菲律宾蛤仔机械化采捕行走机构及避障系统设计
发布时间：2019-05-16 07:33
【摘要】：我国是贝类养殖大国,海洋贝类养殖产量约占海水养殖总产量的80%并且贝类的年产量逐年增长,2015年我国海水养殖贝类产量约1316.55万t。其中贝类采捕是贝类养殖的重要环节,随着贝类产量的增加传统的采捕方式暴露出了一些问题。传统作业方式因海底环境的多变性与未知性对海底环境和采捕设备造成了一定程度的影响。为海下采捕设备添加智能避障技术将有效地提高工作效率,减小对海底贝类养殖区生态环境和设备的损害。针对海下采捕设备工作过程中对工作路线、工作环境不可预测造成采捕效率下降、设备损坏以及海底贝类养殖区生态环境破坏等问题,本文开展了贝类采捕海下智能避障系统的研究。论文主要完成了采捕设备行走系统设计和采捕设备避障系统设计,并对采捕设备行走避障系统初步试验研究。采捕设备避障行走系统设计,通过分析计算海底工作环境中的各种参数,如海底底质、接地比压等泥土性质,并结合采捕行走机构自身因素,选定履带式行走机构作为采捕设备行走系统的行走方式;考虑工作过程中海底环境和噪音干扰等状况,选用超声波探测为该采捕设备的主要探测方式。针对海下特殊工作环境设计完成了采捕设备小型样机行走系统的硬件部分,包括驱动轮、支重轮、导向轮、支架等结构,整体尺寸为60cm×38cm×32cm、重约30kg。采捕设备避障系统采用了超声波探测、红外线等传感器,以及LabVIEW软件和NI 9201模拟输入模块、NI 9265模拟输出模块、NI cDAQ-9178机箱等硬件设备,快速建立自动测试程序进行数据采集、数据处理、数据分析以及信号滤波等处理,完成对采捕设备预定路线上的障碍物信息采集处理。系统设计的软件控制部分主要包括障碍物探测系统的设计、采捕车动态路径的选择和数据处理三部分。通过使用LabVIEW软件编写信息采集子模块(DAQ.vi)、信号发生子模块(ConFig.ure Simulate Signal.vi)以及信号调整子模块等子程序,分别完成了采捕设备行进过程中障碍物的探测、对所收集信号的处理和对采捕设备运动路线的控制。通过在实验室水槽(8m×1m×0.8m)中安放不同的障碍物,对采捕设备进行行走系统的初步试运行、行走机构越障特性的测试、对前方障碍物的识别能力分析以及避障试验等初步试验研究。试验结果表明,拥有智能避障系统的采捕行走机构达到了如下性能1)可以在水下保持匀速平稳的行走;2)可以越过垂直高度为13cm以下的障碍物并保持正常行走;3)可以探测到5m以内的障碍物,并接收到障碍物信息误差可达1%;4)可根据探测信息确定避障行走路线。
[Abstract]:China is a large shellfish culture country, the marine shellfish culture yield accounts for about 80 per cent of the total mariculture yield and the annual output of shellfish increases year by year. In 2015, the mariculture shellfish yield in China is about 13.1655 million t. Among them, shellfish harvesting is an important link in shellfish culture, and some problems have been exposed with the increase of shellfish yield. The traditional operation mode has a certain degree of influence on the seafloor environment and mining equipment because of the variability and unknowability of the seafloor environment. The addition of intelligent obstacle avoidance technology to underwater mining equipment will effectively improve the work efficiency and reduce the damage to the ecological environment and equipment of seafloor shellfish culture area. In view of the problems such as the decrease of harvesting efficiency, the damage of equipment and the destruction of ecological environment in seafloor shellfish culture area due to the unpredictable working route and unpredictable working environment of subsea mining equipment, In this paper, the intelligent obstacle avoidance system for shellfish harvesting and trapping is studied. In this paper, the design of walking system of mining equipment and the design of obstacle avoidance system of mining equipment are completed, and the preliminary experimental study on the walking obstacle avoidance system of mining equipment is also carried out. The design of obstacle avoidance walking system of mining equipment, through the analysis and calculation of various parameters in the working environment of the seafloor, such as bottom quality, grounding specific pressure and other soil properties, and combined with the factors of the mining and walking mechanism itself, The crawler walking mechanism is selected as the walking mode of the walking system of the acquisition equipment. Considering the seafloor environment and noise interference in the working process, ultrasonic detection is selected as the main detection mode of the acquisition equipment. According to the special working environment under sea, the hardware part of the walking system of small prototype of mining equipment is designed, including drive wheel, support wheel, guide wheel, support and so on. The overall size is 60cm 脳 38cm 脳 32 cm, and the weight is about 30 kg. The obstacle avoidance system of acquisition equipment adopts ultrasonic detection, infrared and other sensors, as well as LabVIEW software and NI 9201 analog input module, NI 9265 analog output module, NI cDAQ-9178 chassis and other hardware equipment. The automatic test program is established quickly to process the data acquisition, data processing, data analysis and signal filtering, and to complete the collection and processing of obstacle information on the predetermined route of the mining equipment. The software control part of the system design mainly includes the design of obstacle detection system, the selection of dynamic path of mining vehicle and data processing. By using LabVIEW software to write information acquisition sub-module (DAQ.vi), signal generation sub-module (ConFig.ure Simulate Signal.vi) and signal adjustment sub-module, the obstacle detection of mining equipment is completed respectively. The processing of the collected signal and the control of the movement route of the acquisition equipment. By placing different obstacles in the laboratory flume (8m 脳 1m 脳 0.8m), the preliminary trial operation of the walking system and the test of the obstacle characteristics of the walking mechanism are carried out. The identification ability of obstacles in front and obstacle avoidance test are analyzed. The experimental results show that the mining and walking mechanism with intelligent obstacle avoidance system has the following performance: 1) it can keep steady walking at a uniform speed under water, 2) it can cross obstacles with vertical height below 13cm and keep walking normally. 3) obstacles within 5 m can be detected, and the error of receiving obstacle information can reach 1% 鈮，
本文编号：2478121
[Abstract]:China is a large shellfish culture country, the marine shellfish culture yield accounts for about 80 per cent of the total mariculture yield and the annual output of shellfish increases year by year. In 2015, the mariculture shellfish yield in China is about 13.1655 million t. Among them, shellfish harvesting is an important link in shellfish culture, and some problems have been exposed with the increase of shellfish yield. The traditional operation mode has a certain degree of influence on the seafloor environment and mining equipment because of the variability and unknowability of the seafloor environment. The addition of intelligent obstacle avoidance technology to underwater mining equipment will effectively improve the work efficiency and reduce the damage to the ecological environment and equipment of seafloor shellfish culture area. In view of the problems such as the decrease of harvesting efficiency, the damage of equipment and the destruction of ecological environment in seafloor shellfish culture area due to the unpredictable working route and unpredictable working environment of subsea mining equipment, In this paper, the intelligent obstacle avoidance system for shellfish harvesting and trapping is studied. In this paper, the design of walking system of mining equipment and the design of obstacle avoidance system of mining equipment are completed, and the preliminary experimental study on the walking obstacle avoidance system of mining equipment is also carried out. The design of obstacle avoidance walking system of mining equipment, through the analysis and calculation of various parameters in the working environment of the seafloor, such as bottom quality, grounding specific pressure and other soil properties, and combined with the factors of the mining and walking mechanism itself, The crawler walking mechanism is selected as the walking mode of the walking system of the acquisition equipment. Considering the seafloor environment and noise interference in the working process, ultrasonic detection is selected as the main detection mode of the acquisition equipment. According to the special working environment under sea, the hardware part of the walking system of small prototype of mining equipment is designed, including drive wheel, support wheel, guide wheel, support and so on. The overall size is 60cm 脳 38cm 脳 32 cm, and the weight is about 30 kg. The obstacle avoidance system of acquisition equipment adopts ultrasonic detection, infrared and other sensors, as well as LabVIEW software and NI 9201 analog input module, NI 9265 analog output module, NI cDAQ-9178 chassis and other hardware equipment. The automatic test program is established quickly to process the data acquisition, data processing, data analysis and signal filtering, and to complete the collection and processing of obstacle information on the predetermined route of the mining equipment. The software control part of the system design mainly includes the design of obstacle detection system, the selection of dynamic path of mining vehicle and data processing. By using LabVIEW software to write information acquisition sub-module (DAQ.vi), signal generation sub-module (ConFig.ure Simulate Signal.vi) and signal adjustment sub-module, the obstacle detection of mining equipment is completed respectively. The processing of the collected signal and the control of the movement route of the acquisition equipment. By placing different obstacles in the laboratory flume (8m 脳 1m 脳 0.8m), the preliminary trial operation of the walking system and the test of the obstacle characteristics of the walking mechanism are carried out. The identification ability of obstacles in front and obstacle avoidance test are analyzed. The experimental results show that the mining and walking mechanism with intelligent obstacle avoidance system has the following performance: 1) it can keep steady walking at a uniform speed under water, 2) it can cross obstacles with vertical height below 13cm and keep walking normally. 3) obstacles within 5 m can be detected, and the error of receiving obstacle information can reach 1% 鈮，
本文编号：2478121
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