Journal ArticleDOI
Generalized likelihood ratio method for gross error identification
TLDR
In this paper, a nouvelle methode statistique is utilisee for detecter, identifier and estimer les grosses erreurs (erreurs systematiques and fuites) which peuvent se presenter dans les procedes chimiques en regime permanent.Abstract:
Une nouvelle methode statistique est utilisee pour detecter, identifier et estimer les grosses erreurs (erreurs systematiques et fuites) qui peuvent se presenter dans les procedes chimiques en regime permanent. Developpement d'un modele mathematique pour decrire les fuites et les erreurs systematiques. Une nouvelle strategie de detection de grosses erreurs multiples basee sur la compensation serielle des grosses erreurs est aussi proposeeread more
Citations
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Journal ArticleDOI
Statistical process monitoring: basics and beyond
TL;DR: It is demonstrated that the reconstruction-based framework provides a convenient way for fault analysis, including fault detectability, reconstructability and identifiability conditions, resolving many theoretical issues in process monitoring.
Journal ArticleDOI
Data reconciliation — Progress and challenges
TL;DR: The detection of gross errors in data and of pre-adjustment of data, finding departures from steady state, estimation of the variance structure of the data, observability of unmeasured quantities and redundancy of measurements are discussed.
Journal ArticleDOI
Linear constraint relations in biochemical reaction systems: II. Diagnosis and estimation of gross errors
TL;DR: Conservation equations derived from elemental balances, heat balances, and metabolic stoichiometry, can be used to constrain the values of conversion rates of relevant components for detection and localization of significant errors of the following types.
Journal ArticleDOI
Redescending estimators for data reconciliation and parameter estimation
Nikhil Arora,Lorenz T. Biegler +1 more
TL;DR: In this article, the three part redescending estimator of Hampel was compared with the Fair function of Huber estimator and the Fair estimator for data reconciliation and parameter estimation.
Journal ArticleDOI
Simultaneous robust data reconciliation and gross error detection through particle swarm optimization for an industrial polypropylene reactor
TL;DR: In this article, a nonlinear dynamic data reconciliation procedure (NDDR) based on the particle swarm optimization (PSO) method was developed and validated in line and in real time with actual industrial data obtained for an industrial polypropylene reactor.
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