中文摘要：

为了明确农机总动力增长波动变化的特征,分析不同因素对农机总动力增长波动影响的大小,进而采取有效的措施来稳定和加快农机总动力增长。针对农机总动力增长波动的复杂性与非线性的特点,采用经验模态分解法对1986-2013年农机总动力增长及其影响因素进行多层次、多尺度分解,得到各本征模态函数分量和趋势量,并采用集对分析理论分析农机总动力增长各本征模态函数分量与其相对应影响因素之间的联系度,进而计算得到各影响因素对农机总动力增长波动的综合影响率。结果表明,政府投入、劳均（每个劳动力）播种面积、燃料价格指数、粮食单产、非农产业的发展和第一产业从业人员数对农机总动力增长波动的综合影响率分别为23.89%、23.73%、23.67%、7.13%、7.41%和14.17%,农民人均纯收入、农业劳均产值、机械化农具价格指数、初中文化以上农村劳动力比例4个影响因素对农机总动力增长波动不产生影响,只对增长趋势量有影响。该研究成果为农业机械化发展政策的调整和制定提供了参考。

英文摘要：

As the main indicator to measure the development level of agricultural mechanization, total power of agricultural machinery provides an important reference basis to formulate the development policy for related department of agricultural mechanization. The growth of agricultural machinery total power has important significance to accelerate the development of agricultural mechanization, realize agricultural modernization, construct the comprehensive socialism new countryside, and guarantee food production and food security. Therefore, it is significant to research the main influence factors of growth fluctuations of agricultural machinery total power, and maintain its steady growth. The growth of China＇s agricultural machinery total power is affected by many factors, and its data series have the characteristics of complexity and nonlinearity. Using the empirical mode decomposition（EMD） method, the growth of agricultural machinery total power and its influence factors from 1986 to 2013 were decomposed in multi levels and multi scales, and fluctuation components of intrinsic mode function（IMF） affecting the growth of agricultural machinery total power were obtained. Based on this, set pair analysis（SPA） theory was used to analyze the correlations between each IMF component of the growth of agricultural machinery total power and the corresponding influencing factors, and then the comprehensive influence rate of each factor to the fluctuations of the growth of agricultural machinery total power was calculated. The comprehensive influence rates of government finance investment, planting area per capita, fuel price index, grain yield per unit area, development of non-agricultural industries and number of the first industry professionals were as follows： 23.89%, 23.73%, 23.67%, 7.13%, 7.41% and 14.17% respectively. It showed that the main factors influencing the fluctuations of the growth of agricultural machinery total power were government finance investment, planting area per capita and fuel price inde