【摘要】：針對(duì)當(dāng)前鐵路扣件狀態(tài)自動(dòng)識(shí)別準(zhǔn)確率和穩(wěn)定性不高等問題,利用直射式激光三角測(cè)量法原理研發(fā)扣件檢測(cè)系統(tǒng),采集不受環(huán)境光影響的高質(zhì)量軌道三維數(shù)據(jù)。提出基于三維圖像的扣件區(qū)域定位方法,并利用先驗(yàn)知識(shí)驗(yàn)證扣件位置以保證扣件定位的準(zhǔn)確性;基于彈條的高度規(guī)律信息提取彈條,采用HGOH作為特征描述算子;根據(jù)特征向量的模是否等于零可識(shí)別出缺失扣件,將模不為零的特征向量送入已訓(xùn)練的SVM分類器,從而識(shí)別斷裂扣件和完整扣件。室內(nèi)試驗(yàn)研究結(jié)果表明,采用本文提出的扣件缺陷自動(dòng)檢測(cè)算法,識(shí)別準(zhǔn)確率可達(dá)98.0%,能滿足扣件缺陷自動(dòng)化檢測(cè)的需要。
[Abstract]:In order to solve the problem of low accuracy and stability in automatic identification of railway fasteners, a fastener detection system based on direct laser triangulation is developed to collect high-quality 3D orbital data unaffected by ambient light. Ensure the accuracy of fastener positioning; extract the bullet strip based on the height rule information of the bullet strip, and use HGOH as the feature descriptor operator; identify missing fasteners according to whether the modulus of the feature vector is equal to zero, and send the modulus of non-zero feature vector to the trained SVM classifier to identify broken fasteners and complete fasteners. The results show that the recognition accuracy can reach 98.0% by using the proposed algorithm, which can meet the needs of automatic detection of fastener defects.
【作者單位】： 西南交通大學(xué)土木工程學(xué)院;西南交通大學(xué)道路工程四川省重點(diǎn)實(shí)驗(yàn)室;俄克拉荷馬州立大學(xué)土木與環(huán)境工程學(xué)院;西南交通大學(xué)高速鐵路線路工程教育部重點(diǎn)實(shí)驗(yàn)室;
【基金】：國(guó)家自然科學(xué)基金(51478398,51308477,U1534203) 中央高�；究蒲袠I(yè)務(wù)費(fèi)專項(xiàng)資金(2682015CX091)
【分類號(hào)】：TP391.41;U216.3
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本文編號(hào)：2212957