• Application of genetic algorithm in selection of dominant input variables in sensor fault diagnosis of nonlinear systems 

      Elkoujok, M.; Benammar, M.; Meskin, Nader; Al-Naemi, M.; Langari, R. ( 2013 IEEE International Conference on Prognostics and Health Management, PHM 2013 , 2013 , Conference Paper)
      Industrial processes rely heavily on information provided by sensors. Reliability of sensor data is vital to assure an acceptable performance of these complex and nonlinear processes. In this paper, the analytical redundancy ...
    • Multiple sensor fault diagnosis by evolving data-driven approach 

      El-Koujok, M.; Benammar, M.; Meskin, N.; Al-Naemi, M.; Langari, R. ( Elsevier Inc. , 2014 , Article)
      Sensors are indispensable components of modern plants and processes and their reliability is vital to ensure reliable and safe operation of complex systems. In this paper, the problem of design and development of a data-driven ...
    • Multiple sensor fault diagnosis for non-linear and dynamic system by evolving approach 

      El-Koujok, M.; Benammar, M.; Meskin, Nader; Al-Naemi, M.; Langari, R. ( 2012 3rd Annual IEEE Prognostics and System Health Management Conference, PHM-2012 , 2012 , Conference Paper)
      Reliability of sensor measurement is vital to assure the performance of complex and nonlinear industrial operation. In this paper, the problem of designing and development of a data-driven multiple sensor fault detection ...