發(fā)布時間：2018-10-26 06:39

【摘要】：電鏟是一種廣泛應用于露天礦產(chǎn)的重要采掘設備,其鏟斗的斗齒在工作時因受到礦石物料較大的反作用力而容易發(fā)生脫落現(xiàn)象,脫落的斗齒連同礦石物料一同進入碎石機中會導致碎石機損壞,進而引發(fā)整條采掘——破碎生產(chǎn)線的停工,造成重大的經(jīng)濟損失。針對這一問題,本文利用紅外機器視覺系統(tǒng)對電鏟斗齒的工作狀態(tài)進行監(jiān)控,并結合圖像處理技術對斗齒脫落的視覺檢測算法進行了研究。主要內容如下:通過分析電鏟的工作過程,利用電鏟斗齒在工作時與礦石物料不斷摩擦并向外輻射紅外線的機理,采用紅外熱像儀對斗齒進行成像,以滿足電鏟晝夜不停的工作要求,同時能獲得較高質量的監(jiān)控圖像。在檢測算法上,先使用梯度方向直方圖(HOG)特征結合支持向量機(SVM)的目標檢測框架對紅外圖像中的斗齒對象進行目標檢測;在此傳統(tǒng)目標檢測方法的基礎上,通過分析斗齒圖像在形狀上的相似性關系,利用形狀上下文(Shape-Context)算法提取斗齒的形狀特征,并使用形狀匹配方法向斗齒的目標檢測過程添加形狀特征約束,以提高目標檢測的準確率。在準確檢測出圖像中的斗齒目標后,通過分析電鏟鏟斗與紅外相機之間的相對運動關系,確定了斗齒在圖像中空間位置關系的不變性,并以此為依據(jù)對斗齒脫落與否進行判斷,最后,通過實驗對整套檢測算法進行了驗證并分析了誤差產(chǎn)生的原因,提出了一些改進思路和方法。
[Abstract]:Electric shovel is a kind of important mining equipment which is widely used in opencast mine. The bucket tooth of its bucket is easy to fall off because of the reaction force of ore material. The lost bucket teeth along with the ore material entering the stone crusher will lead to the damage of the stone crusher, which will lead to the stoppage of the whole excavation-crushing production line, resulting in great economic losses. In order to solve this problem, the infrared machine vision system is used to monitor the working state of bucket teeth, and the visual detection algorithm of bucket tooth loss is studied in combination with image processing technology. The main contents are as follows: by analyzing the working process of the electric shovel, using the mechanism that the bucket teeth of the electric shovel continuously rub with the ore material and radiate infrared ray, the infrared thermal imager is used to image the bucket tooth. In order to meet the working requirements of the shovel day and night, at the same time can obtain a higher quality of monitoring images. In the detection algorithm, the target detection framework based on gradient direction histogram (HOG) feature and support vector machine (SVM) is used to detect the object in infrared image. On the basis of the traditional object detection method, the shape feature of bucket tooth is extracted by using shape context (Shape-Context) algorithm by analyzing the shape similarity of bucket tooth image. The shape matching method is used to add shape feature constraints to the object detection process in order to improve the accuracy of target detection. After accurately detecting the bucket tooth target in the image, by analyzing the relative motion relationship between the shovel bucket and the infrared camera, the invariance of the spatial position relation of the bucket tooth in the image is determined. Finally, the whole detection algorithm is verified by experiments, the causes of error are analyzed, and some improved ideas and methods are put forward.
【學位授予單位】：中北大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TD422.21;TP391.41

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