Ash Detection of Coal Slime Flotation Tailings Based on Chromatographic Filter Paper Sampling and Multi-Scale Residual Network

作     者：Wenbo Zhu Neng Liu Zhengjun Zhu Haibing Li Weijie Fu Zhongbo Zhang Xinghao Zhang 

作者机构：School of Mechatronic Engineering and AutomationFoshan UniversityFoshan528000China China Coal Technology Engineering Group Tangshan Research InstituteTangshan063000China 

出 版 物：《Intelligent Automation & Soft Computing》 (智能自动化与软计算（英文）)

年 卷 期：2023年第38卷第12期

页      面：259-273页

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：This work was supported by National Natural Science Foundation of China:Grant No.62106048 

主　　题：Coal slime flotation ash detection chromatography filter paper multi-scale residual network 

摘      要：The detection of ash content in coal slime flotation tailings using deep learning can be hindered by various factors such as foam,impurities,and changing lighting conditions that disrupt the collection of tailings *** address this challenge,we present a method for ash content detection in coal slime flotation *** method utilizes chromatographic filter paper sampling and a multi-scale residual network,which we refer to as ***,tailings are sampled using chromatographic filter paper to obtain static tailings images,effectively isolating interference factors at the flotation ***,the MRCN,consisting of a multi-scale residual network,is employed to extract image features and compute ash *** the MRCN structure,tailings images undergo convolution operations through two parallel branches that utilize convolution kernels of different sizes,enabling the extraction of image features at various scales and capturing a more comprehensive representation of the ash content ***,a channel attention mechanism is integrated to enhance the performance of the *** combination of the multi-scale residual structure and the channel attention mechanism within MRCN results in robust capabilities for image feature extraction and ash content *** experiments demonstrate that this proposed approach,based on chromatographic filter paper sampling and the multi-scale residual network,exhibits significantly superior performance in the detection of ash content in coal slime flotation tailings.