菲律賓蛤仔機械化采捕行走機構(gòu)及避障系統(tǒng)設(shè)計
發(fā)布時間：2019-05-16 07:33
【摘要】：我國是貝類養(yǎng)殖大國,海洋貝類養(yǎng)殖產(chǎn)量約占海水養(yǎng)殖總產(chǎn)量的80%并且貝類的年產(chǎn)量逐年增長,2015年我國海水養(yǎng)殖貝類產(chǎn)量約1316.55萬t。其中貝類采捕是貝類養(yǎng)殖的重要環(huán)節(jié),隨著貝類產(chǎn)量的增加傳統(tǒng)的采捕方式暴露出了一些問題。傳統(tǒng)作業(yè)方式因海底環(huán)境的多變性與未知性對海底環(huán)境和采捕設(shè)備造成了一定程度的影響。為海下采捕設(shè)備添加智能避障技術(shù)將有效地提高工作效率,減小對海底貝類養(yǎng)殖區(qū)生態(tài)環(huán)境和設(shè)備的損害。針對海下采捕設(shè)備工作過程中對工作路線、工作環(huán)境不可預(yù)測造成采捕效率下降、設(shè)備損壞以及海底貝類養(yǎng)殖區(qū)生態(tài)環(huán)境破壞等問題,本文開展了貝類采捕海下智能避障系統(tǒng)的研究。論文主要完成了采捕設(shè)備行走系統(tǒng)設(shè)計和采捕設(shè)備避障系統(tǒng)設(shè)計,并對采捕設(shè)備行走避障系統(tǒng)初步試驗研究。采捕設(shè)備避障行走系統(tǒng)設(shè)計,通過分析計算海底工作環(huán)境中的各種參數(shù),如海底底質(zhì)、接地比壓等泥土性質(zhì),并結(jié)合采捕行走機構(gòu)自身因素,選定履帶式行走機構(gòu)作為采捕設(shè)備行走系統(tǒng)的行走方式;考慮工作過程中海底環(huán)境和噪音干擾等狀況,選用超聲波探測為該采捕設(shè)備的主要探測方式。針對海下特殊工作環(huán)境設(shè)計完成了采捕設(shè)備小型樣機行走系統(tǒng)的硬件部分,包括驅(qū)動輪、支重輪、導(dǎo)向輪、支架等結(jié)構(gòu),整體尺寸為60cm×38cm×32cm、重約30kg。采捕設(shè)備避障系統(tǒng)采用了超聲波探測、紅外線等傳感器,以及LabVIEW軟件和NI 9201模擬輸入模塊、NI 9265模擬輸出模塊、NI cDAQ-9178機箱等硬件設(shè)備,快速建立自動測試程序進行數(shù)據(jù)采集、數(shù)據(jù)處理、數(shù)據(jù)分析以及信號濾波等處理,完成對采捕設(shè)備預(yù)定路線上的障礙物信息采集處理。系統(tǒng)設(shè)計的軟件控制部分主要包括障礙物探測系統(tǒng)的設(shè)計、采捕車動態(tài)路徑的選擇和數(shù)據(jù)處理三部分。通過使用LabVIEW軟件編寫信息采集子模塊(DAQ.vi)、信號發(fā)生子模塊(ConFig.ure Simulate Signal.vi)以及信號調(diào)整子模塊等子程序,分別完成了采捕設(shè)備行進過程中障礙物的探測、對所收集信號的處理和對采捕設(shè)備運動路線的控制。通過在實驗室水槽(8m×1m×0.8m)中安放不同的障礙物,對采捕設(shè)備進行行走系統(tǒng)的初步試運行、行走機構(gòu)越障特性的測試、對前方障礙物的識別能力分析以及避障試驗等初步試驗研究。試驗結(jié)果表明,擁有智能避障系統(tǒng)的采捕行走機構(gòu)達到了如下性能1)可以在水下保持勻速平穩(wěn)的行走;2)可以越過垂直高度為13cm以下的障礙物并保持正常行走;3)可以探測到5m以內(nèi)的障礙物,并接收到障礙物信息誤差可達1%;4)可根據(jù)探測信息確定避障行走路線。
[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，
本文編號：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，
本文編號：2478121
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