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文章摘要
污水处理厂还原硫化物和臭气浓度的电子鼻监测技术探究
Detection of Reduced Sulfide and Odor Concentration in Sewage Treatment Plant using Electronic Nose
  
DOI:
中文关键词: 电子鼻  还原硫化物  臭气浓度  响应面分析法  偏最小二乘法  污水处理厂
英文关键词: Electronic nose  Reduced sulfide  Odor concentration  Response surface methodology  Partial least squares  Sewage treatment plant
基金项目:国家自然科学基金资助项目(21577096);国家重点研发计划基金资助项目(2016YFC0700603-003)
作者单位
孟洁 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天津迪兰奥特环保科技开发有限公司 
商细彬 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天津迪兰奥特环保科技开发有限公司 
荆博宇 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天津迪兰奥特环保科技开发有限公司 
王亘 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 
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中文摘要:
      用电子鼻监测技术探究污水处理厂还原硫化物质量浓度和臭气质量浓度预测方法。结果表明,使用响应面分析法(RSM)建立还原硫化物质量浓度与电子鼻响应值关系,构建还原硫化物质量浓度预测模型,准确率可达95%。使用偏最小二乘法(PLS)建立不同质量浓度还原硫化物的传感器响应值与对应臭气质量浓度之间的关系,构建臭气浓度预测模型,并用实际样品验证。
英文摘要:
      A method for predicting the concentration of reduced sulfide and odor in sewage treatment plant were developed by using electronic nose technology. Response surface methodology (RSM) was used to build the relationship between reduced sulfide concentration and the response value of electronic nose, and establish a model for reduced sulfide concentration prediction. The accuracy was up to 95%. Partial least squares (PLS) method was used to build the relationship between the sensor response value of reduced sulfide at different concentrations and the corresponding odor mass concentration, and establish a model for odor concentration prediction. The method was verified by actual samples.
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