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Environmental research v.160, 2018년, pp.183 - 194   SCI SCIE
본 등재정보는 저널의 등재정보를 참고하여 보여주는 베타서비스로 정확한 논문의 등재여부는 등재기관에 확인하시기 바랍니다.

Enhanced data validation strategy of air quality monitoring network

Harkat, Mohamed-Faouzi (Chemical Engineering Program, Texas A&M University at Qatar, Doha, Qatar ) ; Mansouri, Majdi (Electrical and Computer Engineering Program, Texas A&M University at QATAR, Doha, Qatar ) ; Nounou, Mohamed (Chemical Engineering Program, Texas A&M University at Qatar, Doha, Qatar ) ; Nounou, Hazem (Electrical and Computer Engineering Program, Texas A&M University at QATAR, Doha, Qatar ) ;
  • 초록  

    Abstract Quick validation and detection of faults in measured air quality data is a crucial step towards achieving the objectives of air quality networks. Therefore, the objectives of this paper are threefold: (i) to develop a modeling technique that can be used to predict the normal behavior of air quality variables and help provide accurate reference for monitoring purposes; (ii) to develop fault detection method that can effectively and quickly detect any anomalies in measured air quality data. For this purpose, a new fault detection method that is based on the combination of generalized likelihood ratio test (GLRT) and exponentially weighted moving average (EWMA) will be developed. GLRT is a well-known statistical fault detection method that relies on maximizing the detection probability for a given false alarm rate. In this paper, we propose to develop GLRT-based EWMA fault detection method that will be able to detect the changes in the values of certain air quality variables; (iii) to develop fault isolation and identification method that allows defining the fault source(s) in order to properly apply appropriate corrective actions. In this paper, reconstruction approach that is based on Midpoint-Radii Principal Component Analysis (MRPCA) model will be developed to handle the types of data and models associated with air quality monitoring networks. All air quality modeling, fault detection, fault isolation and reconstruction methods developed in this paper will be validated using real air quality data (such as particulate matter, ozone, nitrogen and carbon oxides measurement).


  • 주제어

    Data validation .   Air quality monitoring network .   Exponentially weighted moving average .   Generalized likelihood ratio test .   Midpoint-radii .   Principal component analysis.  

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