The supervision and verification of grain bulks is an important segment during storage. Reliable reserves monitoring method for grain storage can effectively guarantee national grain quantity security. To solve the problems such as time consuming, labor cost and other problems in the manual audit of reserves, a monitoring method for grain storage quantity based on correlation analysis was proposed. Firstly, the autocorrelation and intercorrelation of the temperature measurement planes in the grain bulks were analyzed, so that the abnormal date and planes were detected. Secondly, the autocorrelation and the intercorrelation of temperature measurement lines in the abnormal date were analyzed, and the abnormal lines were detected in the abnormal date. Then the autocorrelation and intercorrelation of the temperature measurement points in the abnormal temperature line were analyzed. The number of abnormal points was counted, and the type of abnormal occurrence and the abnormal proportion were determined according to the number. At the same time, the granaries were selected in three storage grain areas: low temperature zone, medium temperature zone and high temperature zone for correlation analysis. According to the analysis results, the threshold of autocorrelation coefficient of temperature measurement plane was set to be 08, the threshold of change rate of intercorrelation coefficient was [-0.15d-1, 0.15d-1]; the threshold of autocorrelation coefficient of temperature measurement line was 0.8; and the autocorrelation coefficient of temperature measurement point was 0.8. Meanwhile, the analysis results showed that the correlation between temperature measurement lines and points in short period can not be used as an anomaly criterion. The supervision test of grain storage was carried out. The test results showed that the grain storage supervision method based on the correlation analysis can not only realize the reserves monitoring, but also detect the local heating and other anomalies of grain bulk. The purpose was to analyze the correlation coefficient of grain temperature data in the granaries of several different grain storage areas, monitor the quantity of grain and provide a theoretical basis for the analysis of grain data in different regions.