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Research for fluid impurity detection based on ANN and infrared spectrum analysis technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A series of economic losses is caused by the biofilm of water pipe in industrial real water systems. Combined optical fiber self-relative technology with infrared spectrum analysis technology, real time detection technique for forming thickness and ingredient is put forward in the paper, which provides technical support and reliable data for analyzing biofouling influencing factors, contaminant separation and warning. Schematic diagram of biofouling detection is presented. Compensation technology based on radial basis function (RBF) neural network and learning algorithm are studied in order to solve the problem of measurement precision and range. Biofouling forming and optical characteristics in industrial real water systems are researched and standard specimen collection is set up. Correcting model explaining quantitatively relation between substance ingredient content and infrared spectrum based on partial least squares (PLS) method. A new method is provided for the research on biofouling in real water system, which can be used in other fields such as mining, environment protection, medical treatment and transportation of oil, gas and water.

Original languageEnglish
Title of host publicationInternational Symposium on Photoelectronic Detection and Imaging 2011
Subtitle of host publicationSensor and Micromachined Optical Device Technologies
DOIs
StatePublished - 2011
EventInternational Symposium on Photoelectronic Detection and Imaging 2011: Sensor and Micromachined Optical Device Technologies - Beijing, China
Duration: 24 May 201126 May 2011

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8191
ISSN (Print)0277-786X

Conference

ConferenceInternational Symposium on Photoelectronic Detection and Imaging 2011: Sensor and Micromachined Optical Device Technologies
Country/TerritoryChina
CityBeijing
Period24/05/1126/05/11

Keywords

  • Biofouling detection
  • Partial least squares (PLS) method
  • RBF neural network

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