【摘要】 采取RTK-GNSS技术对海上石油平台桩腿结构进行水平位移监测以分析其振动特征.针对复杂环境下多路径效应对RTK-GNSS监测结果的影响,利用草地和水域两种场地环境进行多路径效应测试试验.经分析,水域环境中多路径误差更大,而对于极为复杂的海上环境更需要对监测数据滤波降噪以削弱多路径误差.因此,提出了基于自相关函数和相关系数的集合经验模态分解(EEMD)-切比雪夫滤波对埕岛油田一平台桩腿结构的RTK-GNSS监测数据进行处理.结果表明:(1)RTK-GNSS技术能够用于海上环境中的平台桩腿动态位移监测;(2)自相关函数与相关系数相联合可以实现本征模态函数的有效选取和信号重构;(3)降噪前后信号的相关性均高于0.85,证明所提滤波方法既能保留有效信息成分又能削弱多路径误差;(4)经降噪后,可更清晰地看出桩腿结构的实时水平位移信息及运动轨迹,为海上结构监测提供了更优的途径.更多还原

【Abstract】 RTK-GNSS technology was adopted to monitor the horizontal displacement of the offshore oil platform pile leg structure to analyze its vibration characteristics. Aiming at the impact of multipath effects on the RTK-GNSS monitoring results in complex environments,a multipath effect test experiment was conducted using two field environments of grassland and water. Analysis results revealed a greater multipath error in the water environment. However,it was necessary to filter and reduce noise on the monitoring data for extremely complex marine environments to eliminate multipath errors. Therefore,the ensemble empirical mode decomposition(EEMD)-Chebyshev filter based on autocorrelation function and correlation coefficient was proposed to process the RTK-GNSS deformation monitoring data of the pile leg structure of Chengdao oilfield. Results showed that:(1)RTK-GNSS technology can be used on the sea dynamic deformation monitoring of platform legs in the environment;(2)the combined autocorrelation function and correlation coefficient can achieve an effective selection and signal reconstruction of intrinsic modal functions;(3)the correlation of signals before and after noise reduction was higher than 0.85,which proved that the proposed filtering method can retain effective information components and suppress multipath errors;and(4)after noise reduction,real-time horizontal displacement information and movement trajectory of the pile leg structure was evident,providing a better way for the deformation monitoring of offshore structures.更多还原