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

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

【摘要】：核退役是核工業(yè)機(jī)器人重點應(yīng)用場景之一,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,其中很重要的一項是表面污染檢測,檢測結(jié)果將影響被退役核設(shè)施的處置方案實施。本課題以當(dāng)前國內(nèi)外核退役技術(shù)、機(jī)器人技術(shù)以及表面污染檢測技術(shù)的研究現(xiàn)狀為背景,主要圍繞機(jī)器人進(jìn)行表面污染檢測時,如何使機(jī)械臂末端的檢測儀器,在滿足表面污染相關(guān)檢測特性的前提下,可以順利完成表面污染檢測任務(wù)展開研究。課題研究目的是設(shè)計一套可行的方案。在本方案中使用線結(jié)構(gòu)光掃描系統(tǒng)完成待測物表面點云數(shù)據(jù)的采集,經(jīng)過法向估計和適于表面污染檢測特性的點云法向偏置處理,得到檢測軌跡所在曲面的點云。通過點云切片等方法規(guī)劃出機(jī)械臂任務(wù)空間的檢測軌跡,機(jī)器人根據(jù)生成的軌跡自主完成檢測目標(biāo)的表面污染檢測任務(wù)。本課題針對表面污染檢測,主要研究了α、β這兩種核退役表面污染檢測中重點關(guān)注的放射性污染源輻射特性及常用的檢測方法,結(jié)合對中核821廠的待退役核反應(yīng)堆及其周邊輔助設(shè)施的實地考察,對待檢測對象和表面污染檢測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MOTOMAN-MH6S機(jī)械臂建立連桿模型,求解其正運動學(xué)方程,針對使用傳統(tǒng)方法求解機(jī)械臂逆運動學(xué)存在計算量比較大、且傳統(tǒng)BP(Back Propagation)神經(jīng)網(wǎng)絡(luò)在被用來求解機(jī)器人逆運動學(xué)時會出現(xiàn)輸出誤差偏大的問題,這主要因其易陷入局部極值導(dǎo)致,論文對一種基于PSO優(yōu)化的BP神經(jīng)網(wǎng)絡(luò)在求解機(jī)器人逆運動學(xué)中的應(yīng)用進(jìn)行較深入地研究。在滿足表面污染檢測任務(wù)的相關(guān)需求下,為了能夠獲取任務(wù)空間的檢測軌跡,在研究過程中,對待檢測物進(jìn)行表面深度信息掃描,獲取其點云數(shù)據(jù),經(jīng)過對獲取到點云數(shù)據(jù)進(jìn)行預(yù)處理,得到更加有利于生成任務(wù)空間檢測軌跡的點云數(shù)據(jù)。再通過點云數(shù)據(jù)表面法線估計以及法向偏置算法,得到分別適用于α、β這兩種放射源檢測距離下檢測軌跡所在曲面的點云數(shù)據(jù),對其進(jìn)行點云切片等算法處理,最終完成任務(wù)空間的軌跡生成,并對生成的軌跡進(jìn)行了實驗驗證。本課題完成了表面污染檢測特性及核輻射探測方法研究、機(jī)械臂運動學(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++語言結(jié)合PCL開源庫在VS2010平臺下對各算法進(jìn)行了設(shè)計和實現(xiàn),同時對本文研究結(jié)果進(jìn)行實驗驗證。實驗結(jié)果表明:本文方案生成的檢測軌跡在進(jìn)行模擬表面污染檢測任務(wù)過程中,針對直徑60cm、70cm、80cm、90cm、100cm管道上切割下來的待檢測曲面,進(jìn)行α和β表面污染模擬檢測時,檢測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)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TL943;TP242

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