聚焦换能器的焦域声压扫描是其声学特性计量的重要步骤,而传统的扫描路径测量效率较低,提出基于聚焦声场分布特征的扫描路径规划方法。首先给出了实验方案和原理,分析了聚焦换能器声场的焦域声场特性,然后对聚焦换能器进行有限元仿真分析,获得焦域声场的声压分布,根据声场同心圆分布特性,以焦点处为 0dB声压级,获得不同声压级对应区域作为水听器扫描特征区域。最后,搭建了实验系统,实验结果表明,-6dB的焦域长度和宽度等参数均与理论值、传统机械测量机构的测量值一致,保证了测量精度并且有效提高了测量效率。
Abstract
The focus area sound pressure scanning of a focused transducer is an important step in the measurement of its acoustic characteristics, while the traditional scanning path measurement is inefficient. A scanning path planning method based on the distribution characteristics of the focused sound field is proposed.First, the experimental scheme and principle are given, the focus area sound field characteristics of the focused transducer sound field are analyzed, and then finite element simulation analysis is carried out for the focusing transducer, according to the concentric circle distribution characteristics of the sound field, the corresponding areas of different sound pressure levels are obtained as the hydrophone scanning characteristic areas with the focus being 0dB sound pressure level. Finally, an experimental system is built,the experimental results show that the parameters such as -6dB focal length and width are consistent with the theoretical values and the measured values of traditional mechanical measuring mechanisms, the measurement accuracy is guaranteed and the measurement efficiency is effectively improved.
关键词
计量学 /
声压分布 /
聚焦换能器 /
焦域 /
扫描路径规划 /
手眼系统
Key words
metrology;sound pressure distribution;focus transducer;focal region;scanning path planning /
hand-eye system
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
［1］隋永杰. 超声探头声场参数测量的研究［D］. 北京: 北京化工大学, 2013.
［2］於炜力, 曹永刚, 郑慧峰, 等. 声透镜聚焦相控阵换能器的波束特性研究［J］. 传感技术学报, 2019, 32(7): 991-995.
Yu W L, Cao Y G, Zheng H F, et al. Study on beam characteristics of acoustic lens focusing phased array transducer ［J］. Journal of Sensing Technology, 2019, 32 (7): 991-995.
［3］李荣基, 赵鹏, 王月兵, 等. 球壳换能器电声效率测量方法研究［J］. 计量学报, 2020, 41(12): 1521-1528.
Li R J, Zhao P, Wang Y B, et al. Research on measurement method of electroacoustic efficiency of spherical shell transducer ［J］. Acta Metrologica Sinica, 2020, 41 (12): 1521-1528.
［4］周真祥. 超声换能器声场特性自动化检测技术的研究［D］. 杭州: 浙江大学, 2016.
［5］李国忠. 机器视觉将与多领域技术融合［J］. 现代制造, 2013(3): 11.
Li G Z. Machine vision will be integrated with multi domain technologies ［J］. Modern Manufacturing, 2013 (3): 11.
［6］彭圆, 郑慧峰, 董照诚, 等. 基于机器视觉的聚焦换能器焦点快速定位研究［J］. 计量学报, 2022, 43(10): 1313-1318.
Peng Y, Zheng H F, Dong Z C, et al. Research on fast focus location of focusing transducer based on machine vision ［J］. Acta Metrologica Sinica, 2022, 43 (10): 1313-1318.
［7］GB/T 16540—1996 声学在0.5~15MHz频率范围内的超声场特性及其测量水听器法［S］. 1996.
［8］郑维, 王昊,王洪斌. 动态环境下基于自适应步长Informed-RRT*和人工势场法的机器人混合路径规划［J］. 计量学报, 2023, 44(1): 26-34.
Zheng W, Wang H, Wang H B. Adaptive Step Size Informed-RRT* and Artificial Potential Field Algorithm for Hybrid Path Planning of Robot［J］. Acta Metrologica Sinica, 2023, 44(1): 26-34.
［9］Bazaz S A, Tondu B. Minimum time on-line joint trajectory generator based on low order spline method for industrial manipulators［J］. Robotics and Autonomous Systems, 1999, 29(4): 257-268.
［10］王馨蕊, 薛梓, 黄垚, 等. 基于空间位姿测量设备溯源的轨迹规划［J］. 计量学报, 2020, 41(10): 1184-1191.
Wang X R, Xue Z, Huang Y, et al. Trajectory Planning Based on Traceability of Spatial Pose Measurement Equipment［J］. Acta Metrologica Sinica, 2020, 41(10): 1184-1191.
［11］Boscariol P, Richiedei D, Tamelin I. Residual vibration suppression in uncertain systems: a robust trajectory planning structure modification method ［J］. Robot and Computer Integrated Manufacturing, 2022, 74: 102282.
［12］赵业和, 刘达新, 刘振宇, 等. 基于多种群竞争松鼠搜索算法的机械臂时间最优轨迹规划［J］. 浙江大学学报(工学版), 2022, 56(12): 2321-2329, 2402.
Zhao Y H, Liu D X, Liu Z Y, et al. Time optimal trajectory planning of manipulator based on multi-group competitive squirrel search algorithm ［J］. Journal of Zhejiang University (Engineering Edition), 2022, 56 (12): 2321-2329, 2402.
［13］杨锦涛, 姜文刚, 林永才. 工业机器人冲击最优的轨迹规划算法［J］. 科学技术与工程, 2014, 14(28): 70-75.
Yang Jintao, Jiang Wengang, Lin Yongcai Trajectory planning algorithm for optimal impact of industrial robots ［J］ Science, Technology and Engineering, 2014, 14(28): 70-75
［14］Han S, Shan X, Fu J, et al. Industrial robot trajectory planning based on improved pso algorithm ［J］. Journal of Physics: Conference Series, 2021, 1820(1): 012185 .
［15］Buschhaus A, Krusemark S, Karlidag E, et al. Universal fine interpolation algorithms for accuracy improvements of industrial robots［C］//Lisbon, Portugal: IEEE International Congress on Ultra Modern Telecommunications & Control Systems & Workshops, 2016: 356-362.
［16］赖啸, 刘勇. 笛卡尔和关节空间联合轨迹规划研究［J］. 机械传动, 2017, 41(1): 142-145.
Lai X, Liu Y. Joint Cartesian and Joint Space Trajectory Planning ［J］. Mechanical transmission, 2017, 41 (1): 142-145.
［17］Rossi C, Savino S. Robot trajectory planning by assigning positions and tangential velocities［J］. Robotics and Computer-Integrated Manufacturing, 2013, 29(1): 139-156.
［18］王丽燕. UR10工业机械臂动力学分析［D］. 杭州: 浙江理工大学, 2020.
［19］郑启强. 基于视觉引导的工业机器人贴标系统研究［D］. 福州: 福建工程学院, 2020.
［20］刘松国. 六自由度串联机器人运动优化与轨迹跟踪控制研究［D］. 杭州: 浙江大学, 2009.
基金
国家重点研发计划(2017YFF0205004);浙江省自然科学基金(LY17E050015,LQ20A040007);浙江省重点研发计划(2022C01002);浙江省质量技术监督系统科研计划(20180103);浙江省‘仪器科学与技术’重中之重学科人才培育项目(JL150506);浙江省教育厅科研资助(Y201942513);浙江省大学生科研创新团队资助(2021R409052)
PDF(105660 KB)
