Evaluation of schemes for detecting and identifying gross errors in process data

Abstract

Ind. Eng. Chem. Res. Prausnitz, J.; Anderson, T.; Grens, E.; Eckert, C.; Hsieh, S.; O'Connell, J. Computer Calculations for Multicomponent Vapor-Liquid and Liquid-Liquid Equilibria; Prentice Hall: Englewood Cliffs, NJ, 1980. Renon, H.; Prausnitz, J. M. AZChEHitherto the detection of gross errors has been focused on the u'se of three separate statistical tests. These tests sometimes give conflicting predictions, and none of them takes into consideration bound violations. In this paper we propose two new composite tests, DMT and EMT, which make use of more than one statistical test to reduce mispredictions and to account for bound violation. These

Recognition Method of Abnormal Data Based on Interval Estimation

“…After detect outliers in marked abnormal data to be processed [7][8][9]. When the overall amount of data is huge and the amount of abnormal data is small (abnormal data generally considered the proportion of 5% or less), excluding outliers direct way is very effective in both in terms of efficiency and reliability.…”

Accurate Identification of Biased Measurements Under Serial Correlation

“…It has been used in a number of methods under the assumption of white noise (Iordache et al 13 , Heenan and Serth 14 , Rosenberg et al 15 , Narasimhan and Mah 16 ). To the authors' knowledge, Kao et al's application of the MT, is the only GED method dealing with serial correlation that has been formally evaluated and thus, should be used as the medium for comparing the performance of the new methods stated here.…”

Sensor Network Design for Failure Detection and Isolation

“…Various methods have been proposed in recent years for gross error detection and isolation in process data (Mah and Tamhane, 1982;Serth and Heenan, 1986;Rosenberg et al, 1987;Narasimhan and Mah, 1987;Crowe, 1989). The parity space or imbalance residual method, which are strictly identical (Maquin and Ragot, 1991), is briefly remember here.…”