Abstract: To ensure the accurate and reliable transmission of the measured value of a measurement standard device, research was conducted for the process quality control technology of flowmeter verification in terms of big data analysis. It was the first time that the method for checking verification data with the multivariate linear prediction based on the historical data was explored, which could realize the control indicators of linear regression prediction error within ± 0.1℃ for temperature, －0.01-0.015 MPa for pressure and ±5 m³/h for flow, and the real-time check method based on the mean and standard deviation control charts was proposed. Based on the segment of the flow range of standard turbine flowmeter, the historical data was dynamically calculated to determine the warning limit of the mean and the standard deviation dynamic control charts, which could monitor if the deviation of the standard turbine flowmeter exceeds the dynamic warning limit. Here, the control limit was set as 0.29% for the uncertainty of the device. Thereby, the operation status of the measurement standard device can be presented in real time according to the warning limit and the control limit, and the intelligent analysis and processing of the verification data can be realized, which comprehensively improves the quality and efficiency of metrological verification of natural gas.