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采用新兴的大数据分析技术，通过相关性算法对装置运行数据的挖掘，发现预加氢分馏塔塔底重沸炉F602支路流量与汽油收率有强正相关性，通过适当增大F602支路流量来提高重整汽油收率。在生产中对所提方法进行验证，短期验证结果显示大数据分析结果符合实际验证情况，其中汽油收率平均提高约0．14％，说明通过适当增大预加氢分馏塔塔底重沸炉F602支路流量来提高重整汽油收率的新手段有效，能缓解重整汽油增产瓶颈问题。长期实施效果也证明了大数据技术在提高重整汽油收率及其他石油化工领域的工业分析上是可行的。“,”The traditional optimization methods can not meet the existing demand for improving the yield of gasoline reforming ,and the re-forming gasoline production has reached the bottleneck .In order to further increase gasoline production ,a new method of increasing gasoline yield is proposed .The new big data analysis technology is used to analyze and validate the operation parameters of the plant .Experiments show that the F602 branch flow reducer has a strong positive correlation with gasoline yield through the analysis of large data .The actual in-dustrial test is used based on the verification scheme .Results show that the data analysis is in accordance with the actual verification .And the gasoline yield increases by about 0 .14% .Thus it is proved that the method of increasing the yield of reformed gasoline is feasible by in-creasing the flow rate of F602 .