宁夏大学学报（自然科学版）2025，Vol.46Issue(4)：418-427,10.DOI:10.20176/j.cnki.nxdz.20251208
融合持续学习策略的近红外光谱煤炭挥发分检测方法
Continual Learning for Volatile Matter Detection in Coal via Near-Infrared Spectroscopy
摘要
Abstract
Volatile matter is a key indicator for evaluating coal quality and combustion characteristics,as its con-tent directly affects combustion efficiency,reaction activity,and process adaptability.Near-infrared spectros-copy is a rapid and non-destructive analytical technique that has been widely applied to the quantitative predic-tion of coal volatile matter.However,in cross-batch applications,systematic spectral drift often occurs.When new data is used to rebuild the model,the predictive capability for previous samples diminishes,exacerbating the issue of catastrophic forgetting during model updates.To address this challenge,this study introduces a continual-learning modeling method for coal volatile-matter prediction.During the feature extraction stage,a network combining dense connections and self-attention mechanisms is developed to effectively capture both local spectral details and global dependencies.In the model updating stage,a continual learning strategy inte-grating statistical feature replay and knowledge distillation is implemented to achieve knowledge retention and task adaptability without accessing original historical samples.Experiments conducted with three batches of coal samples demonstrate that the proposed method effectively mitigates catastrophic forgetting and maintains stable prediction performance under distributional shifts.Its overall accuracy approaches that of independent single-task models,thereby providing a feasible technical solution for long-term and stable volatile matter detection in complex industrial environments.关键词
煤质/近红外光谱/持续学习/特征回放/知识蒸馏Key words
coal quality/near-infrared spectroscopy/continual learning/feature replay/knowledge distillation分类
化学化工引用本文复制引用
WU Zhifeng,CHEN Hailin,YE Jinyan,ZHAO Jinqiu,ZOU Liang..融合持续学习策略的近红外光谱煤炭挥发分检测方法[J].宁夏大学学报（自然科学版）,2025,46(4):418-427,10.基金项目
国家自然科学基金资助项目(62473368,62373360) （62473368,62373360）
中国检验认证集团河北有限公司(2025ZJHBYF004-1) （2025ZJHBYF004-1）
海关总署科研项目(2023HK113) （2023HK113）
