摘要
作为重组竹的基本单元,疏解竹束的质量对所制备的重组竹性能产生了关键性影响。然而,传统方法采用人工方式来检测疏解竹束,导致检测准确率低、效率低且主观性过强等问题。为解决人工检测存在的弊端,文章提出了一种基于深度学习U-Net网络的疏解竹束分级检测方法,该方法能快速实现疏解竹束的分级。最后,从工业设计角度出发,设计并开发了一款疏解竹束分级检测设备。该检测设备的开发成功解决了传统方法的弊端,有利于开发多元化的重组竹产品。
As the basic unit of reconstituted bamboo,the quality of bamboo bundles has a critical impact on the performance of the prepared reconstituted bamboo.However,traditional methods rely on manual methods to detect bamboo bundles,resulting in low detection accuracy,low efficiency,and excessive subjectivity.To address the drawbacks of manual detection,this article proposes a bamboo bundle grading detection method based on deep learning U-Net network,which can quickly achieve the grading of bamboo bundles.Finally,from the perspective of industrial design,we have designed and developed a bamboo bundle grading detection device.The successful development of this detection device has solved the drawbacks of traditional methods and is conducive to the development of diversified recombinant bamboo products.
作者
张铭浩
吴珏
ZHANG Minghao;WU Yu(School of Art&Design,Zhejiang Sci-Tech University,Hangzhou 310018,China)
出处
《工业设计》
2025年第2期52-55,共4页
Industrial Design
关键词
工业设计
深度学习技术
疏解竹束
分级检测
设备设计
Industrial Design
Deep Learning Technology
Relieve Bamboo Bundles
Graded Testing
Equipment Design
