一種基于卷積神經(jīng)網(wǎng)絡的輕量級焊縫缺陷識別算法
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關鍵詞：焊縫缺陷;卷積神經(jīng)網(wǎng)絡;MobileNetV3;fire模塊;ECA模塊;輕量級;智能識別 中圖分類號：TP391.14 文獻標志碼：A doi：10.12415/j.issn.1671-7872.23178
A Lightweight Weld Defect Identification Algorithm Based on Convolutional Neural Network
XU Feihu， LI Dan， ZHAO Wenjie
（School of Electrical & Information Engineering， Anhui University of Technology，Maanshan ， China）
Abstract： To address the issues of low recognition eficiency and accuracy in traditional weld defect detection methodswhen processing large-scale industrial data，a lightweight weld defect recognition algorithm based on convolutional neural networks was proposed.The fire module was introduced into the original MobileNetV3 to reduce parameter size，whilethe ECA （eficient channel atention） module was incorporated to enhance feature chanel learming capability，thereby optimizing computational resource allocation and improving feature extraction performance.To validate the efectiveness of the proposed algorithm，comparative experiments were conducted with common classification models on a weld defect test dataset. The results demonstrate that，compared to other classification models， an average recognition accuracy of 98.50% is achieved by the proposed algorithm for common industrial defects such as dents，pores，and burrs，with the original algorithm being significantly outperformed， thanks to the combined effects of the fire module's lightweight design and the ECA module's feature enhancement. Moreover，both parameter size and floating-point operationsaresignificantly reduced by the improved MobileNetV3 algorithm while high recognitionaccuracy is maintained，making it particularlysuitable for deployment on industrial inspection devices with limited computational resources.A practical solution is thus provided for real-time quality inspection in the field of intelligent manufacturing.
Keywords： weld seam defect; convolutional neural networks; MobileNetV3;fire module; ECA module; lightweight; intelligent identify
焊接工藝作為一種通過加熱、高溫或高壓實現(xiàn)金屬和熱塑性材料接合的關鍵制造技術，在現(xiàn)代工業(yè)的鐵路建設、橋梁工程、汽車制造、航空航天等核心領域具有不可替代的應用價值。（剩余12679字）