When this algorithm is used to solve binary combinatorial optimization problems, its global optimization-seeking ability and solving speed are enhanced by varying the pitch adjusting rate (PAR) according to the number of generations. To further show how successful this technology is, it is also applied to an actual airplane landing gear system.