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引用本文:卢宏博,李明智,李尚远,孙天泽,曲春虎,曲文龙.扇贝苗规格识别与计数统计装置的设计研究[J].海洋科学,2021,45(2):59-67.
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扇贝苗规格识别与计数统计装置的设计研究
卢宏博, 李明智, 李尚远, 孙天泽, 曲春虎, 曲文龙
大连海洋大学大学生"蔚蓝"科技创新创业基地, 辽宁 大连 116023
摘要:
本文针对目前底播扇贝苗种时,在海上规格识别与计数统计用工量大、劳动强度高、破损率高及统计误差大等问题,设计了扇贝苗规格识别与计数统计装置,该装置主要由初级分拣机构、差速排队传送装置和规格识别与计数统计系统3部分组成。为确定影响贝苗规格识别与计数统计装置准确性的因素,建立了5因素4水平的正交实验进行分析验证,并确定了扇贝苗规格识别与计数统计装置的最佳组合参数为:入料口尺寸为40×25 mm,传送带电机转速125 r·min–1,姿态调节机构弧度20°,姿态调节机构距传送带末端距离40 mm,规格识别间隔为17 ms、25 ms。在验证性试验中,装置平均的识别计数准确率为94.4%,因此可见本装置稳定性较好,可为扇贝苗海上收购、底播一体化提供技术支撑。
关键词:  扇贝苗  规格识别  计数统计  PLC  光电传感器
DOI:10.11759/hykx20200719001
分类号:S985.3*6
基金项目:国家贝类产业技术体系设施养殖岗位(CARS-48);辽宁省大学生创新创业训练计划项目(201910158094)
Design of scallop seedling specification recognition and counting device
LU Hong-bo, LI Ming-zhi, LI Shang-yuan, SUN Tian-ze, QU Chun-hu, QU Wen-long
Students Cerulean Sci-tech Innovation Entrepreneurship Base of Liaoning Province, Dalian Ocean University, Dalian 116023, China
Abstract:
In this study, considering the problems of large labor, high labor intensity, high breakage rate, and large statistical error in the marine specification identification and counting statistics of bottom-sown scallop seedlings, a device for identifying and counting the scallop seedlings was designed; the device consisted of three parts: primary sorting mechanism, differential queuing conveyor and specification identification system, and counting statistics system. To determine the factors affecting the device accuracy for identifying and counting shellfish seedlings, five factors and four levels were established for orthogonal test analysis and verification, and the best process parameters of the device for shellfish seedling classification were determined. The size of the feeding port was 40 mm×25 mm, the rotating speed of the conveyor belt motor was 125 r·min-1, the radian of the attitude-adjusting mechanism was 20, the distance between the attitude-adjusting mechanism and the end of the conveyor belt was 4 mm, and the interval for the shellfish seedling identification was 17 ms and 25 ms. In the verification test, the average recognition and counting accuracy was 94.4%; thus, the device has good stability and can therefore provide technical support for the integration of scallop seedling acquisition and the bottom sowing at sea.
Key words:  scallop seedling  specification identification  counting statistics  PLC  photoelectric sensor
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