發(fā)布時間：2018-07-21 15:34

【摘要】：機器視覺檢測是建立在計算機視覺和圖像處理基礎(chǔ)上的一門新興檢測技術(shù)，它通過圖像處理獲得被測工件對象的各種可描述參數(shù)，并對參數(shù)進行理解和判斷，最終應(yīng)用于實際檢測、測量和控制，具有非接觸、測量精度高、適用范圍廣和自動化程度高的特點。由于機器視覺在線檢測設(shè)備安裝在生產(chǎn)線上，其檢測速度必須與高速生產(chǎn)線保持高度同步，實現(xiàn)其同步的關(guān)鍵技術(shù)是相機拍照的精確控制和圖像的高速檢測。因此研究機器視覺在線檢測的相機高速拍照精確控制和圖像的高速檢測，開發(fā)研制自主知識產(chǎn)權(quán)的智能在線檢測設(shè)備，對促進高速視覺檢測的理論探索和創(chuàng)新及滿足當前國內(nèi)智能制造業(yè)市場的迫切需求皆具有重要的意義。 本文圍繞實現(xiàn)機器視覺在線檢測的關(guān)鍵技術(shù)，對機器視覺中的高速準確控制和圖像的高速檢測進行了研究，并以皇冠瓶蓋的在線檢測為應(yīng)用案例給出了可行的設(shè)計方案，主要工作概括如下： 首先，提出了基于兩層網(wǎng)絡(luò)控制理論的機器視覺在線檢測系統(tǒng)組成結(jié)構(gòu)，為實現(xiàn)高速的機器視覺在線檢測提供了新的研究思路和方向。將圖像處理任務(wù)放在高層處理單元，將系統(tǒng)控制放在本地控制單元，各單元根據(jù)需要處理的任務(wù)分別采用相應(yīng)的處理器，化解了信號集中處理時處理器負擔過重的問題，同時采用模塊化設(shè)計各子系統(tǒng)，便于安裝調(diào)試、維護和擴展。 其次，提出了基于迭代學習控制和卡爾曼濾波的高速準確控制方法，實現(xiàn)了相機位置受限條件下高速運動工件圖像的精確抓拍，解決了視覺檢測中復雜現(xiàn)場環(huán)境下的工件圖像高質(zhì)量精確采集的難題。同時建立了基于迭代學習控制和卡爾曼濾波相結(jié)合的相機控制模型，并理論推導和分析了模型的收斂性和收斂范圍，給出了數(shù)值仿真和實際的實驗結(jié)果。 第三，提出了基于局部能量離散路徑水平集方法的圖像邊緣搜索策略。將窄帶水平集搜索減少為按照窄帶中有限條數(shù)的線路搜索，極大降低了邊緣搜索的數(shù)據(jù)量。同時考慮水平集內(nèi)外的局部能量因素，克服了現(xiàn)場圖像中出現(xiàn)的干擾以及光照不均勻引起的誤差。 第四，提出了圓區(qū)域投影直方圖旋轉(zhuǎn)不變特征，將2D匹配數(shù)據(jù)轉(zhuǎn)化為1D數(shù)據(jù)，提高了匹配效率，為高速檢測提供了前提。同時提出采用稀疏表示的方法進行圖像的旋轉(zhuǎn)匹配和瑕疵檢測的策略，該策略在執(zhí)行實時檢測前通過對標準樣本的學習，建立標準數(shù)據(jù)字典，減少了檢測過程中的計算量，縮短了檢測計算時間，是實現(xiàn)實時高速在線檢測的關(guān)鍵。 第五，，設(shè)計搭建了模擬生產(chǎn)線的視覺檢測實驗平臺，并通過調(diào)整實驗平臺的相關(guān)參數(shù)，測試在線視覺檢測的性能，實現(xiàn)了在實驗室中對高速視覺檢測的仿真和測試。 最后，研制了用于實際生產(chǎn)的皇冠瓶蓋在線檢測系統(tǒng)，并安裝到生產(chǎn)現(xiàn)場進行實際的測試，實現(xiàn)了2600個/分鐘的皇冠瓶蓋在線檢測，文中給出了現(xiàn)場測試結(jié)果。通過10個月的試運行，該系統(tǒng)達到了皇冠瓶蓋高速在線檢測的要求，驗證了本文理論研究成果的可行性與有效性。 本文研究成果不僅僅局限于皇冠瓶蓋的在線檢測，還可以擴展到其他領(lǐng)域產(chǎn)品的在線檢測，市場前景廣闊。
[Abstract]:Machine vision detection is a new detection technology based on computer vision and image processing. Through image processing, it can obtain all kinds of description parameters of the object being measured and understand and judge the parameters. It is finally applied to actual detection, measurement and control. It has non contact, high precision, wide range of application and self. Because the machine vision on-line detection equipment is installed on the production line, the detection speed must keep high synchronization with the high speed production line. The key technology to realize its synchronization is the precise control of camera photography and the high speed detection of the image. The rapid detection of images and the development and development of intelligent online detection equipment for independent intellectual property are of great significance to the theoretical exploration and innovation of high speed vision detection and the urgent needs of the current domestic market of intelligent manufacturing industry.
This paper focuses on the key technology to realize the on-line inspection of machine vision, and studies the high-speed and accurate control of machine vision and the high speed detection of the image. The feasible design scheme is given with the online detection of the crown cap. The main work is summarized as follows:
First, the structure of the machine vision on-line detection system based on the two layer network control theory is proposed, which provides a new research idea and direction for the realization of the high-speed machine vision on-line detection. The image processing task is placed in the high-level processing unit, and the system control is placed in the local control unit. The tasks of each unit are respectively processed according to the needs. The corresponding processor is used to solve the problem that the processor is overloaded when the signal is centralized. At the same time, each subsystem is designed by modularization, which is easy to install, debug, maintain and expand.
Secondly, a high speed and accurate control method based on iterative learning control and Calman filter is proposed, which realizes the accurate capture of the high speed moving workpiece image under the limited position of the camera, and solves the difficult problem of the high quality and precision acquisition of the workpiece image in the complex scene environment. The camera control model is combined with the Kalman filter, and the convergence and convergence range of the model are theoretically deduced and analyzed. Numerical simulation and practical experimental results are given.
Third, the image edge search strategy based on the local energy discrete path level set method is proposed. The narrow band level set search is reduced to the line search of the limited number of narrow bands in the narrow band, which greatly reduces the amount of data in the edge search. Error caused by uneven illumination.
Fourth, the rotation invariant feature of the circular region projection histogram is proposed, and the 2D matching data is converted into 1D data. The matching efficiency is improved and the precondition for high-speed detection is provided. At the same time, the strategy of using sparse representation to carry out the rotation matching and defect detection of the image is put forward. The strategy adopts the study of the standard sample before executing the real-time detection. The establishment of standard data dictionary reduces the amount of computation in the detection process and shortens the detection time. It is the key to achieve real-time high-speed online detection.
Fifth, the visual inspection experiment platform of the simulated production line is designed and built, and the performance of the on-line visual inspection is tested by adjusting the related parameters of the experimental platform, and the simulation and test of the high speed vision detection in the laboratory are realized.
Finally, the online inspection system for the crown bottle cap for actual production is developed, and the actual test is installed on the production site to realize the on-line test of the crown bottle cap of 2600 / minute. The test results are given in the paper. The system has reached the requirement of the high speed on-line detection of the crown bottle cap through the trial operation of 10 months. The feasibility and effectiveness of the theoretical research results.
The research results in this paper are not only limited to the on-line detection of crown caps, but also can be extended to other products for on-line detection.
【學位授予單位】：上海大學
【學位級別】：博士
【學位授予年份】：2014
【分類號】：TP391.41

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