深水铺管起重船多传感器数据融合技术研究  

Research on Multisensory Data Fusion Technology for Deepwater Pipelay Crane Vessel

作　　者：蔡连博[1] 许文兵[1] 曲俊生[1] 石振华[1] 

机构地区：[1]中国海洋石油总公司深水铺管起重船工程项目组,北京100016

出　　处：《中国造船》2014年第3期202-209,共8页Shipbuilding of China

摘　　要：深水铺管起重船"海洋石油201"是我国首艘DP3级动力定位工程船舶。船上的位置测量系统为动力定位系统提供足够准确和可靠的位置、速度和姿态等信息,是实现精确定位的前提。论文基于卡尔曼滤波算法和联邦卡尔曼滤波算法,对HiPAP501系统传感器数据进行融合研究。通过仿真试验证明了融合方法的有效性,在信息传输和检测过程中减少了外来干扰与设备内部噪声的影响;多传感器信息的利用显著提高了数据的精度和可靠性。Deepwater pipelay crane vessel ＂Hai Yang Shi You 201＂ is a DP3 class dynamic positioning construction vessel. Position measurement system provides accurate and reliable information of position, velocity and attitude for dynamic positioning system, which is the premise of achieving precise positioning. Sensor data fusion for HiPAP501 system is researched in this paper based on both Kalman filtering algorithm and federal Kalman filtering algorithm. The effectiveness of the fusion method has been proved through simulation experiment. The fusion method can reduce external interference in transmission, detection process and reduce internal noise, and the accuracy and reliability of data can be improved by using multi-sensor information.

关 键 词：多传感器数据融合 卡尔曼滤波 联邦卡尔曼滤波 动力定位船舶 

分 类 号：U664.82[交通运输工程—船舶及航道工程]