摘要
污水在市政污水管道的运输过程中,会释放大量的硫化氢(H_(2)S),易引发恶臭、中毒和管道腐蚀等问题。采用合理的预测模型对管道中H_(2)S的产生进行预测,可为后续采取相关的H_(2)S控制措施提供依据,对于污水管网的规划也具有重要意义。因此,首先分析了影响污水管道中H_(2)S生成的主要因素;其次将H_(2)S生成预测模型按照传统统计学和机器学习2类进行归类,并总结其研究进展;最后,探索了H_(2)S生成预测模型的潜在研究热点和难点,以期为市政污水管道H_(2)S预测模型的建立提供参考。
When sewage is transported in municipal sewer pipes,a large amount of hydrogen sulfide(H_(2)S)will be released.This toxic and harmful gas is easy to cause odor,poisoning,and pipeline corrosion.Using a reasonable prediction model to predict the generation of H_(2)S in the pipeline can provide a basis for the subsequent adoption of relevant H_(2)S control measures,and has important practical significance for the planning of the sewage pipeline network.In this paper,the main factors affecting the generation of H_(2)S in the sewage pipeline are analyzed;H_(2)S generation prediction models are classified into two types of traditional statistics and machine learning,and their research progress is summarized;the potential research hotspots and difficulties of H_(2)S prediction model are explored to provide a reference for establishment of H_(2)S prediction model of municipal sewage pipeline.
作者
远野
高君
张璐璐
陈天明
丁成
YUAN Ye;GAO Jun;ZHANG Lulu;CHEN Tianming;DING Cheng(School of Environmental Science and Engineering,Yancheng Institute of Technology,Yancheng 224051,China;Jiangsu Environmental Protection Equipment Intelligent Engineering Research Center,Yancheng 224051,China;Science and Technology Department of Yancheng Institute of Technology,Yancheng 224051,China)
出处
《环境工程》
CAS
CSCD
北大核心
2023年第11期69-77,共9页
Environmental Engineering
基金
国家自然科学基金项目(52170054,51608467)。
关键词
市政污水管道
硫化氢
影响因素
机器学习
预测模型
municipal sewage pipeline
H_(2)S
influencing factors
machine learning
prediction models
