Gross Error Elimination Based on the Polynomial Least Square Method in Integrated Monitoring System of Subway

Abstract

The measurement data of parameter in the electrical equipment contains many noises in subway integrated monitoring system. To eliminate the impact of gross error in the measurement data, a polynomial least square curve fitting algorithm is used in this paper. Based on the Rajda criterion, the algorithm gives the variance estimation of the noises, and then uses dynamic threshold to detect and replace the measurement data with gross error by statistical estimation. Finally, a data processing procedure has been presented to deal with the gross error. The practical application indicates that the proposed algorithm can effectively eliminate the gross error in many types of measurement signals so as to ensure the reliability of the monitoring system. DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.4145