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NEAR TERM SHIP MOTION FORECASTING FROM PRIOR MOTION

机译:从先前运动预测的近期船舶运动

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Ship-motion forecasting can be useful for naval operations such as aircraft landing, cargo transfer, off-loading of small boats, and ship "mating" between a large transport ship and smaller ships. The forecasted ship motion is particularly useful in sea states above SS3 when unanticipated large motions can suddenly occur. A 5- to 10-second forecast of future ship motion provides the operator time to compensate for the motion to avoid serious collisions. Ship motion forecasting can enable autonomous landing during higher sea states and can also provide an alternative ship location estimate during emergency procedures such as loss of communication link. This paper summarizes the evaluation of four categories of forecasting methodologies: subspace algorithms, autoregressive algorithms, nonlinear autoregressive using a wavelet network, and perturbation error methods. Simulated Model 5415 ship motion was evaluated in 24 conditions including sea states 4-6, ship speeds of 5, 10, 20, and 30 kts, and wave headings 150 and 180 deg (bow and head seas). For each condition, the simulation motion data was divided into twenty 7.5-minute segments consisting of 0.5 to 5 minutes of training data and 2.5 minutes of testing data. Two types of forecasting accuracy metrics were developed. One metric was based on forecasting simulated ship motion and the other metric involved forecasting periods when the motion exceeds threshold limits within a 4-second window, representing a quiescent period. The results indicate that for simulation forecast accuracy, the correlation coefficient between forecasted and actual motion was greater than 80% for 5-sec forecast horizons, and greater than 60% for 10-sec forecast horizons. For motion threshold forecasting, the forecasting accuracy was greater than 90% for 5-sec horizons and greater than 60% for 10-sec horizons. A qualitative assessment of both simulation and threshold metrics indicated that 80% accuracy produces a good forecast and 60% accuracy produces an acceptable forecast. Threshold forecasting can forecast the presence and duration of near-future quiescent periods, enabling safer, more efficient operations and reduced cost of ship-based aviation operations such as launch, recovery, and movement of aircraft.
机译:船舶运动预测对于海军作战(例如飞机降落,货物转运,小型船的卸货以及大型运输船和小型船之间的船舶“交配”)很有用。当SS3之上的海况突然发生无法预料的大运动时,预测的船舶运动特别有用。 5到10秒的未来船舶运动预测可为操作员提供时间来补偿运动,从而避免发生严重的碰撞。船舶运动预测可以在较高海况下实现自主降落,还可以在紧急程序(例如,通信链路丢失)期间提供替代的船舶位置估计。本文总结了四种预测方法的评估:子空间算法,自回归算法,使用小波网络的非线性自回归和摄动误差方法。在包括海况4-6,船速5、10、20和30 kts以及航向150和180度(船首海和头海)在内的24种条件下评估了模拟的5415模型船的运动。对于每种条件,将模拟运动数据分为20个7.5分钟的段,其中包括0.5到5分钟的训练数据和2.5分钟的测试数据。开发了两种类型的预测准确性度量。一种度量是基于对模拟船舶运动的预测,而另一种度量则是在运动超过4秒钟窗口内的阈值限制(代表静止周期)时,预测周期。结果表明,对于模拟预测精度,对于5秒的预测范围,预测运动与实际运动之间的相关系数大于80%,而对于10秒的预测范围,则大于60%。对于运动阈值预测,对于5秒范围的预测准确性大于90%,对于10秒范围的预测准确性大于60%。对模拟量和阈值量度的定性评估表明,80%的准确度可产生良好的预测,而60%的准确度可产生可接受的预测。阈值预测可以预测不久的休止期的存在和持续时间,从而实现更安全,更有效的运营,并降低舰载航空运营(如飞机的发射,恢复和移动)的成本。

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