【作者】 张君； 刘咏； 商细彬；

【Author】 ZHANG Jun, LIU Yong, SHANG Xi-bin Tianjin Academy of Environmental Sciences, State Key Laboratory of Odor Pollution Control, Tianjin 300191,China

【机构】 天津市环境保护科学研究院 国家环境保护恶臭污染控制重点实验室；

【摘要】 恶臭污染在全球范围内被广泛重视,随着经济发展,恶臭问题加重;同时人们环保意识增强,对恶臭问题的重视度加大。源解析的结果可以指导恶臭污染防治工作,也是制定恶臭污染防治规划的依据。人工神经网络(ANN)是基于仿效生物大脑的结构和功能而构成的一种信息处理系统,人工神经网络在源解析定性分析过程的应用为污染控制提供了基础指导。本论文实验在天津环境保护科学研究院完成,所研究的人工神经网络主要运用在定性分析中,并与气敏元件结合对空气样品进行解析分析,判定样品组成种类;之后再进行定量分析,进一步判定物质各组分的含量,综合分析污染来源;然后进行臭气浓度的测定,为环境监测,污染控制方法和恶臭治理对策提供依据。更多还原

【Abstract】 With the development of economy, the air pollution caused widespread attention in the worldwide. Odor problem became worse. At the same time, people’s environmental protection consciousness enhanced, the attention to odor importance was increased. The source apportionment can guide odor pollution prevention and control work, and is the basis of make stench planning of pollution prevention and control. Artificial neural networks (ANN) is based on imitate biological brain structure and function and a composition of a information processing system. In the process of qualitative analysis, the application of artificial neural networks can provide a basis for guidance for the pollution control.The experiment was done at Tianjin Academy of Environmental Sciences. The thesis studies the main use of artificial neural network in qualitative analysis. Integrated with gas-sensitive element of air samples and analysis air samples to judge species. Later in the quantitative analysis, determine the content of various components of the material further, and analyze pollution sources comprehensively. Again it can be used to determine odor concentration, and provide the basis for pollution control method and the stench countermeasures.更多还原