Gross error detection and stage efficiency estimation in a separation process
- Texas A and M Univ., Kingsville, TX (United States). Dept. of Chemical and Natural Gas Engineering
- Univ. of Dar-Es-Salaam (Tanzania, United Republic of). Dept. of Chemical and Process Engineering
Accurate process models are required for optimization and control in chemical plants and petroleum refineries. These models involve various equipment parameters, such as stage efficiencies in distillation columns, the values of which must be determined by fitting the models to process data. Since the data contain random and systematic measurement errors, some of which may be large (gross errors), they must be reconciled to obtain reliable estimates of equipment parameters. The problem thus involves parameter estimation coupled with gross error detection and data reconciliation. MacDonald and Howat (1988) studied the above problem for a single-stage flash distillation process. Their analysis was based on the definition of stage efficiency due to Hausen, which has some significant disadvantages in this context, as discussed below. In addition, they considered only data sets which contained no gross errors. The purpose of this article is to extend the above work by considering alternative definitions of state efficiency and efficiency estimation in the presence of gross errors.
- OSTI ID:
- 5897202
- Journal Information:
- AIChE Journal (American Institute of Chemical Engineers); (United States), Vol. 39:10; ISSN 0001-1541
- Country of Publication:
- United States
- Language:
- English
Similar Records
Thermal performance monitoring and assessment in Dukovany nuclear power plant
An Adaptive Bayesian Parameter Estimation of a Synchronous Generator Under Gross Errors