Attempts to prevent invasion of marine biofouling on marine vessels are demanding. By developing a system to detect marine fouling on vessels in an early stage of fouling is a viable solution. However, there is a lack of database for fouling images for performing image processing and machine learning algorithm.
A computational efficient battery pack model with thermal consideration is essential for simulation before real-time embedded implementation. The proposed temperature-dependent battery model (LiFePO4 battery cell, ANR26650M1-B from A123 Systems) will increase the lifespan of the battery. The simulation outputs are validated by a set of independent experimental data at a different ambient temperature using the dataset collected at 5 °C, 15 °C, 25 °C, 35 °C and 45 °C.
Noise control is required to ensure crew habitability onboard an offshore platform. Applying noise prediction is important to identify the potential noise problem at the early stage of the offshore platform design to avoid costly retrofitting in the implementation stage. Noise data were collected. The 4 output targets are namely: spatial sound pressure level (SPL), spatial average SPL, structure-borne noise and airborne noise at different octave frequencies (e.g. 125Hz, 250Hz, 500Hz, 1000Hz, 2000Hz, 4000Hz, 8000 Hz).