Experimental Investigation of the Performance of a Tuned Heave Plate Energy Harvesting System for a Semi-Submersible Platform

Heave plates are widely used for improving the sea keeping performance of ocean structures. In this paper, a novel tuned heave plate energy harvesting system (THPEH) is presented for the motion suppression and energy harvesting of a semi-submersible platform. The heave plates are connected to the platform though a power take-off system (PTO) and spring supports. The performance of the THPEH was investigated through forced oscillation tests of a 1:20 scale model. Firstly, the hydrodynamic parameters of the heave plate were experimentally studied under different excitation motion conditions, and a force model of the power take-off system was also established through a calibration test. Then, the motion performance, control performance, and energy harvesting performance of the THPEH subsystem were systematically studied. The effects of the tuned period and PTO damping on the performance of the THPEH were analyzed. Finally, a comparison between the conventional fixed heave plate system and THPEH was carried out. The results show that a properly designed THPEH could consume up to 2.5 times the energy from the platform motion compared to the fixed heave plate system, and up to 80% of the consumed energy could be captured by the PTO system. This indicates that the THPEH could significantly reduce the motion of the platform and simultaneously provide considerable renewable energy to the platform.

Real-Time Webcam Heart-Rate and Variability Estimation with Clean Ground Truth for Evaluation

Remote photo-plethysmography (rPPG) uses a camera to estimate a person’s heart rate (HR). Similar to how heart rate can provide useful information about a person’s vital signs, insights about the underlying physio/psychological conditions can be obtained from heart rate variability (HRV). HRV is a measure of the fine fluctuations in the intervals between heart beats. However, this measure requires temporally locating heart beats with a high degree of precision. We introduce a refined and efficient real-time rPPG pipeline with novel filtering and motion suppression that not only estimates heart rates, but also extracts the pulse waveform to time heart beats and measure heart rate variability. This unsupervised method requires no rPPG specific training and is able to operate in real-time. We also introduce a new multi-modal video dataset, VicarPPG 2, specifically designed to evaluate rPPG algorithms on HR and HRV estimation. We validate and study our method under various conditions on a comprehensive range of public and self-recorded datasets, showing state-of-the-art results and providing useful insights into some unique aspects. Lastly, we make available CleanerPPG, a collection of human-verified ground truth peak/heart-beat annotations for existing rPPG datasets. These verified annotations should make future evaluations and benchmarking of rPPG algorithms more accurate, standardized and fair.