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http://dx.doi.org/10.5407/jksv.2021.19.1.062

Real-time SCR-HP(Selective catalytic reduction - high pressure) valve temperature collection and failure prediction using ARIMA  

Lee, Suhwan (School of Mechanical Engineering, PNU)
Hong, Hyeonji (Eco-friendly Smart Ship Parts Technology Innovation Center, PNU)
Park, Jisoo (Hyunsong controls Inc., R&D department)
Yeom, Eunseop (School of Mechanical Engineering, Pusan National University (PNU))
Publication Information
Journal of the Korean Society of Visualization / v.19, no.1, 2021 , pp. 62-67 More about this Journal
Abstract
Selective catalytic reduction(SCR) is an exhaust gas reduction device to remove nitro oxides (NOx). SCR operation of ship can be controlled through valves for minimizing economic loss from SCR. Valve in SCR-high pressure (HP) system is directly connected to engine exhaust and operates in high temperature and high pressure. Long-term thermal deformation induced by engine heat weakens the sealing of the valve, which can lead to unexpected failures during ship sailing. In order to prevent the unexpected failures due to long-term valve thermal deformation, a failure prediction system using autoregressive integrated moving average (ARIMA) was proposed. Based on the heating experiment, virtual data mimicking temperature range around the SCR-HP valve were produced. By detecting abnormal temperature rise and fall based on the short-term ARIMA prediction, an algorithm determines whether present temperature data is required for failure prediction. The signal processed by the data collection algorithm was interpolated for the failure prediction. By comparing mean average error (MAE) and root mean square error (RMSE), ARIMA model and suitable prediction instant were determined.
Keywords
ARIMA; SCR; Data processing;
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