Parameter optimization of laser displacement sensor based on particle swarm optimization algorithm
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摘要: 为了提高激光三角测距精度、优化传感器设计过程中的光学参量，采用数学建模和计算机辅助分析的方法，解析了激光三角测距传感器中的关键参量与测量系统各指标的关系，并采用一种基于粒子群算法的参量优化方法，得到符合系统优化要求的光学参量，进行了理论分析和验证。结果表明，在进行参量设计时，各参量相互牵制；确定了粒子群搜索空间和约束；在灵敏度Smin达到2.2386mm时，系统分辨力可达到2.8μm，且其它各参量取值符合系统要求，同时优化效率大大提高。该优化方法算法简单、操作方便。Abstract: In order to improve the precision of laser triangulation sensor and optimize the optical parameters of design process, through mathematical modeling and computer-aided analysis method, the relationship between key parameters of laser triangulation sensor and each index of measurement system was analyzed. A method of parameter optimization based on particle swarm algorithm was adopted. After theoretical analysis and experimental verification, the parameters to meet the requirements of optical system optimization were gotten. The results show that, the parameter is controlled by each other during designing. Search spaces and constraints of particle swarm are determined. When sensitivity Smin reaches 2.2386mm, the resolution of system can reach 2.8μm. Other parameters meet the system requirements, and the optimization efficiency is greatly improved. The optimization method is simple and convenient to operate.
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Figure 2. Relationship between each index and working distance
a—sensitivity b—resolution c—measurement range d—horizontal width
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Figure 3. Relationship between each index and working angle
a—sensitivity b—resolution c—measurement range d—horizontal width
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Figure 4. Relationship between each index and focal length of image lens
a—sensitivity b—resolution c—measurement range d—horizontal width
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Figure 6. Function iteration graph
a—sensitivity b—working distance c—working angle d—lens focal length
Table 1 The optimized results
parameter optimization result S 2.2386mm k 0.0028mm a 61.2862mm b 115.1680mm α 25.2900° β 14.2971° f 40.0000mm 
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