ABS齒圈環(huán)形表面缺陷檢測方法
發(fā)布時間:2019-06-02 12:12
【摘要】:針對傳統(tǒng)人工方式檢測汽車用ABS齒圈環(huán)形表面缺陷時存在檢測效率低、易錯檢漏檢的問題,提出一種基于圖像處理的ABS齒圈環(huán)形表面缺陷檢測方法。根據(jù)生產(chǎn)實際設(shè)計并組裝ABS齒圈環(huán)形表面缺陷在線視覺檢測系統(tǒng),利用旋轉(zhuǎn)電缸結(jié)合齒圈托臺帶動齒圈旋轉(zhuǎn),由線陣CCD掃描并得到齒圈環(huán)形表面圖像,在經(jīng)過基于OpenCV編寫的圖像處理算法處理后根據(jù)缺陷所在區(qū)域判斷缺陷類型,進而判斷齒圈合格性。通過實驗將系統(tǒng)檢測與人工檢測結(jié)果進行對比,結(jié)果表明,每個齒圈平均檢測時間≤4 s,缺陷分類正確率≥92%。
[Abstract]:In order to solve the problems of low detection efficiency and easy error detection when the traditional manual method is used to detect the annular surface defects of ABS ring for automobile, a method of detecting annular surface defects of ABS tooth ring based on image processing is proposed. According to the production practice, the on-line visual detection system of ABS ring surface defect is designed and assembled. The rotating electric cylinder combined with the tooth ring bracket is used to drive the tooth ring to rotate, and the ring surface image of the tooth ring is scanned and obtained by linear CCD. After the image processing algorithm based on OpenCV, the defect type is judged according to the defect area, and then the tooth ring qualification is judged. The results of system detection and manual detection are compared through experiments. The results show that the average detection time of each tooth ring is less than 4 s, and the correct rate of defect classification is 鈮,
本文編號:2491090
[Abstract]:In order to solve the problems of low detection efficiency and easy error detection when the traditional manual method is used to detect the annular surface defects of ABS ring for automobile, a method of detecting annular surface defects of ABS tooth ring based on image processing is proposed. According to the production practice, the on-line visual detection system of ABS ring surface defect is designed and assembled. The rotating electric cylinder combined with the tooth ring bracket is used to drive the tooth ring to rotate, and the ring surface image of the tooth ring is scanned and obtained by linear CCD. After the image processing algorithm based on OpenCV, the defect type is judged according to the defect area, and then the tooth ring qualification is judged. The results of system detection and manual detection are compared through experiments. The results show that the average detection time of each tooth ring is less than 4 s, and the correct rate of defect classification is 鈮,
本文編號:2491090
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