Abstract Data rectification can be classified into two parts: data reconciliation, gross error detection and identification. Gross error detection and identification is the bottleneck of data rectification. For bias type of gross error, existing methods cannot deal with the case effectively that there are multiple gross errors in measurements. In order to address the problem, the concept of gross error identifiability of process is proposed. And the identifiable condition of gross errors is derived. An identification approach based on parameter estimation is proposed. The identification results show that the method can identify multiple gross errors existing in the measurements accurately.