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中文摘要: 陀螺漂移序列具有非平稳和非线性的特点，针对单一模型难以对其实现精确预测的问题，首次提出一种基于集合经验模态分解(EEMD)和相关向量机(RVM)的混合建模方法，实现对陀螺漂移序列的区间预测。首先，利用集合经验模态分解将漂移序列多个模态和一个余量；将模态区分为噪声和趋势两个分量，对噪声分量建立统计模型，对趋势分量建立RVM模型，两者等权相加还原得混合模型；最后，给定置信度，得到置信区间预测结果。将该方法用于某振动陀螺漂移序列预测实例，结果表明：该混合预测模型能准确预测陀螺漂移,其中RVM的预测精度达到99.86%，且验证集以给定的置信度落在预测区间内，可为陀螺的寿命预测和可靠性诊断提供依据。
Abstract:In view that the time series of gyro drift can not be precisely predicted by single forecasting model due to its non-linear and non-stationary characteristics, interval forecasting for gyro drift series can be obtained with hybrid modeling method based on ensemble empirical mode decomposition (EEMD) and relevance vector machine (RVM) which is first proposed. Firstly, the drift data is decomposed into a series of intrinsic mode function and one residue via EEMD; Secondly, modes is classified into two categories: noise component and trend component, the statistical model of noise component and the RVM model of trend component is established, two models are added with equal weight to establish the hybrid model; In the end, set the confidence coefficient to obtain interval forecasting. By using the proposed method for a vibratory gyro drift prediction, the experiment is made shows: in hybrid model, RVM prediction accuracy is 99.86%, validation set is contained by prediction interval with designated confidence coefficient. The hybrid model could provide reliable evidence for life prediction and reliability diagnoses of gyro.
keywords: gyro drift modeling forecasting ensemble empirical mode decomposition relevance vector machine
文章编号：cg15000371 中图分类号： 文献标志码：
基金项目:总装探索研究项目“半球谐振陀螺惯导系统技术”
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