Identification of trends in process measurements using the wavelet transform

Flehmig, Folko; Watzdorf, R. von; Marquardt, Wolfgang

doi:10.1016/s0098-1354(98)00092-1

Cited by 40 publications

(27 citation statements)

References 5 publications

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“…Alternatively to the method applied in this paper , Flehmig et al (1998) and Akbaryan & Bishnoi (2000) present other wavelet-based methods for qualitative interpretation of data. Typical applications of these methods aim at process monitoring and diagnosis (Akbaryan & Bishnoi 2001;Rubio et al 2004;Flehmig & Marquardt 2006) or process data mining (Stephanopoulos et al 1997).…”

Section: Introductionmentioning

confidence: 99%

Qualitative representation of trends: an alternative approach to process diagnosis and control

Villez

Rosén

Anctil

et al. 2008

Water Science and Technology

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The potential for qualitative representation of trends in the context of process diagnosis and control is evaluated in this paper. The technique for qualitative description of the data series is relatively new to the field of process monitoring and diagnosis and is based on the cubic spline wavelet decomposition of the data. It is shown that the assessed qualitative description of trends can be coupled easily with existing process knowledge and does not demand the user to understand the underlying technique in detail, in contrast to, for instance, multivariate techniques in Statistical Process Control. The assessed links can be integrated straightforwardly into the framework of supervisory control systems by means of look-up tables, expert systems or case-based reasoning frameworks. This in turn allows the design of a supervisory control system leading to fully automated control actions. The technique is illustrated by an application to a pilot-scale SBR.

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Section: Introductionmentioning

confidence: 99%

Qualitative representation of trends: an alternative approach to process diagnosis and control

Villez

Rosén

Anctil

et al. 2008

Water Science and Technology

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“…Wavelet-based methods however, try to separate signals from noises and not to degrade them. WT for data processing has been proved by many authors as the most robust technique for extracting the true process trend and omitting the random errors [18][19][20][21][22].…”

Section: De-noising Methodsmentioning

confidence: 99%

Combination of data rectification techniques and soft sensor model for robust prediction of sulfur content in HDS process

Shokri¹,

Marvast²,

Sadeghi

et al. 2016

Journal of the Taiwan Institute of Chemical Engineers

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“…The method first tests the equality of the covariance matrices of consecutive time windows and then a second test establishes whether the means of the two periods are equal using the Hotelling's T 2 -test (Hotelling, 1931). Alternatively, methods have been developed that do not require a time window, see Flehmig et al (1998); Cao and Rhinehart (1995); Rhinehart (1995); Brown and Rhinehart (2000). According the authors, these methods are faster, but typically also applicable only to noisy measurements.…”

Section: Simulation Stop Timementioning

confidence: 99%

A methodology and a tool for evaluating hybrid electric powertrain configurations

Murgovski

Sjöberg

Fredriksson

2011

IJEHV

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This paper describes a methodology for automatic optimization of hybrid electric powertrains. This methodology is developed and implemented in a tool, CAPSimO, and the paper is written in the form of describing the tool. Given the user inputs, which are dynamic vehicle model, driving cycle and optimization criterion, the tool first produces a simplified powertrain model in a form of static maps, before dynamic programming is used to find an optimal power split which minimizes the chosen criterion. The tool does not require that the vehicle model is transparent, which makes it possible to work on models hidden for intellectual property reasons. The paper presents two examples of powertrain evaluation, in terms of fuel consumption, for a parallel and a parallel-series powertrain.

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Identification of trends in process measurements using the wavelet transform

Cited by 40 publications

References 5 publications

Qualitative representation of trends: an alternative approach to process diagnosis and control

Qualitative representation of trends: an alternative approach to process diagnosis and control

Combination of data rectification techniques and soft sensor model for robust prediction of sulfur content in HDS process

A methodology and a tool for evaluating hybrid electric powertrain configurations

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