1.1影像測量儀機器視覺檢測
1.1.1機器視覺
機器視覺是研究用相機和計算機來模仿人的眼睛和大腦完成對目標的識別、跟蹤和測量等任務的科學【11。由于機器視覺涉及到多個學科，給出一個精確的定義是很困難的。美國制造工程師協會(SME)機器視覺分會和美國機器人工業協會(RIA)自動化視覺分會關于機器視覺的定義是:“機器視覺是使用光學器件進行非接觸感知，自動獲取和解釋一個真實場景的圖像，以獲取信息或控制機器或過程。”
人們從20世紀50年代開始研究二維圖像的統計模式識別，60年代Roberts開始進行三維機器視覺的研究，70年代中期，Mrr人工智能實驗室正式開設《機器視覺》課程，80年代初期開始了全球性的研究熱潮，機器視覺獲得了蓬勃發展，新概念、新理論不斷涌現。伴隨著計算機技術的不斷提高和圖像處理與傳輸技術的日益成熟，機器視覺在生產實踐中的應用也加快了步伐。現在機器視覺已經廣泛地用于工業、農業、軍事、航空、醫學等領域中。同時，機器視覺在理論研究上也取得了很大的發展，現在機器視覺涉及了多們學科，包括:光學、機械、圖像處理、計算機圖形學、模式識別、人工智能、人工神經網絡等。
1.1.2機器視覺檢測技術
隨著制造業的不斷發展，先進制造技術的研究和應用越來越廣泛。先進制造技術以及自動化制造系統和先進生產模式的推廣應用都要求先進的檢測手段與之相適應。將機器視覺應用到制造業的檢測領域中，用機器視覺系統確定產品相對于一組標準要求的偏差的過程通常稱為機器視覺檢測2。它特指機器視覺在工業檢測方面的應用，是機器視覺應用和研究領域中的一個重要分支。視覺檢測就是檢測被測目標時，把圖像當作檢測和傳遞信息的手段或載體加以利用的檢測方法，其目的是從圖像中提取有用的信號，它是以現代光學為基礎，融合電子學、計算機圖像學、信息處理、計算機視覺等科學技術為一體的現代檢測技術。由于機器視覺系統可以快速獲取大量信息，而且易于與設計信息及加工控制信息集成，基于視覺檢測技術的儀器設備能夠實現智能化、數字化、小型化、網絡化和多功能化，具備在線檢測、實時分析、實時控制的能力，在
軍事、工業、商業、醫學等領域得到廣泛關注和應用【3】【4】。機器視覺檢測通常涉及指定零件的特征如配件完整性、表面完好性和幾何尺寸的測量等。機器視覺檢測的工作過程大致為:首先，使用相機將被攝取目標轉換成圖像信號，傳送給專用的圖像處理系統，圖像系統對這些圖像中包含的信息進行處理和計算;然后計算機根據處理的結果做出判斷或決策;最后將控制信號傳送給執行機構。機器視覺的特點是自動化、客觀、非接觸和高精度，與一般意義上的圖像處理系統相比，機器視覺強調的是精度和速度以及工業現場環境下的可靠性。機器視覺檢測與傳統的人工檢測相比效率更高，檢測結果更加準確可靠。由于機器視覺檢測不會受到操作者的疲勞度、責任心和經驗等因素的影響，在一些不適合人工作業的危險場合，工視覺難以滿足要求的場合和帶有高度重復性、智能性并且靠人的眼睛無法連續穩定地進行產品檢測的場合，機器視覺可以發揮它自身的優勢來高效、高質量的完成檢測任務。
1.2虛擬儀器
虛擬儀器(virtual Instrument)是日益發展的計算機硬、軟件和總線技術在向其它相關技術領域密集滲透的過程中，與測試技術、儀器儀表技術密切結合共同孕育出的一項全新的成果【5】。虛擬儀器利用IO接口設備完成信號的采集與處理，利用計算機的顯示功能來模擬傳統儀器的控制面板，以多種形式輸出檢測結果，利用計算機強大的軟件功能實現信號數據的運算、分析和處理，從而完成各種測試功能的一種計算機儀器系統。虛擬儀器是現代計算機技術和儀器技術深層次結合的產物，也是當今計算機輔助測試(CAT)領域的一項重要技術。虛擬儀器可利用計算機強大的圖形環境和在線幫助功能，構成既有普通儀器的基本功能又有一般儀器所沒有的特殊功能的高檔、廉價的新型儀器。它可建立中英文界面的虛擬儀器面板，完成對儀器的控制、數據分析和顯示，它改變了傳統儀器的使用方式，使儀器的功能和使用效率明顯提高，大幅度降低了儀器的價格，使用戶可以根據自己需要定義儀器的新功能。在虛擬儀器系統中，硬件僅僅是為了解決信號的輸入輸出，軟件才是整個儀器的關鍵，基于軟件體系的結構可以大大節省開發和維護的費用。虛擬儀器的品種多、功能強、自動化程度高、具有良好的人機界面，它與傳統儀器的功能是相同的:采集數據，對數據分析處理，以及數據的結果處理。它們之間重要區別之一是靈活性方面。虛擬儀器可由用戶自己定義，這意味著用戶可以自由地組合計算機平臺、硬件、軟件以及各種完成應用系統所需要的附件。而這種靈活性在由供應商定義、功能固定的傳統儀器中是做不到的。因此，虛擬儀器是儀器發展史上的一場革命，代表著儀器發展的最新方向和潮流，并且是信息技術的一個重要領域，對科學技術的發展和工業生產將產生巨大的作用，將成為儀器發展的方向和趨勢。1.3機器視覺檢測的發展現狀在國外機器視覺檢測從上世紀八十年代初開始已經得到了廣泛的研究，國內的機器視覺檢測研究從上世紀九十年代才逐步開始。當前，隨著機器視覺檢測系統應用的增加，對機器視覺的研究也越來越多。根據機器視覺的應用領域不同，對機器視覺檢測的研究可以分為不同的種類，不同的學者對分類也有不同的見解。文獻【4】將工業中應用的機器視覺質量控制系統分為四個類別:尺寸質量、表面質量、裝配結構和操作質量。文獻61機器視覺的應用領域分為四類:產品檢查、機器人、產品分類和其他應用。尺寸測量是機器視覺研究和應用的重要應用領域，也是一個比較早開始的研究的方向。機器視覺應用于尺寸測量工程中時，從機器視覺系統的硬件(光源、圖像傳感器等)的選用到軟件算法的設計中的每一個環節都對最終的性能產生影響。需要根據工程的自身特點選擇合適的硬件。文獻【7】研究電盤尺寸的檢測，采用兩個756X581象素的CCD傳感器分別采集電盤兩個側面的圖像，通過輪廓跟蹤、直線分割、和亞象素定位獲得工件的尺寸。系統精度達到正負0．3毫米，每個工件檢測花費的時間約0．3秒。
文獻【8】研究了基于計算機視覺的活塞環閉151間隙測量系統。采用795 X595象素數的CCD傳感器，根據活塞環本身幾何參數的特點推導出了活塞環各個參數之間的關系。使用了對圖像邊緣的亞像素定位技術對300微米的開口進行測量，測量系統的測量精度為士47微米。
文獻9】研究的機器視覺在線測量系統測量范圍從十幾絲到30毫米工件的外輪廓，經過實驗在同一狀態下長時間測量同一工件誤差達到±3微米。
總之，機器視覺在高精度的尺寸測量領域有著很大的應用空間，隨著機器視覺硬件制造技術的成熟和硬件成本的降低，機器視覺在現代化生產中將應用的越來越廣泛，其測量精度也會逐漸提高【10】。
1.4設計的主要內容
在查閱大量國內外文獻的基礎上設計基于虛擬儀器和機器視覺技術的機械零件尺寸測量儀系統。從理論上對機器視覺尺寸檢測進行研究，設計適合課題要求、與硬件設備配套使用的視覺檢測程序。本課題具體的工作內容包括:
1．機器視覺系統的總體構建與實施方案設計，按照機器視覺系統的結構，分析系統的組成和硬件的參數以及性能，這些硬件包括:光學鏡頭、光源、CCD相機、圖像采集卡，步進電機控制模塊，選擇各軟件模塊，完成整個系統的系統設計設計。
2．對圖像處理方法進行研究，對常用的圖像濾波和邊緣檢算法進行研究。通過試驗比較它們對機械加工零件圖像的處理效果，找到適合零件圖像的預處理方法。
3．研究基于IMAQ Vision的圖像處理函數以及相機的模型和相機標定算法。對本文搭建的機器視覺的相機進行標定，利用標定獲得的內參數校正采集到的圖像的畸變，提高測量效果。
4．編制軟件程序實現圖像的采集、圖像處理、特征提取和參數計算等功能。
5.分析影像測量儀的精度是否合理。
1.5設計的背景和意義
隨著我國經濟的持續增長和工業產品精密程度的提高，以及對產品數量和質量要求的提高，傳統的尺寸測量手段(如:卡尺、量規、萬能工具顯微鏡、輪廓儀、X射線等)己經不能滿足生產的需要。卡尺、量規等檢測手段雖然簡便、快捷，但測量數據較少、精度不高;萬能工具顯微鏡、輪廓儀等檢測手段雖然有較高的精度，但要求在特定的設備、特定的環境下進行檢測，不但勞動強度大，效率低，而且檢測過程同生產過程是分離的，這與現代工業所要求的在線檢測、實時控制的要求不符。機器視覺檢測可以高速、可靠和不間斷地對工業產品的質量問題進行準確的檢測，所以有望能取代以往費時費神但又無法保證檢測質量的人工檢測方法。基于虛擬儀器的視覺測量系統融合了最新的傳感器、電子測量和計算機等技術，使得視覺檢測設備具有前所未有的速度、靈活性、測量精度和資源的可重用性。CCD攝像設備的分辨率和成像速度等技術性能的不斷提高，數字圖像處理技術的逐步完善，以及計算機的性能和性價比的迅速提高，為這一領域的研究提供了相當有利的條件。此外，采用先進的虛擬儀器技術還可以大大縮短產品的開發周期，通過計算機網絡可獲得豐富的信息亦有助于我們解決各種各樣的技術問題。鑒于現在機器視覺在產品測量中應用的現狀，本課題針對機器視覺在機械加工零件尺寸檢測中的應用進行研究。課題的目標是利用機器視覺在工業檢測中的優勢對工業產品中基本的直線和圓形特征進行檢測。本課題的目標是研究開發基于機器視覺的柔性好、效率高的工件尺寸檢測系統。本文的研究對提高我國機器視覺檢測系統的開發應用水平，提高工業檢測的質量和效率以及突破國外公司對我國機器視覺市場的技術壟斷都具有現實意義，所研究的機器視覺系統具有一定的經濟價值。
英斯特力儀器是一家集研發、生產及銷售于一體的 影像測量儀，拉力試驗機, 硬度計 ,探傷儀, 粗糙度儀, 測厚儀, 金相設備廠家, 致力于為客戶提供更好的檢測儀器。
1.1 Machine vision detection
1.1.1 Machine vision
Machine vision is a science that studies the use of cameras and computers to imitate human eyes and brain to complete tasks such as target recognition, tracking and measurement [11]. As machine vision involves multiple disciplines, it is difficult to give an accurate definition. Machine vision is defined by the Machine Vision branch of the Society of Manufacturing Engineers (SME) and the Automation Vision Branch of the Robotics Industry association of America (RIA) as: "Machine vision is the use of optical devices for contactless perception to automatically acquire and interpret an image of a real scene in order to obtain information or control a machine or process."
People began to study statistical pattern recognition of two-dimensional images in the 1950s, Roberts began to study THREE-DIMENSIONAL machine vision in the 1960s, and Mrr Artificial Intelligence Laboratory formally opened the course machine Vision in the mid-1970s. In the early 1980s, global research boom began, and machine vision gained vigorous development. New concepts and theories keep emerging. With the continuous improvement of computer technology and the increasingly mature image processing and transmission technology, the application of machine vision in production practice has accelerated the pace. Now machine vision has been widely used in industry, agriculture, military, aviation, medicine and other fields. At the same time, machine vision has made great progress in theoretical research. Now machine vision involves many disciplines, including optics, machinery, image processing, computer graphics, pattern recognition, artificial intelligence, artificial neural network and so on.
1.1.2 Machine vision detection technology
With the continuous development of manufacturing industry, the research and application of advanced manufacturing technology are more and more extensive. The popularization and application of advanced manufacturing technology, automatic manufacturing system and advanced production mode require advanced testing methods to adapt to them. Machine vision is applied to the testing field of manufacturing industry, and the process of determining the deviation of products relative to a set of standard requirements with machine vision system is usually called machine vision testing 2. It refers to the application of machine vision in industrial inspection and is an important branch in the field of machine vision application and research. Visual inspection is to be measured, the image as a means of testing and pass information or carrier to take advantage of detection method, the purpose of useful signal is extracted from the image, it is based on the modern optics, image fusion of electronics, computer science, information processing, computer vision and so on science and technology for the integration of modern testing technology. Because machine vision system can quickly obtain a lot of information, and easy to integrate with the design information and processing control information, based on the vision detection technology of the instrument and equipment to achieve intelligence, digitalization, miniaturization, networking and multi-function, with online detection, real-time analysis, real-time control ability, in
Military, industrial, commercial, medical and other fields have been widely concerned and applied [3] [4]. Machine vision inspection usually involves the measurement of the characteristics of specified parts such as accessory integrity, surface integrity and geometric dimensions. The working process of machine vision detection is roughly as follows: First, the camera will be used to convert the target into image signals and send them to a special image processing system, which will process and calculate the information contained in these images; The computer then makes a judgment or decision based on the result of processing; Finally, the control signal is transmitted to the actuator. Machine vision is characterized by automation, objectivity, non-contact and high precision. Compared with general image processing systems, machine vision emphasizes accuracy and speed as well as reliability in the industrial field environment. Compared with traditional manual detection, machine vision detection is more efficient and the detection results are more accurate and reliable. Because machine vision detection will not be affected by the operator's fatigue, sense of responsibility and experience and other factors, in some dangerous occasions not suitable for manual operation, work vision is difficult to meet the requirements of the occasion and with a high degree of repeatability, intelligence and rely on people's eyes can not be continuous and stable product detection occasions, Machine vision can play its own advantages to complete the detection task efficiently and with high quality.
1.2 Virtual Instrument
Virtual Instrument is a brand new achievement which is closely combined with testing technology and Instrument technology in the process of intensive penetration of computer hardware, software and bus technology into other related technical fields [5]. Virtual instrument using IO interface equipment complete signal acquisition and processing, the use of computer display function to simulate the traditional instrument control panel, the output test results with a variety of forms, using computer powerful software implementation evaluation of signal data, analysis and processing, so as to complete a computer instrument system which has the function of the various tests. Virtual instrument is the product of the deep combination of modern computer technology and instrument technology, and it is also an important technology in the field of computer aided testing (CAT). Virtual instrument can make use of the powerful graphics environment and online help function of computer to form a high-grade and cheap new instrument which has both the basic functions of common instruments and special functions that common instruments do not have. It can establish the virtual instrument panel with Chinese and English interface, complete the control, data analysis and display of the instrument, it changes the way of using the traditional instrument, improve the function and efficiency of the instrument, greatly reduce the price of the instrument, the user can define the new function of the instrument according to their own needs. In the virtual instrument system, hardware is only to solve the signal input and output, software is the key of the whole instrument, the structure based on software system can greatly save the development and maintenance cost. The virtual instrument has many varieties, strong functions, high degree of automation and good man-machine interface. Its functions are the same as those of traditional instruments: data collection, data analysis and processing, and data result processing. One of the key differences between them is flexibility. Virtual instruments can be customized by users, which means that users are free to combine computer platforms, hardware, software, and accessories needed to complete applications. This flexibility is not available in traditional vendor-defined, fixed-function instruments. Therefore, virtual instrument is a revolution in the history of instrument development, representing the latest direction and trend of instrument development, and is an important field of information technology, will have a huge effect on the development of science and technology and industrial production, will become the direction and trend of instrument development. 1.3 The development status of machine vision detection in foreign machine vision detection from the beginning of the 1980s has been widely studied, the domestic machine vision detection research from the 1990s gradually began. At present, with the increase of the application of machine vision inspection system, more and more research on machine vision. According to the different application fields of machine vision, the research on machine vision inspection can be divided into different categories, and different scholars have different opinions on classification. Literature [4] divides machine vision quality control systems applied in industry into four categories: dimension quality, surface quality, assembly structure and operation quality. Reference 61 The application fields of machine vision are divided into four categories: product inspection, robotics, product classification and other applications. Dimensional measurement is an important field of machine vision research and application, and it is also a relatively early research direction. When machine vision is applied to dimension measurement engineering, every link from the choice of hardware (light source, image sensor, etc.) of machine vision system to the design of software algorithm will affect the final performance. The proper hardware should be selected according to the characteristics of the project. Literature [7] studied the size detection of electrical disk. Two CCD sensors with 756X581 pixels were used to collect images from the two sides of electrical disk respectively, and the size of the workpiece was obtained through contour tracking, straight line segmentation and sub-pixel positioning. The accuracy of the system reaches plus or minus 0.3 mm, and the detection time of each workpiece is about 0.3 seconds.
Reference [8] studied the piston ring closing 151 clearance measurement system based on computer vision. Using CCD sensor with 795 X595 pixels, the relationship between piston ring parameters is deduced according to the characteristics of piston ring geometry parameters. The sub-pixel positioning technology of the image edge was used to measure the 300 micron opening, and the measurement accuracy of the system was 47 microns.
Reference 9】 The machine vision online measurement system studied measured the range from a dozen threads to the outer contour of 30 mm workpiece. After the experiment, the error of measuring the same workpiece for a long time in the same state reached ±3 microns.
In short, machine vision has great application space in the field of high-precision dimensional measurement. With the maturity of machine vision hardware manufacturing technology and the reduction of hardware cost, machine vision will be more and more widely used in modern production, and its measurement accuracy will gradually improve [10].
1.4 Main contents of the design
On the basis of consulting a large number of domestic and foreign literature design of mechanical parts size measuring instrument system based on virtual instrument and machine vision technology. From the theory of machine vision size detection research, design suitable for the subject requirements, and supporting the use of hardware visual detection program. The specific work content of this project includes:
1. Machine vision system overall construction and implementation of the scheme design, according to the structure of the machine vision system, the analysis and the parameters of the hardware and the system performance, the hardware includes: optical lens, light source, CCD camera, image acquisition card, the stepper motor control module, select each software module, complete the system design of the whole system design.
2. Image processing methods are studied, and common image filtering and edge detection algorithms are studied. By comparing their processing effects on machined parts image, a suitable preprocessing method for parts image is found.
3. The image processing function, camera model and camera calibration algorithm based on IMAQ Vision are studied. To calibrate the machine vision camera built in this paper, the internal parameters obtained from the calibration are used to correct the distortion of the image collected and improve the measurement effect.
4. The software program is designed to realize the functions of image acquisition, image processing, feature extraction and parameter calculation.
5. Analyze whether the accuracy of the image measuring instrument is reasonable.
1.5 Background and significance of the design
With the continuous growth of China's economy and the improvement of the precision of industrial products, as well as the improvement of the requirements for the quantity and quality of products, the traditional measurement methods (such as calipers, gauges, universal tool microscope, profilometer, X-ray, etc.) have been unable to meet the needs of production. Caliper, gauge and other detection methods are simple and fast, but the measurement data is less, the accuracy is not high; Although universal tool microscope, profilometer and other detection methods have higher accuracy, they require detection in specific equipment and specific environment, which not only has high labor intensity and low efficiency, but also separates the detection process from the production process, which is inconsistent with the requirements of online detection and real-time control required by modern industry. Machine vision inspection can be high-speed, reliable and uninterrupted quality problems of industrial products for accurate detection, so it is expected to replace the previous time-consuming and laborious but unable to ensure the quality of the manual detection method. The visual measurement system based on virtual instrument integrates the latest sensor, electronic measurement and computer technology, which makes the visual inspection equipment have unprecedented speed, flexibility, measurement accuracy and resource reuse. The continuous improvement of resolution and imaging speed of CCD camera equipment, the gradual improvement of digital image processing technology, as well as the rapid improvement of computer performance and cost performance, provide quite favorable conditions for the research in this field. In addition, the use of advanced virtual instrument technology can greatly shorten the product development cycle, through the computer network can obtain rich information also helps us to solve a variety of technical problems. In view of the current situation of the application of machine vision in product measurement, this topic is aimed at the application of machine vision in machining parts size detection. The goal of this project is to use the advantages of machine vision in industrial inspection to detect the basic straight and circular features in industrial products. The goal of this topic is to develop a flexible and efficient workpiece size detection system based on machine vision. The research of this paper has practical significance for improving the development and application level of machine vision inspection system in Our country, improving the quality and efficiency of industrial inspection and breaking through the technological monopoly of foreign companies on the machine vision market in our country. The machine vision system studied has certain economic value.
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