The invention relates to a method for checking sensor data mined based on an association rule of matrix singular values, which is realized by two parts, namely, the first part is measuring point mining of the similar association rule, while the second part is online checking of the sensor data; and the method comprises the following steps: modeling sought measuring point groups with similar association for least square support vector regression, and selecting all operating condition data by a training sample to cover all operating conditions; and for n measuring points, aggregately establishing (n+1) regression models comprising one residual error generating module of n inputs subtracting n outputs for monitoring operating data, and n No. K data reconstruction modules of (n-1) inputs subtracting a single output for reconstructing the operating data of each measuring point, wherein n is the number of sensors for checking the data on line. The invention provides a concept of fluctuationsimilarity among measuring points of running equipment in the field of uninterrupted industrial production, expands the concept of association rules to similar fluctuated association rules, is supplement and efficient expansion for the association rules in the field, and has actual significance.