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中文摘要：
应用经验模式分解（EMD）方法分析抽油机系统效率变化的趋势项。讨论了EMD方法的端点效应。为了解决EMD的端点效应，首先应用支持向量回归（SVR）方法对抽油机系统效率测试数据进行回归和预测，与实测数据对比表明SVR回归和预测具有较高精度；然后应用SVR方法对系统效率测试原始数据进行双边延拓，对延拓后的数据信号进行经验模式分解。延拓前后分解所得的效率变化趋势对比表明，SVR方法可以有效地解决EMD的端点效应，提高抽油机系统效率变化趋势的预测精度。
英文摘要：
We apply the empirical mode decomposition （EMD） method to analyzing the trend of change in the efficiency of an oil well system and deal with the end effects of the EMD. First we employ the support vector regression （SVR） method to regress and predict the test data on the efficiency of the system. The comparison of the test data with measurement data shows that the regression and prediction with the SVR method are highly accurate. Then we carry out the bilateral extension of the crude test data of the systemts efficiency with the SVR method. The signal of bilaterally-extended data is decomposed via the EMD method. The comparison of the trend of efficiency change before and after extension indicate that the SVR method can effectively solve the end effects of EMD and enhance the accuracy of predicting the trend of change.
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