Lag in detecting ship heave motion signals severely affects the performance of ocean heave compensation systems. Therefore, accurate heave motion prediction can effectively improve the stability and real-time performance of these systems. To improve the engineering practicability of a heave motion prediction model, we designed an autoregressive time-series model featuring high calculation efficiency, simple programing, and a small accumulation error. Moreover, to further address the poor adaptability of the model to nonlinear and nonstationary complex sea conditions and long-term predictions, we developed a combined prediction model based on wavelet transform and improved autoregression using the wavelet multiscale analysis method and achieved online multistep prediction of heave motions by decomposing and transforming historical data, reconstructing sub-sequence prediction, and forecasting data synthesis. Finally, theoretical testing and experiments were conducted on stationary random waveforms and nonstationary waveforms measured on ships. The analysis results show that the combined model exhibits good prediction performance and can effectively reduce the control error of the ocean heave compensation system caused by the lag in the heave motion signal detection.

To achieve the best separation effect and oil phase collection efficiency, a self-induced vortex oil collector was designed to collect residual oil from the turbulent sea. The inlet flow angle and suction pipe insertion depth of the device were adjusted and optimized via numerical simulation calculations. By comparing the volume of oil phase remaining inside the device in the same operation time, we concluded that at an inlet flow angle of 20° and a suction pipe insertion depth of h/3, the device could maintain a high oil phase separation efficiency, suppress oil-water mixing, and reduce oil-water interface diffusion and impurities. After determining the optimal structure, we analyzed the oil removal effect of the device in different water surface environments by changing its inlet flow velocity. The higher the inlet flow velocity, the higher the performance of the device for collecting the oil phase and better its oil removal effect. In addition, the entire oil collection process occurs inside the device without being affected by the external environment, suggesting that the device can collect oil from complex water surface environments. Moreover, the main body of the device has no moving parts, hence, it relies solely on the baffle to guide the swirl for collecting the oil phase.