摘要
基于模糊聚类的放射设备自动控制方法,对检测数据的收敛能力较差,为此研究基于改进粒子群算法的放射科设备自动化控制方法。该方法利用改进粒子群算法的多维度变量,描述控制目标,通过决策变量可行域和规则函数,设置放射设备约束条件;依赖内部时间序列、外部时钟体系合并采样单元,以同步跳变的形式采集检测数据;投入改进粒子群算法,实现动态双种群粒子优化,实现该设备的自动化控制。实验结果表明:与传统的控制方法相比,所提出方法的反应时间短,收敛指数提高了0.47。由此可见,所研究的方法更适用于放射科设备的日常管控。
The automatic control method of radiology equipment based on fuzzy clustering has poor convergence ability to the detection data.Therefore,an automatic control method of radiology equipment based on improved particle swarm optimization is studied.In this method,the multi-dimensional variable of the improved particle swarm optimization algorithm is used to describe the control target,and the constraint condition of the radiological equipment is set through the feasible region of the decision variable and the rule function.Depending on the combination of internal time series and external clock system,the detection data is collected in the form of synchronous hopping.The improved particle swarm optimization algorithm is applied to realize the dynamic two-population particle optimization and realize the automatic control of the equipment.The experimental results show that compared with the traditional control method,the proposed method has a shorter reaction time and a higher convergence index of 0.47.It can be seen that the studied method is more suitable for daily control of radiology equipment.
作者
吴秀
李晓琴
苏健
孙小莉
WU Xiu;LI Xiaoqin;SU Jian;SUN Xiaoli(Second,affiliated Hospital of PLA Army military Medical University,Chongqing 400037,China)
出处
《自动化与仪器仪表》
2020年第7期175-178,共4页
Automation & Instrumentation
基金
社会民生专项(No.csts2015shmszx120088)。
关键词
改进粒子群算法
放射科设备
自动化控制
收敛
improved particle swarm optimization
radiology equipment
automatic control
convergence
