Browsing by Author "Al-Naemi, M."
Now showing items 1-5 of 5
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Application of genetic algorithm in selection of dominant input variables in sensor fault diagnosis of nonlinear systems
( 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
( 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
( 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 ... -
Sensor data validation and fault diagnosis using Auto-Associative Neural Network for HVAC systems
( Elsevier Ltd , 2020 , Article)The Heating, Ventilation, and Air conditioning (HVAC) system is a major system in buildings for conditioning the indoor environment. Sensor data validation and fault diagnosis for HVAC systems are essentially important to ... -
Sensor Fault Diagnosis of Multi-Zone HVAC Systems Using Auto-Associative Neural Network
( Institute of Electrical and Electronics Engineers Inc. , 2019 , Conference Paper)This paper presents a data-driven sensor fault diagnosis algorithm for multi-zone Heating, Ventilation, and Air conditioning (HVAC) systems based on an Auto-Associative Neural Networks (AANNs) framework. The proposed method ...