To identify the endemic error of the precise point positioning which cannot be weakened or eliminated in precise point positioning (PPP) zero-difference model, the 24 h observation data acquired from CHAN station on O...To identify the endemic error of the precise point positioning which cannot be weakened or eliminated in precise point positioning (PPP) zero-difference model, the 24 h observation data acquired from CHAN station on Oct 31st, 2010, were adopted for analyses, different correction models of various errors were discussed and their influences on traditional zero-difference model were analyzed. The results show that the errors cannot be ignored. They must be corrected with suitable models and estimated with auxiliary parameters. The influence magnitudes of all errors are defined, and the results have guiding significance to improve the accuracy of precise point positioning zero-difference model.展开更多
基金Project(20060417004)supported by the PhD Programs Foundation of Ministry of Education of ChinaProject(2009S049)supported by the Liaoning Province University Research Program,China
文摘To identify the endemic error of the precise point positioning which cannot be weakened or eliminated in precise point positioning (PPP) zero-difference model, the 24 h observation data acquired from CHAN station on Oct 31st, 2010, were adopted for analyses, different correction models of various errors were discussed and their influences on traditional zero-difference model were analyzed. The results show that the errors cannot be ignored. They must be corrected with suitable models and estimated with auxiliary parameters. The influence magnitudes of all errors are defined, and the results have guiding significance to improve the accuracy of precise point positioning zero-difference model.
文摘偏航角零点漂移严重影响风电机组性能,将之消除的前提是对其进行可靠且快速的检测。基于风能捕获机理,该文提出一种运用机器学习算法的偏航角零点漂移诊断方法。首先,采用孤立森林(isolated forest,IF)异常值检测算法对数据进行预处理;其次,建立非参数模型稀疏高斯过程回归(sparse Gaussian process regression,SGPR)估计偏航角零点漂移;最后,利用多个风电场的风电机组实际运行数据对所提方法进行验证,并分析不同诊断模型对数据量的依赖性。结果表明:IF+SGPR方法准确性高,所需数据量少,能够快速诊断偏航角零点漂移;该诊断方法能够应用于各种电场不同型号的风电机组,普适性较高。
