中国电机工程学报2024，Vol.44Issue(9)：3610-3618,中插23,10.DOI:10.13334/j.0258-8013.pcsee.222435
基于图像对抗卷积自编码的燃烧稳定性定量监测
Quantitative Monitoring of Combustion Stability Based on Image Adversarial Convolutional Autoencoder
摘要
Abstract
Accurate monitoring of combustion stability is of great significance in optimizing the combustion state.Traditional combustion stability monitoring methods are not only highly dependent on prior expert knowledge,but also difficult to achieve quantitative evaluation.To overcome these limitations,a novel quantitative assessment method for combustion stability is proposed in this study.In this method,an adversarial convolutional autoencoder(ACAE)is established to extract deep features of the flame images,and a quantitative assessment index is applied for feature analysis.Especially,the ACAE adopts a novel adversarial mechanism to improve the training efficiency and thereby enhance the feature learning ability.The numerical interval of the quantitative assessment index is[0,1],and when the assessment index is lower than 0.5,the combustion state is stable.The feasibility of the stability monitoring method is verified by ethylene combustion experiments,and the testing results confirm that the deep image features extracted by the ACAE can be used to quantitatively estimate the combustion stability.Furthermore,the proposed monitoring method has a strong generalization performance that can accurately identify flame images beyond the scope of the training dataset.关键词
燃烧稳定性/火焰图像/对抗卷积自编码/定量监测Key words
combustion stability/flame image/adversarial convolutional autoencoder/quantitative monitoring分类
能源科技引用本文复制引用
韩哲哲,曾文浩,唐晓雨,王益,许传龙..基于图像对抗卷积自编码的燃烧稳定性定量监测[J].中国电机工程学报,2024,44(9):3610-3618,中插23,10.基金项目
江苏省高校哲学社会科学研究一般项目(2023SJYB 0432) （2023SJYB 0432）
南京工程学院高等教育研究课题(2022ZC09) （2022ZC09）
江苏省配电网智能技术与装备协同创新中心开放基金项目(XTCX202309). General Project of Philosophy and Social Science Research of Jiangsu Province Universities(2023SJYB0432) （XTCX202309）
High Education Research Project of Nanjing Institute of Technology(2022ZC09) （2022ZC09）
Project funded by the Open Fund of Jiangsu Provincial Distribution Network Intelligent Technology and Equipment Collaborative Innovation Center(XTCX202309). （XTCX202309）
