Andrzej Romanowski

Dr. Andrzej Romanowski

Institute of Applied Computer Science, Lodz University of Technology, 90-537 Lodz, Poland
orcid

Research Focus & Metrics

Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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12 July 2018 in IEEE Transactions on Industrial Informatics
Verified
Journal Article
Open access
ARAndrzej Romanowski
Andrzej Romanowski
This paper presents a new approach to analyzing measurement records from industrial processes. The proposed methodology is based on the model of contextual processing and uses big data from experimental process tomography datasets. Electrical capacitance tomography (ECT) is used to monitor non-invasive flow and for data acquisition. The measurement data are collected, stored and processed to identify process regimes and process threats. A specific physical modification was introduced into the pneumatic conveying flow rig in order to study flow behaviour under extreme conditions, extending the available knowledge base. A support vector machine (SVM) was applied for data classification. This study illustrates how contextual processing can facilitate data interpretation and opens the way for the development of methods for detecting pre-emergency flow patterns.

30 September 2010 in Flow Measurement and Instrumentation
Verified
Journal Article
Closed access
KGKrzysztof Grudzień
Krzysztof Grudzień
ARAndrzej Romanowski
Andrzej Romanowski
ZCZbigniew Chaniecki
Zbigniew Chaniecki
Maciej NiedostatkiewiczMaciej Niedostatkiewicz
Maciej Niedostatkiewicz
DSDominik Sankowski
Dominik Sankowski

26 January 2010 in Industrial & Engineering Chemistry Research
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Journal Article
Closed access
BMBartosz Matusiak
Bartosz Matusiak
MSMarco Jose da Silva
Marco Jose da Silva
UHUwe Hampel
Uwe Hampel
ARAndrzej Romanowski
Andrzej Romanowski

1 December 2016 in Archives of Electrical Engineering
Verified
Journal Article
Open access
PDF file
HGHela Garbaa
Hela Garbaa
Lidia Jackowska-StrumiłłoLidia Jackowska-Strumiłło
Lidia Jackowska-Strumiłło
KGKrzysztof Grudzień
Krzysztof Grudzień
ARAndrzej Romanowski
Andrzej Romanowski
A new approach to solve the inverse problem in electrical capacitance tomography is presented. The proposed method is based on an artificial neural network to estimate three different parameters of a circular object present inside a pipeline, i.e. radius and 2D position coordinates. This information allows the estimation of the distribution of material inside a pipe and determination of the characteristic parameters of a range of flows, which are characterised by a circular objects emerging within a cross section such as funnel flow in a silo gravitational discharging process. The main advantages of the proposed approach are explicitly: the desired characteristic flow parameters are estimated directly from the measured capacitances and rapidity, which in turn is crucial for online flow monitoring. In a classic approach in order to obtain these parameters in the first step the image is reconstructed and then the parameters are estimated with the use of image processing methods. The obtained results showed significant reduction of computations time in comparison to the iterative LBP or Levenberg-Marquard algorithms.

26 September 2018 in Annals of Computer Science and Information Systems
Verified
Conference Paper
Closed access
ARAndrzej Romanowski
Andrzej Romanowski

11 October 2015
Verified
Conference Paper
Closed access
MSMichał Skuza
Michał Skuza
ARAndrzej Romanowski
Andrzej Romanowski