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Dammika Seneviratne is a Researcher in Tecnalia Research and Innovation in Spain. He attained a PhD in Offshore Technology from University of Stavanger and Post Doc in Lulea University of Technology. Research interests includes condition monitoring, operation and maintenance; risk-based inspection planning, risk-based maintenance, and RAMS analysis.
Heating, ventilation, and air conditioning (HVAC) systems installed in a passenger train carriage are critical systems, whose failures can affect people or the environment. This, together with restrictive regulations, results in the replacement of critical components in initial stages of degradation, as well as a lack of data on advanced stages of degradation. This paper proposes a hybrid model-based approach (HyMA) to overcome the lack of failure data on a HVAC system installed in a passenger train carriage. The proposed HyMA combines physics-based models with data-driven models to deploy diagnostic and prognostic processes for a complex and critical system. The physics-based model generates data on healthy and faulty working conditions; the faults are generated in different levels of degradation and can appear individually or together. A fusion of synthetic data and measured data is used to train, validate, and test the proposed hybrid model (HyM) for fault detection and diagnostics (FDD) of the HVAC system. The model obtains an accuracy of 92.60%. In addition, the physics-based model generates run-to-failure data for the HVAC air filter to develop a remaining useful life (RUL) prediction model, the RUL estimations performed obtained an accuracy in the range of 95.21–97.80% Both models obtain a remarkable accuracy. The development presented will result in a tool which provides relevant information on the health state of the HVAC system, extends its useful life, reduces its life cycle cost, and improves its reliability and availability; thus enhancing the sustainability of the system.
Antonio Gálvez; Alberto Diez-Olivan; Dammika Seneviratne; Diego Galar. Fault Detection and RUL Estimation for Railway HVAC Systems Using a Hybrid Model-Based Approach. Sustainability 2021, 13, 6828 .
AMA StyleAntonio Gálvez, Alberto Diez-Olivan, Dammika Seneviratne, Diego Galar. Fault Detection and RUL Estimation for Railway HVAC Systems Using a Hybrid Model-Based Approach. Sustainability. 2021; 13 (12):6828.
Chicago/Turabian StyleAntonio Gálvez; Alberto Diez-Olivan; Dammika Seneviratne; Diego Galar. 2021. "Fault Detection and RUL Estimation for Railway HVAC Systems Using a Hybrid Model-Based Approach." Sustainability 13, no. 12: 6828.
Hybrid models combine physics-based models and data-driven models. This combination is a useful technique to detect fault and predict the current degradation of equipment. This paper proposes a physics-based model, which will be part of a hybrid model, for a heating, ventilation, and air conditioning system installed in the passenger vehicle of a train. The physics-based model is divided into four main parts: heating subsystems, cooling subsystems, ventilation subsystems, and cabin thermal networking subsystems. These subsystems are developed when considering the sensors that are located in the real system, so the model can be linked via the acquired sensor data and virtual sensor data to improve the detectability of failure modes. Thus, the physics-based model can be synchronized with the real system to provide better simulation results. The paper also considers diagnostics and prognostics performance. First, it looks at the current situation of the maintenance strategy for the heating, ventilation, air conditioning system, and the number of failure modes that the maintenance team can detect. Second, it determines the expected improvement using hybrid modelling to maintain the system. This improvement is based on the capabilities of detecting new failure modes. The paper concludes by suggesting the future capabilities of hybrid models.
Antonio Gálvez; Dammika Seneviratne; Diego Galar. Hybrid Model Development for HVAC System in Transportation. Technologies 2021, 9, 18 .
AMA StyleAntonio Gálvez, Dammika Seneviratne, Diego Galar. Hybrid Model Development for HVAC System in Transportation. Technologies. 2021; 9 (1):18.
Chicago/Turabian StyleAntonio Gálvez; Dammika Seneviratne; Diego Galar. 2021. "Hybrid Model Development for HVAC System in Transportation." Technologies 9, no. 1: 18.
Integrating Ergonomics in Maintanability: A Case Study from Manufacturing Industry
Kiumars Teymourian; Dammika Seneviratne; Diego Galar. Integrating Ergonomics in Maintanability:A Case Study from Manufacturing Industry. Journal of Industrial Engineering and Management Science 2019, 2018, 131 -150.
AMA StyleKiumars Teymourian, Dammika Seneviratne, Diego Galar. Integrating Ergonomics in Maintanability:A Case Study from Manufacturing Industry. Journal of Industrial Engineering and Management Science. 2019; 2018 (1):131-150.
Chicago/Turabian StyleKiumars Teymourian; Dammika Seneviratne; Diego Galar. 2019. "Integrating Ergonomics in Maintanability:A Case Study from Manufacturing Industry." Journal of Industrial Engineering and Management Science 2018, no. 1: 131-150.
The New Asset Management: Implications of Servitization in Circular Economy
Dammika Seneviratne; Roberto Villarejo; Diego Galar. The New Asset Management: Implicationsof Servitization in Circular Economy. Journal of Industrial Engineering and Management Science 2019, 2018, 109 -120.
AMA StyleDammika Seneviratne, Roberto Villarejo, Diego Galar. The New Asset Management: Implicationsof Servitization in Circular Economy. Journal of Industrial Engineering and Management Science. 2019; 2018 (1):109-120.
Chicago/Turabian StyleDammika Seneviratne; Roberto Villarejo; Diego Galar. 2019. "The New Asset Management: Implicationsof Servitization in Circular Economy." Journal of Industrial Engineering and Management Science 2018, no. 1: 109-120.