A computationally simple method is demonstrated for automated identification of steady state and transient state in noisy process signals of an industrial-scale, single or multi-variable process. This steady state and transient state identification method uses the R-statistic method, which is a ratio of estimated variances, and independent of the process variance. It has been implemented for automated identification of steady state of a single variable water flow rate to an absorption column in the Unit Operations Lab and the multi-variable commercial scale distillation process in FRI. When there is an upset in the process the steady state identifier indicates so. Most often the visual identification of steady state agrees with the statist...
Global homotopy continuation is used to identify multiple steady states in ideal reactive flash and ...
In this article, a multivariate statistical process control (MSPC) strategy, devoted to bias identif...
Steady-state solutions represent the long-term response of linear systems due to specified input sig...
This paper introduces a novel steady-state identification (SSI) method based on the auto-regressive ...
This study addresses the steady-state operation and control of an ethanol-water distillation column....
Fault diagnosis in continuous dynamic systems can be challenging, since the variables in these syste...
In this work three new methods are presented for improved identification of measurement biases in li...
The utilization of steady state monitoring techniques has become an established means of providing d...
Most of the existing steady state detection approaches are designed for univariate signals. For mult...
Experimental assessment or prediction of plant steady state is important for many applications in th...
Fault detection and diagnosis have gained an importance in the automation process industries over th...
Gillespie’s direct method is a stochastic simulation algorithm that may be used to calculate the ste...
Process simulation tools are widely adopted for the design and optimization of chemical processes. H...
textToday’s process control industry, which is extensively automated, generates huge amounts of proc...
[EN] In this paper a new process identification method based in open loop step response of overdampe...
Global homotopy continuation is used to identify multiple steady states in ideal reactive flash and ...
In this article, a multivariate statistical process control (MSPC) strategy, devoted to bias identif...
Steady-state solutions represent the long-term response of linear systems due to specified input sig...
This paper introduces a novel steady-state identification (SSI) method based on the auto-regressive ...
This study addresses the steady-state operation and control of an ethanol-water distillation column....
Fault diagnosis in continuous dynamic systems can be challenging, since the variables in these syste...
In this work three new methods are presented for improved identification of measurement biases in li...
The utilization of steady state monitoring techniques has become an established means of providing d...
Most of the existing steady state detection approaches are designed for univariate signals. For mult...
Experimental assessment or prediction of plant steady state is important for many applications in th...
Fault detection and diagnosis have gained an importance in the automation process industries over th...
Gillespie’s direct method is a stochastic simulation algorithm that may be used to calculate the ste...
Process simulation tools are widely adopted for the design and optimization of chemical processes. H...
textToday’s process control industry, which is extensively automated, generates huge amounts of proc...
[EN] In this paper a new process identification method based in open loop step response of overdampe...
Global homotopy continuation is used to identify multiple steady states in ideal reactive flash and ...
In this article, a multivariate statistical process control (MSPC) strategy, devoted to bias identif...
Steady-state solutions represent the long-term response of linear systems due to specified input sig...