Identification and quantification of mixed air pollutants based on homotopy method for gas sensor array

Details

• Personal Author:
  Mason AJ ; Yang Y
• Description:
  Accurate recognition of air pollutants and estimation of their concentrations are critical for human health and safety monitoring and can be achieved using gas sensor arrays. In this paper, an efficient method based on a homotopy algorithm is presented for the analysis of sensor arrays responding to binary mixtures. The new method models the responses of a gas sensor array as a system of nonlinear equations and provides a globally convergent way to find the solution of the system. Real data measurement for CH4 and SO2 are used to model sensor responses. The model is applied to the method for prediction and it shows the prediction results are within 1% variation of true values for both gas models. [Description provided by NIOSH]
• Subjects:
  Air Pollutants, Occupational Occupational Health Safety Safety Management
• Keywords:
  Air Pollutants Algorithms Gases Health Protection Models Monitoring Systems Safety Monitoring Sensors
• ISBN:
  9781424441198
• ISSN:
  1557-170X
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Proceedings
• Place as Subject:
  Michigan ; OSHA Region 5
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  2012
• NIOSHTIC Number:
  nn:20048656
• Citation:
  Conf Proc IEEE Eng Med Biol Soc, 2012 Nov; 2012:4221-4224
• CAS Registry Number:
  Methane (CAS RN 74-82-8) ; Sulfur dioxide (CAS RN 7446-09-5)
• Federal Fiscal Year:
  2013
• Performing Organization:
  Michigan State University
• Peer Reviewed:
  False
• Start Date:
  20100901
• Source Full Name:
  Conference Proceedings of the IEEE Engineering in Medicine and Biology Society
• End Date:
  20150831
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:5a96f3cabf20e94f07f86592e7028ad111056b9b8e17a9faf4828caf5d5430104f685e12ffe08b102b9585890b26e5deb5dc49fe6260d72edbcad93ea397f7c1
• Download URL:
  https://stacks.cdc.gov/view/cdc/203364/cdc_203364_DS1.pdf
• File Type:
  [PDF - 734.68 KB ]