量子粒子群算法在可燃性气体检测中的应用

The Application of Quantum-behaved Particle Swarm Optimization in the Combustible Gas Detection

可燃气体检测报警器是现代工业现场中必不可少的安全仪表,如何有效地布置可燃气体检测报警器是感器技术发展领域的一个重要课题。本文把量子粒子群算法(QPSO)引用到大型工业现场可燃气体检测报警器的布置方案设计中,在顾及生产安全的前提下综合考虑到投资和维护的成本。实验结果表明,该算法能进行有效的布点设计,并在寻优能力和收敛速度方面都取得了良好的效果。

Combustible gas detection and alarm is absolutely necessary safety Instruments in modern industry,so it is very important to layout the sensor in a reasonable way.To combine with the safety and cost,the thesis makes a thorough research on Quantum-behaved Particle Swarm Optimization（QPSO） for the arrangement of the sensor.It is validated experimentally that this algorithm achieved much better result both in convergence speed and optimization capabilities in comparison with other algorithms.