本文選題：輸送帶 + 撕裂檢測(cè)��； 參考：《太原理工大學(xué)》2017年碩士論文

【摘要】：由于帶式輸送機(jī)具有大運(yùn)量、高速度、不間斷運(yùn)輸?shù)膬?yōu)點(diǎn),其被廣泛應(yīng)用于散狀、塊狀物料運(yùn)輸系統(tǒng)。在煤炭生產(chǎn)、運(yùn)輸過(guò)程中,帶式輸送機(jī)也是同樣擁有其他運(yùn)輸設(shè)備無(wú)可比擬的優(yōu)勢(shì)。因此,帶式輸送機(jī)是重要的煤炭生產(chǎn)、運(yùn)輸設(shè)備之一。帶式輸送機(jī)長(zhǎng)期、高負(fù)荷運(yùn)行過(guò)程中,輸送帶面臨著托輥、滾筒故障摩擦、金屬物件卡阻刺穿、矸石劃傷等造成的輸送帶撕裂危險(xiǎn)。輸送帶撕裂往往造成煤炭運(yùn)輸系統(tǒng)癱瘓和貨物灑落堵塞巷道事故。嚴(yán)重情況更會(huì)導(dǎo)致人員傷亡事故,對(duì)煤炭安全生產(chǎn)造成了不利影響。本課題在深入了解對(duì)機(jī)器視覺(jué)系統(tǒng)的基礎(chǔ)上,研究多種圖像處理算法在輸送帶撕裂視覺(jué)檢測(cè)系統(tǒng)應(yīng)用的可行性,旨在設(shè)計(jì)出一套實(shí)用性更強(qiáng)的輸送帶撕裂視覺(jué)檢測(cè)系統(tǒng),為煤炭生產(chǎn)、運(yùn)輸系統(tǒng)保駕護(hù)航。本文主要研究主要包括:1、目前,輸送帶撕裂視覺(jué)檢測(cè)方法相比較于其他輸送帶撕裂檢測(cè)方法具有無(wú)法比擬的優(yōu)越性。結(jié)合現(xiàn)有機(jī)器視覺(jué)系統(tǒng)在輸送帶撕裂檢測(cè)領(lǐng)域的應(yīng)用研究,提出一種實(shí)用性、可靠性、穩(wěn)定性、實(shí)時(shí)性更強(qiáng)的基于Otsu算法的輸送帶撕裂視覺(jué)檢測(cè)的研究方案。2、在深入分析研究機(jī)器視覺(jué)理論、結(jié)構(gòu)的基礎(chǔ)上,根據(jù)煤炭生產(chǎn)檢測(cè)系統(tǒng)的設(shè)計(jì)原則,提出基于Otsu算法的輸送帶撕裂視覺(jué)檢測(cè)系統(tǒng)設(shè)計(jì)方案,并深入研究系統(tǒng)結(jié)構(gòu)、功能以及實(shí)現(xiàn)系統(tǒng)功能所需全部硬件設(shè)備。3、圖像處理算法研究是輸送帶撕裂視覺(jué)檢測(cè)系統(tǒng)設(shè)計(jì)的核心。課題針對(duì)工業(yè)CCD相機(jī)采集的灰度圖像進(jìn)行以下三部分算法研究:1圖像預(yù)處理算法;2圖像處理算法;3撕裂診斷算法。系統(tǒng)采用中值濾波和直方圖均衡化對(duì)輸送帶表面圖像進(jìn)行預(yù)處理,達(dá)到去除椒鹽噪聲、增強(qiáng)圖像對(duì)比度的目的。圖像閾值分割處理是系統(tǒng)對(duì)輸送帶表面圖像處理的方法,是系統(tǒng)撕裂檢測(cè)的關(guān)鍵步驟。課題通過(guò)研究局部閾值分割算法、迭代閾值分割算法、Otsu閾值分割算法,綜合比較三者圖像處理時(shí)間、圖像處理效果方面的優(yōu)劣,確定Otsu閾值分割算法作為輸送帶撕裂視覺(jué)檢測(cè)系統(tǒng)的圖像處理算法。最后根據(jù)輸送帶表面二值圖像的特點(diǎn)規(guī)定撕裂診斷規(guī)則、算法,達(dá)到系統(tǒng)撕裂檢測(cè)的目的。4、提出輸送帶撕裂視覺(jué)檢測(cè)系統(tǒng)軟件設(shè)計(jì)結(jié)構(gòu)流程,分析如何通過(guò)軟件實(shí)現(xiàn)系統(tǒng)功能。虛擬儀器技術(shù)不斷發(fā)展,模塊化硬件結(jié)構(gòu)設(shè)計(jì),簡(jiǎn)潔的圖形化Lab VIEW編程環(huán)境,為機(jī)器視覺(jué)系統(tǒng)帶來(lái)了一次全新的革命�；谏鲜鰞�(yōu)點(diǎn),輸送帶撕裂視覺(jué)檢測(cè)系統(tǒng)使用虛擬儀器實(shí)現(xiàn)系統(tǒng)圖像處理、數(shù)據(jù)通信、數(shù)據(jù)庫(kù)存儲(chǔ)等功能。5、依托實(shí)驗(yàn)室中現(xiàn)有的帶式輸送機(jī)設(shè)備,針對(duì)系統(tǒng)實(shí)現(xiàn)功能選擇合適的工業(yè)CCD相機(jī)、LED光源、速度傳感器、下位機(jī)PXI平臺(tái)、上位PC機(jī)等硬件設(shè)備搭建實(shí)驗(yàn)平臺(tái)。在帶式輸送機(jī)5m/s的運(yùn)行速度下,啟動(dòng)系統(tǒng),通過(guò)系統(tǒng)界面檢驗(yàn)運(yùn)行狀態(tài)下系統(tǒng)對(duì)輸送帶表面圖像處理效果,分析、對(duì)比系統(tǒng)輸出的正常、撕裂輸送帶表面二值圖像數(shù)據(jù),設(shè)定撕裂診斷算法參數(shù),證明系統(tǒng)的可行性。本系統(tǒng)是機(jī)器視覺(jué)在輸送帶撕裂檢測(cè)領(lǐng)域的應(yīng)用研究,系統(tǒng)通過(guò)CCD相機(jī)獲取輸送帶表面圖像,并綜合應(yīng)用中值濾波、直方圖均衡化、Otsu灰度閾值分割方法對(duì)其處理、撕裂診斷,實(shí)現(xiàn)了對(duì)運(yùn)行狀態(tài)下輸送帶實(shí)時(shí)無(wú)損檢測(cè)的功能。
[Abstract]:As the belt conveyor has the advantages of large volume, high speed and uninterrupted transportation, it is widely used in bulk and bulk material transportation system. In the process of coal production and transportation, belt conveyor is also unparalleled with other transportation equipment. Therefore, belt conveyor is one of the important coal production and transportation equipment. In the long and high load running process of the conveyor, the conveyor belt is faced with the roller, the friction of the roller failure, the sticking of the metal objects, the damage of the gangue and so on. The tear of the conveyor belt often causes the coal transportation system to be paralyzed and the goods are sprinkled and blocked in the roadway. The whole production has caused a negative impact. On the basis of understanding the machine vision system, this paper studies the feasibility of the application of multiple image processing algorithms in the conveyer belt tearing visual detection system, aiming at designing a set of more practical belt tear visual detection system for coal production and transportation system. The main research is as follows: 1, at present, the visual detection method of conveyer belt tearing is superior to other conveyor belt tearing detection methods. Combined with the application of existing machine vision system in the field of conveyer belt tearing detection, a practical, reliable, stable and more real-time based Otsu algorithm is proposed. .2, based on the analysis and study of the theory of machine vision and the design principle of the coal production detection system, the design scheme of the belt tear visual detection system based on Otsu algorithm is proposed, and the system structure, function and all hardware functions required to realize the system function are deeply studied. .3, the research of image processing algorithm is the core of the design of conveyor belt tearing visual detection system. The following three algorithms are studied for the gray image collected by industrial CCD cameras: the 1 image preprocessing algorithm, the 2 image processing algorithm and the 3 tearing diagnosis algorithm. The system uses median filter and histogram equalization to get the image of the conveyer belt. Preprocessing to remove salt and pepper noise and enhance image contrast. Image threshold segmentation is a system for processing the surface of the conveyer belt. It is the key step of the system tearing detection. By studying the local threshold segmentation algorithm, the iterative threshold segmentation algorithm and the Otsu threshold segmentation algorithm, the three image parts are compared synthetically. According to the advantages and disadvantages of time and image processing effect, the Otsu threshold segmentation algorithm is used as the image processing algorithm for the transmission band tearing visual detection system. Finally, according to the characteristics of the two value image of the conveyer belt, the tearing diagnosis rules are stipulated and the algorithm is used to achieve the purpose of the system tearing detection. The software of the transmission band tearing visual detection system is set up. This paper analyzes how to implement the system function through software. The development of the virtual instrument technology, the design of modular hardware structure and the simple graphical Lab VIEW programming environment have brought a new revolution to the machine vision system. Based on the above advantages, the conveyer belt tearing visual detection system uses virtual instrument to realize the system image Processing, data communication, database storage and other functions.5, relying on the existing belt conveyor equipment in the laboratory, to select the appropriate industrial CCD camera, LED light source, speed sensor, PXI platform of the lower computer, the upper PC machine and other hardware equipment to set up the experimental flat. Over the system interface test operation state of the system on the conveyor belt surface image processing effect, analysis, comparison of the normal output of the system, tearing two value image data on the conveyor belt surface, setting up the tearing diagnosis algorithm parameters, proving the feasibility of the system. This system is the application of machine vision in the field of conveyor belt tearing detection, the system is through the CCD phase The machine obtains the image of the conveyor belt surface, and uses median filter, histogram equalization, Otsu gray threshold segmentation method to handle and tear diagnosis, and realizes the function of real-time nondestructive testing of the conveyer belt in the running state.
【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41

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