At present, the univariate control chart with measurement error has significantly reduced the impact of measurement error on the performance of the control chart, and plays an important role in the actual production process monitoring. However, due to the complexity of multivariate control charts, especially when the covariance matrix shifts, there is still insufficient research on multivariate control charts with measurement errors. Therefore, this paper combines the multivariate measurement error model to construct ME-KQE and KME-KQE control charts that have significant advantages over the covariance matrix drift in the monitoring process, and analyzes the effect of measurement error on detection efficiency. Finally, this article shows that it has a good monitoring effect on the data with measurement errors in practical applications.