棉纺织技术2025，Vol.53Issue(3)：50-58,9.
基于改进MobileNetV3-Small的断纱图像分类算法
Yarn breakage image classification algorithm based on improved MobileNetV3-Small
摘要
Abstract
Aiming the issues of lower test efficiency in yarn breakage detection and environmental susceptibility during ring spinning process,a modified MobileNetV3-Small yarn breakage detection method was proposed.Firstly,an image acquisition system based on four-wheel-four-drive mobile robot platform was designed and constructed,then seven category yarn breakage dataset was obtained.Secondly,Prewitt operator and gamma correction were used for image enhancement,the clarity of fiber features was improved.Next,modified CoordAttention mechanism was integrated in MobileNetV3-Small model.Capture ability of the model to yarn room and channel information was enhanced through adding channel attention mechanism.Finally,to solve the issues of class imbalance and feature learning,combined loss function of Focal Loss and Center Loss was adopted to enhance the model's generalization ability and classification precision.The experimental results showed that accuracy of the model was 97.8%on the validation set.Compared to the baseline model,the accuracy was increased 3.2 percentage points,the number of model parameters was decreased 4.42 M,which highlighting its advantages in lightweight design and high efficiency.The accuracy and real-time performance of yarn breakage detection tasks in the proposed model were higher,which could effectively overcome the limitation of the traditional methods.关键词
断纱检测/MobileNetV3-Small/图像采集系统/注意力机制/联合损失函数/深度学习Key words
yarn breakage detection/MobileNetV3-Small/image acquisition system/attention mechanism/combined loss function/deep learning分类
信息技术与安全科学引用本文复制引用
付奇强,王升,国冰磊,程凯,黄兴宇,陈佳..基于改进MobileNetV3-Small的断纱图像分类算法[J].棉纺织技术,2025,53(3):50-58,9.基金项目
湖北省自然科学基金项目(2022CFB805) （2022CFB805）
福建省科技计划项目(2023T3086) （2023T3086）
