A new approach to the identification of gross errors in chemical engineering measurements

Madron, František

doi:10.1016/0009-2509(85)80121-4

Cited by 21 publications

(11 citation statements)

References 9 publications

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“…Polley et al 18 , is chosen. Both fouling rate models are shown in Equations (27) and (28) respectively. (29) and (30).…”

Section: Fouling Modellingmentioning

confidence: 99%

“…In this work, the "global test" is used for addressing the detection problem 27 . This method uses a statistical test to determine the presence of gross errors.…”

Section: Gross Error Detection and Identificationmentioning

confidence: 99%

“…For the objective function, it is desired to minimize the root mean square error (RMSE) between the fouling resistances calculated from the reconciled data ( ) using Equation (34), and from the ones calculated using the fouling rate models for shell-side and tube-side ̂ (Equations (27) and 28…”

Section: Gross Error Detection and Identificationmentioning

confidence: 99%

“…Outlet temperatures are selected as a criterion for this comparison. Shell-side and tube-side fouling are represented by the fouling rate models from Equations(27) and(28).…”

mentioning

confidence: 99%

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Estimation of Fouling Model Parameters for Shell Side and Tube Side of Crude Oil Heat Exchangers Using Data Reconciliation and Parameter Estimation

Loyola-Fuentes

Jobson

Smith

2019

Ind. Eng. Chem. Res.

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Fouling modelling in crude oil heat exchangers is of great importance industrially. Current approaches use empirical or semi-empirical approaches, where fouling rate models are necessary. A series of parameters need to be determined, which directly depend on the nature and type of crude oil. These parameters can be estimated either by using laboratory experiments or, in principle, by measured process-data. This work focuses on the estimation of fouling rate model parameters using measured-data. An optimization-based data reconciliation approach, which accounts for random and gross errors, is integrated with a parameter-fitting algorithm. The methodology is tested in a case study, where a multi-pass heat exchanger is simulated. The effects of measurement error and fouling deposition on both sides are addressed. The fouling resistance is predicted and compared with the simulated data, showing good agreement as well as providing evidence for a successful separation of fouling resistances on both sides of a heat exchanger. Finally, studies are presented to show the isolation process for the minimum gross error magnitude, for different gross error locations.

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“…Polley et al 18 , is chosen. Both fouling rate models are shown in Equations (27) and (28) respectively. (29) and (30).…”

Section: Fouling Modellingmentioning

confidence: 99%

“…In this work, the "global test" is used for addressing the detection problem 27 . This method uses a statistical test to determine the presence of gross errors.…”

Section: Gross Error Detection and Identificationmentioning

confidence: 99%

Section: Gross Error Detection and Identificationmentioning

confidence: 99%

“…Outlet temperatures are selected as a criterion for this comparison. Shell-side and tube-side fouling are represented by the fouling rate models from Equations(27) and(28).…”

mentioning

confidence: 99%

See 2 more Smart Citations

Estimation of Fouling Model Parameters for Shell Side and Tube Side of Crude Oil Heat Exchangers Using Data Reconciliation and Parameter Estimation

Loyola-Fuentes

Jobson

Smith

2019

Ind. Eng. Chem. Res.

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“…Madron (1985a) has shown that the detection of added gross errors in a stream does not necessarily imply that there will be gross errors in the balances around nodes to which that stream is connected. Madron (1985b) has also discussed the use of the non-central chi-square distribution as a means of detecting gross errors. His applications were restricted to a single gross error.…”

Section: Determination Of Measurement Adjustmentsmentioning

confidence: 99%

Reconciliation of mass flow rate measurements in a chemical extraction plant

1989

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Since measurements of flow rates in a steady state chemical process are subject to errors, the laws of conservation and other constraints are violated. Total mass flow data from a chemical extraction plant are used to determine whether the process operated at steady state and to estimate the variances of the measurements. The data are then reconciled so as to minimize the weighted sum of squares of the adjustments and to test for gross error. Deletion of either of two particular flow rates is shown to remove all of the apparent gross errors in the data.

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Malfunction diagnosis using quantitative models with non‐boolean reasoning in expert systems

Kramer

1987

AIChE Journal

135

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An approach to chemical plant fault diagnosis is presented that utilizes patterns of violation and satisfaction of the quantitative constraints governing the process. Process knowledge consists of a list of the operational constraints on the plant together with sufficient conditions for violation of each constraint. Interpretation of the pattern of constraint violations is treated by Boolean and non-Boolean techniques. It is shown that non-Boolean reasoning techniques increase the stability and sensitivity of the diagnosis in the presence of noise. The techniques introduced in this paper are easily implemented in rule-based expert systems using certainty factors. M. A. KramerDepartment of Chemical Engineering Massachusetts Institute of Technology Cambridge, MA 02139 IntroductionIn an operating chemical plant, product quality is maintained by monitoring process variables and controlling their fluctuations within a desired range. When operating conditions vary outside these design limits, not only is product quality in jeopardy, but if left uncorrected these variations could result in a catastrophic event such as an explosion, fire, or the release of toxic chemicals. Diagnosis of process malfunctions is a difficult task

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A new approach to the identification of gross errors in chemical engineering measurements

Cited by 21 publications

References 9 publications

Estimation of Fouling Model Parameters for Shell Side and Tube Side of Crude Oil Heat Exchangers Using Data Reconciliation and Parameter Estimation

Estimation of Fouling Model Parameters for Shell Side and Tube Side of Crude Oil Heat Exchangers Using Data Reconciliation and Parameter Estimation

Reconciliation of mass flow rate measurements in a chemical extraction plant

Malfunction diagnosis using quantitative models with non‐boolean reasoning in expert systems

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