Finding
In addition, the trend of acquired data can be used to infer the performance of the pump or the timing of elimination of the MGPS when efficiency becomes poor.
Paper
A Study on PCS for ML-Based Electrical Propulsion System
Citations: 0
Full text
Semantic ScholarAbstract
This study proposes a PCS that enables efficient operation of seawater pumps for ships by implementing ML-based algorithms. Seawater temperature, RPM and power consumption data are acquired from two ships with PCS, analyzed with regression analysis method, and new algorithms are presented. Using the algorithms presented, Ship A saved about 36% compared to the PCS application, and ML-based algorithms in certain sea temperatures of 19 to 27 degrees Celsius and above 32 degrees Celsius were about 1% lower than Ship A's PCS. Ship B saved about 50% compared to PCS not applied, and about 2% more than Ship B's PCS in waters above 19°C, a specified sea temperature. The derived data can be used to suggest the optimum pump speed and sea route. In addition, the trend of acquired data can be used to infer the performance of the pump or the timing of elimination of the MGPS when efficiency becomes poor. 키워드 : 머신러닝, 선박용 해수펌프, 에너지 절감, PCS
Authors
Jong-hak Lee, Hunseok Lee, Jinseok Oh
Journal
The Journal of the Korean Institute of Information and Communication Engineering