CAJ | 학술논문

测试节点优化是电路板测试诊断设计优化过程中的一个基本问题,属于经典的N-P难题,但目前用于测试点优化的算法存在搜索速度慢、不收敛等问题,因此提出一种基于遗传粒子群优化算法.该方法通过建立电路测试节点的"故障-测试"矩阵,用遗传算法对数学模型进行优化,并采用粒子群算法搜索实现了快速求解.与传统方法相比较,该方法搜索速度快,优化效果明显,已在工程实践中得到应用.
측시절점우화시전로판측시진단설계우화과정중적일개기본문제,속우경전적N-P난제,단목전용우측시점우화적산법존재수색속도만、불수렴등문제,인차제출일충기우유전입자군우화산법.해방법통과건립전로측시절점적"고장-측시"구진,용유전산법대수학모형진행우화,병채용입자군산법수색실현료쾌속구해.여전통방법상비교,해방법수색속도쾌,우화효과명현,이재공정실천중득도응용.
Test node optimization problem is a key problem of diagnostic design for circuit,which belongs to an N-P completeness problem.Algorithms being applied for the test node optimization problem have some problems such as slow searching speed and no convergence,so a kind of method based on genetic particle swarm optimization algorithm was presented to solve the problem.It optimizes the test node's "fault-test" matrix by genetic algorithm and searches quickly by particle swarm optimization.Searching with the method is faster than traditional methods,and the optimal results are also better.The method has been used in engineering practice.