基于UKF多步和BP修正的船舶升沉运动测量方法

为提高海上风机安装时的稳定性和精准性，需要对浮式起重船进行升沉运动补偿。但由于惯性系统测量的船舶升沉运动信息存在随机漂移和相位超前问题，严重影响升沉补偿系统的实时性和精确性，故本文提出基于UKF多步和BP修正的船舶升沉运动测量方法。基于Stewart波浪运动实验平台模拟船舶升沉运动，采用加速度惯性测量系统采集升沉位移和加速度信息，建立运动的状态空间模型；由此模型建立UKF观测器，并用状态转移矩阵根据动态检测的升沉运动超前相位进行多步观测，消除升沉运动的随机漂移和相位超前；进而结合UKF多步观测值和观测残差训练BP预测模型，通过预测的残差来实时修正多步观测器的观测值，提高测量精度。Stewart平台试验表明，本文测量方法解决了实时检测中船舶升沉运动的漂移和相位超前问题，测量精度可达90%。

Ship heave motion measurement method based on UKF multi-step and BP correction

In order to improve the stability and veracity of offshore wind turbine installation, it is necessary to perform the heave compensation of the floating crane. But the ship heave motion measured by the inertial system has the characteristics of the random drift and the advanced phase, which seriously affects the real time ability and accuracy of the heave compensation system. So this paper proposes a ship heave motion measurement method based on UKF multi-step observer and BP residual correction. Based on the Stewart wave motion experiment platform, the ship heave motion is simulated, and the inertial measurement system is used to collect heave displacement and acceleration information, then the state space model of the motion is established. Thus, a UKF observer is established by the state space model, and then the state transition matrix is used to perform multi-step observation according to the advanced phase of the heave motion of dynamic detection, to eliminate the random drift and the advanced phase of heave motion. And then, UKF multi-step observer and observation residual are applied to train the BP residual prediction model, and then the prediction residual is used to correct the observation of the multi-step observer online to improve measurement accuracy. The experiments based on Stewart platform show that the proposed method solves the problems of the random drift and the advanced phase of ship heave motion, and the measurement accuracy can be improved to 90%.