工業(yè)射線圖像質量的自檢測軟件系統(tǒng)研究與實現(xiàn)
發(fā)布時間：2019-01-17 18:29
【摘要】：伴隨著我國工業(yè)發(fā)展水平的提高,工業(yè)產(chǎn)品的需求和產(chǎn)出在日益增加,相應的工業(yè)產(chǎn)品質量控制難度也在加大,傳統(tǒng)的檢測過程大多依賴人工完成,在不增加人力投入的基礎上,顯然無法滿足日益增加的檢測需求,實現(xiàn)檢測自動化是長遠且有效的解決辦法。無損檢測技術是控制產(chǎn)品質量的一種有效手段,而射線檢測技術是無損檢測首選方法之一,隨著技術的發(fā)展,射線數(shù)字成像技術將成為該領域應用的趨勢。該技術可以形成被檢物件的數(shù)字透照圖像,同時數(shù)字圖像支持計算機圖像處理技術,計算機技術的應用為提高射線檢測過程的自動化水平提供了可能。傳統(tǒng)數(shù)字射線檢測過程可以分為兩步,首先需要對數(shù)字圖像本身質量進行鑒定,然后從合格的數(shù)字圖像中獲取被檢物件的缺陷信息。本文基于數(shù)字射線檢測原理,解決的問題是如何使用計算機代替人工完成射線圖像本身質量的鑒定,通過圖像處理技術實現(xiàn)圖像質量的自檢測。首先,本文對傳統(tǒng)射線圖像質量的檢測工藝進行了研究和介紹,從中總結得到圖像質量評定方法和相關原理,并根據(jù)方法和原理制定了由自動獲取閾值模塊、濾波平滑模塊和矩形識別模塊組成的軟件設計方案。其次,對各模塊中涉及到的算法的原理進行研究,在此基礎上針對本課題所涉及的問題對算法進行了適應性改進,并通過實驗對改進后的算法表現(xiàn)進行評估,改進后的算法在運算效率方面有所提高。通過對三個功能模塊的整合實現(xiàn)了射線圖像質量自檢測系統(tǒng),使用該系統(tǒng)對大量實際透照圖像進行檢測,并與人工檢測結果進行比較,完成了對系統(tǒng)可行性的測試。本文最后對所做工作進行了總結,并對未來工作進行了展望。通過大量實驗表明,本文所提出的軟件系統(tǒng)是有效可行的,基于圖像處理技術的射線圖像質量自檢測功能在執(zhí)行效率、判斷精度和等方面相對于人工檢測都具有優(yōu)勢,且具有很好的發(fā)展空間。
[Abstract]:With the improvement of the level of industrial development in China, the demand and output of industrial products are increasing day by day, the corresponding difficulty of quality control of industrial products is also increasing, the traditional detection process mostly depends on manual completion. On the basis of not increasing manpower input, it is obvious that it is unable to meet the increasing demand of detection, and it is a long-term and effective solution to realize test automation. Non-destructive testing (NDT) technology is an effective means to control product quality, and X-ray testing technology is one of the preferred methods of NDT. With the development of technology, digital radiography technology will become the trend of application in this field. This technique can form the digital radiographic image of the object under inspection, and the digital image supports the computer image processing technology. The application of the computer technology provides the possibility to improve the automation level of the radiographic detection process. The traditional digital ray detection process can be divided into two steps. Firstly, the quality of the digital image itself should be identified, and then the defect information of the subject object should be obtained from the qualified digital image. Based on the principle of digital ray detection, the problem solved in this paper is how to use computer instead of manual to complete the quality identification of the radiographic image itself, and to realize the self-detection of the image quality by image processing technology. First of all, the traditional radiographic image quality detection technology is studied and introduced in this paper, from which the image quality evaluation method and related principles are summarized, and the automatic acquisition threshold module is developed according to the method and principle. The software design scheme of filtering smooth module and rectangle recognition module. Secondly, the principle of the algorithm involved in each module is studied, on the basis of which the adaptive improvement of the algorithm is carried out, and the performance of the improved algorithm is evaluated through experiments. The improved algorithm improves the computational efficiency. Through the integration of the three functional modules, the self-detection system of radiographic image quality is realized. The system is used to detect a large number of actual radiographic images, and compared with the results of manual detection, the feasibility of the system is tested. At the end of this paper, the work done is summarized and the future work is prospected. A large number of experiments show that the software system proposed in this paper is effective and feasible, and the self-detection function of image quality based on image processing has advantages over manual detection in terms of execution efficiency, accuracy of judgement and so on. And has very good development space.
【學位授予單位】：北京郵電大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TP391.41
本文編號：2410253
[Abstract]:With the improvement of the level of industrial development in China, the demand and output of industrial products are increasing day by day, the corresponding difficulty of quality control of industrial products is also increasing, the traditional detection process mostly depends on manual completion. On the basis of not increasing manpower input, it is obvious that it is unable to meet the increasing demand of detection, and it is a long-term and effective solution to realize test automation. Non-destructive testing (NDT) technology is an effective means to control product quality, and X-ray testing technology is one of the preferred methods of NDT. With the development of technology, digital radiography technology will become the trend of application in this field. This technique can form the digital radiographic image of the object under inspection, and the digital image supports the computer image processing technology. The application of the computer technology provides the possibility to improve the automation level of the radiographic detection process. The traditional digital ray detection process can be divided into two steps. Firstly, the quality of the digital image itself should be identified, and then the defect information of the subject object should be obtained from the qualified digital image. Based on the principle of digital ray detection, the problem solved in this paper is how to use computer instead of manual to complete the quality identification of the radiographic image itself, and to realize the self-detection of the image quality by image processing technology. First of all, the traditional radiographic image quality detection technology is studied and introduced in this paper, from which the image quality evaluation method and related principles are summarized, and the automatic acquisition threshold module is developed according to the method and principle. The software design scheme of filtering smooth module and rectangle recognition module. Secondly, the principle of the algorithm involved in each module is studied, on the basis of which the adaptive improvement of the algorithm is carried out, and the performance of the improved algorithm is evaluated through experiments. The improved algorithm improves the computational efficiency. Through the integration of the three functional modules, the self-detection system of radiographic image quality is realized. The system is used to detect a large number of actual radiographic images, and compared with the results of manual detection, the feasibility of the system is tested. At the end of this paper, the work done is summarized and the future work is prospected. A large number of experiments show that the software system proposed in this paper is effective and feasible, and the self-detection function of image quality based on image processing has advantages over manual detection in terms of execution efficiency, accuracy of judgement and so on. And has very good development space.
【學位授予單位】：北京郵電大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TP391.41
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