本文關(guān)鍵詞：適用于表面污染檢測(cè)的機(jī)械臂軌跡生成研究　出處：《西南科技大學(xué)》2017年碩士論文　論文類(lèi)型：學(xué)位論文

  更多相關(guān)文章： 表面污染檢測(cè) 法向估計(jì) 法向偏置 點(diǎn)云切片 軌跡生成

【摘要】：核退役是核工業(yè)機(jī)器人重點(diǎn)應(yīng)用場(chǎng)景之一,其中的智能化核退役工程是重中之重。在核退役工程中涉及到繁雜的核工業(yè)退役工藝流程,其中很重要的一項(xiàng)是表面污染檢測(cè),檢測(cè)結(jié)果將影響被退役核設(shè)施的處置方案實(shí)施。本課題以當(dāng)前國(guó)內(nèi)外核退役技術(shù)、機(jī)器人技術(shù)以及表面污染檢測(cè)技術(shù)的研究現(xiàn)狀為背景,主要圍繞機(jī)器人進(jìn)行表面污染檢測(cè)時(shí),如何使機(jī)械臂末端的檢測(cè)儀器,在滿(mǎn)足表面污染相關(guān)檢測(cè)特性的前提下,可以順利完成表面污染檢測(cè)任務(wù)展開(kāi)研究。課題研究目的是設(shè)計(jì)一套可行的方案。在本方案中使用線(xiàn)結(jié)構(gòu)光掃描系統(tǒng)完成待測(cè)物表面點(diǎn)云數(shù)據(jù)的采集,經(jīng)過(guò)法向估計(jì)和適于表面污染檢測(cè)特性的點(diǎn)云法向偏置處理,得到檢測(cè)軌跡所在曲面的點(diǎn)云。通過(guò)點(diǎn)云切片等方法規(guī)劃出機(jī)械臂任務(wù)空間的檢測(cè)軌跡,機(jī)器人根據(jù)生成的軌跡自主完成檢測(cè)目標(biāo)的表面污染檢測(cè)任務(wù)。本課題針對(duì)表面污染檢測(cè),主要研究了α、β這兩種核退役表面污染檢測(cè)中重點(diǎn)關(guān)注的放射性污染源輻射特性及常用的檢測(cè)方法,結(jié)合對(duì)中核821廠(chǎng)的待退役核反應(yīng)堆及其周邊輔助設(shè)施的實(shí)地考察,對(duì)待檢測(cè)對(duì)象和表面污染檢測(cè)工程的具體條件和需求進(jìn)行了深入地分析和總結(jié)。課題使用D-H方法對(duì)MOTOMAN-MH6S機(jī)械臂建立連桿模型,求解其正運(yùn)動(dòng)學(xué)方程,針對(duì)使用傳統(tǒng)方法求解機(jī)械臂逆運(yùn)動(dòng)學(xué)存在計(jì)算量比較大、且傳統(tǒng)BP(Back Propagation)神經(jīng)網(wǎng)絡(luò)在被用來(lái)求解機(jī)器人逆運(yùn)動(dòng)學(xué)時(shí)會(huì)出現(xiàn)輸出誤差偏大的問(wèn)題,這主要因其易陷入局部極值導(dǎo)致,論文對(duì)一種基于PSO優(yōu)化的BP神經(jīng)網(wǎng)絡(luò)在求解機(jī)器人逆運(yùn)動(dòng)學(xué)中的應(yīng)用進(jìn)行較深入地研究。在滿(mǎn)足表面污染檢測(cè)任務(wù)的相關(guān)需求下,為了能夠獲取任務(wù)空間的檢測(cè)軌跡,在研究過(guò)程中,對(duì)待檢測(cè)物進(jìn)行表面深度信息掃描,獲取其點(diǎn)云數(shù)據(jù),經(jīng)過(guò)對(duì)獲取到點(diǎn)云數(shù)據(jù)進(jìn)行預(yù)處理,得到更加有利于生成任務(wù)空間檢測(cè)軌跡的點(diǎn)云數(shù)據(jù)。再通過(guò)點(diǎn)云數(shù)據(jù)表面法線(xiàn)估計(jì)以及法向偏置算法,得到分別適用于α、β這兩種放射源檢測(cè)距離下檢測(cè)軌跡所在曲面的點(diǎn)云數(shù)據(jù),對(duì)其進(jìn)行點(diǎn)云切片等算法處理,最終完成任務(wù)空間的軌跡生成,并對(duì)生成的軌跡進(jìn)行了實(shí)驗(yàn)驗(yàn)證。本課題完成了表面污染檢測(cè)特性及核輻射探測(cè)方法研究、機(jī)械臂運(yùn)動(dòng)學(xué)研究、任務(wù)空間中相關(guān)任務(wù)需求下的軌跡生成研究,并基于C++語(yǔ)言結(jié)合PCL開(kāi)源庫(kù)在VS2010平臺(tái)下對(duì)各算法進(jìn)行了設(shè)計(jì)和實(shí)現(xiàn),同時(shí)對(duì)本文研究結(jié)果進(jìn)行實(shí)驗(yàn)驗(yàn)證。實(shí)驗(yàn)結(jié)果表明:本文方案生成的檢測(cè)軌跡在進(jìn)行模擬表面污染檢測(cè)任務(wù)過(guò)程中,針對(duì)直徑60cm、70cm、80cm、90cm、100cm管道上切割下來(lái)的待檢測(cè)曲面,進(jìn)行α和β表面污染模擬檢測(cè)時(shí),檢測(cè)距離平均有效率分別達(dá)70.25%和81.27%、71.83%和82.67%、72.41%和83.24%、73.76%和84.57%、75.03%和85.88%,從而驗(yàn)證了該方案的可行性和有效性。
[Abstract]:Nuclear decommissioning is one of the key application scenes of the nuclear industry robot, and the intelligent nuclear decommissioning project is the most important. In the nuclear decommissioning project, there is a complicated process of decommissioning of nuclear industry. A very important aspect is surface contamination detection. The test results will affect the disposition of decommissioned nuclear facilities. The project is based on the current status of nuclear decommissioning technology, robot technology and surface contamination detection technology, mainly around the robot surface contamination detection, how to make the instrument manipulator, to meet the surface pollution related detection characteristics of the premise, can successfully complete the task of surface contamination detection. The purpose of the research is to design a feasible scheme. In this scheme, the line structured light scanning system is used to complete the collection of the point cloud data on the surface of the object to be tested. After the normal direction estimation and the point cloud normal bias processing for the surface pollution detection feature, we get the point cloud for detecting the track surface. Through the point cloud slicing and other methods, we can plan the detection track of the manipulator's task space, and the robot completes the detection task's surface pollution detection task independently according to the generated trajectory. This thesis mainly studies the surface contamination detection, radioactive pollution source radiation characteristics focus on the detection of alpha and beta of the two nuclear decommissioning of surface contamination and detection methods commonly used, combined with the field survey of 821 nuclear plants for decommissioning of nuclear reactor and its surrounding ancillary facilities, to detect objects and surface contamination detection project conditions and needs to conduct in-depth analysis and summary. Use the D-H method to establish linkage model research on MOTOMAN-MH6S manipulator, solving the kinematics equation, to use traditional method to solve the kinematics calculation is relatively large, and the traditional BP (Back Propagation) neural network was used to solve the inverse kinematics of robot hours will output the big error problem, which is mainly due to its easy the lead into the local extremum, a BP neural network based on PSO optimization in solving inverse kinematics of robot application is deeply researched. To meet the needs of related surface contamination detection task, in order to detect the track to get the task space, in the course of the study, to test the surface depth information scanning, obtain the point cloud data, the point cloud data obtained after the pretreatment, get more point cloud data to detect task space trajectory generation. Then the algorithm to bias by point cloud data and surface normal estimation method, point cloud data were applied to these two kinds of alpha and beta radiation source detection distance under the curved surface, the point cloud slicing algorithm, trajectory generation and complete the task space, and the trajectory of the generation of experiments verify. This paper completed the research of trajectory generation tasks related to nuclear radiation detection method and detection characteristics of surface pollution research, kinematics research, task space requirements, and based on C++ language combined with PCL Library in the VS2010 platform for the design and implementation of the algorithm, and experiments are carried out to validate the results of this study. The experimental results show that this scheme generated in the detection of trajectory simulation surface contamination detection tasks, for detecting surface cut diameter of 60cm, 70cm, 80cm, 90cm, 100cm pipe, alpha and beta surface contamination simulation test, the average efficiency of 70.25% and 81.27%, 71.83% and 82.67%, 72.41% and 83.24% 73.76%, and 84.57%, 75.03% and 85.88% respectively with the detection distance, which verifies the validity and feasibility of the scheme.
【學(xué)位授予單位】：西南科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TL943;TP242

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