Theodor Popescu - Academia.edu (original) (raw)
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Papers by Theodor Popescu
Annual Review in Automatic Programming
Circuits, Systems, and Signal Processing
Neural Network World, 2003
The paper presents a method for multivariate time series forecasting using Independent Component ... more The paper presents a method for multivariate time series forecasting using Independent Component Analysis (ICA), as a preprocessing tool. The idea of this approach is to do the forecasting in the space of independent components (sources), and then to transform back the results to the original time series space. The forecasting can be done separately and with a different method for each component, depending on its time structure. The paper gives also a review of the main algorithms for independent component analysis in the case of instantaneous mixture models, using second and high-order statistics. The method has been applied in simulation to an artificial multivariate time series with five components, generated from three sources and a mixing matrix, randomly generated.
Neural Network World, 2000
International Journal of Vehicle Noise and Vibration, Mar 20, 2015
ABSTRACT The paper presents an approach for machine vibration analysis and health monitoring usin... more ABSTRACT The paper presents an approach for machine vibration analysis and health monitoring using blind source separation (BSS). By this approach, the investigated problem is transferred from the original space of the measurements to the space of independent sources, where the reduced number of components will simplify the analysis problem and where different methods can be applied for scalar signals. The BSS will also provide a mixing model of the sources, so it will be possible to see how the evolution of the estimated sources, determined by BSS, are reflected in the original measurements. The assessment of the method on a real machine, a pump driven by an electromotor, is presented.
Proceedings of the 12th Wseas International Conference on Systems, Jul 22, 2008
ABSTRACT Independent Component Analysis (ICA) is an emerging field of fundamental research with a... more ABSTRACT Independent Component Analysis (ICA) is an emerging field of fundamental research with a wide range of applications such as remote sensing, data communications, speech processing and medical diagnosis. It is motivated by practical scenarios that involve multi-sources and multi-sensors. The key objective of ICA is to retrieve the source signals without resorting to any a priori information about the source signals and the transmission channel. ICA using second-order statistics and high-order statistics based techniques and the corresponding algorithms are presented to perform the blind separation of stationary or cyclostationary sources. In the last part of the paper, a case study with real data having as subject dams displacements monitoring will be presented.
Control Eng Practice, 1996
Google, Inc. (search). ...
2015 16th International Conference on Research and Education in Mechatronics (REM), 2015
2013 7th International Conference on Application of Information and Communication Technologies, 2013
2011 International Conference on Computational Science and Its Applications, 2011
The paper presents a new approach for machine vibration analysis and health monitoring based on b... more The paper presents a new approach for machine vibration analysis and health monitoring based on blind source separation (BSS). So, the problem is transferred from the original space of the measurements to the space of independent sources, where the reduced number of components is going to simplify the monitoring problem while the vibration analysis methods are going to be applied for scalar signals. The assessment of the approach on a real machine is presented in this paper. I. INTRODUCTION Vibration sources in machines are events that generate forces and motion during machine operation. These include: shaft imbalance, impacts (e.g. due to bearing faults), fluc- tuating forces during gear mesh (as a result of small varia- tions during machine operation or in local contact stiffness), electromagnetic forces and pressure- and flow related sources. The approach for machine vibration analysis and health mon- itoring, presented in this paper, makes use of blind source separation (BSS). Blind source separation consists in the recovering of the
2011 IEEE 54th International Midwest Symposium on Circuits and Systems (MWSCAS), 2011
Recent Patents on Signal Processing, 2014
Lecture Notes in Computer Science, 2004
The problem of change detection in the poles of signals having unknown time varying zeroes is add... more The problem of change detection in the poles of signals having unknown time varying zeroes is addressed. It is used, instead of the test statistics based upon the standard likelihood ratio approach, which is of no help in this case because of the unknown zeroes, a test statistics based on an identification method (instrumental variables), which is known to decouple the AR and MA coefficients of the model. The procedure has been used for change detection in modal characteristics of a vibrating structure, a multi-story reinforced concrete building, subject to a strong seismic motion.
2006 IEEE International Symposium on Industrial Electronics, 2006
ABSTRACT The paper presents a new approach for machine vibration analysis and health monitoring c... more ABSTRACT The paper presents a new approach for machine vibration analysis and health monitoring combining blind source separation (BSS) and change detection in source signals. So, the problem is translated from the space of the measurements to the space of independent sources, where the reduced number of components will simplify the monitoring problem and where the change detection methods are applied for scalar signals. The approach has been tested in simulation and the assessment on a real machine is presented in the last part of the paper
Annual Review in Automatic Programming
Circuits, Systems, and Signal Processing
Neural Network World, 2003
The paper presents a method for multivariate time series forecasting using Independent Component ... more The paper presents a method for multivariate time series forecasting using Independent Component Analysis (ICA), as a preprocessing tool. The idea of this approach is to do the forecasting in the space of independent components (sources), and then to transform back the results to the original time series space. The forecasting can be done separately and with a different method for each component, depending on its time structure. The paper gives also a review of the main algorithms for independent component analysis in the case of instantaneous mixture models, using second and high-order statistics. The method has been applied in simulation to an artificial multivariate time series with five components, generated from three sources and a mixing matrix, randomly generated.
Neural Network World, 2000
International Journal of Vehicle Noise and Vibration, Mar 20, 2015
ABSTRACT The paper presents an approach for machine vibration analysis and health monitoring usin... more ABSTRACT The paper presents an approach for machine vibration analysis and health monitoring using blind source separation (BSS). By this approach, the investigated problem is transferred from the original space of the measurements to the space of independent sources, where the reduced number of components will simplify the analysis problem and where different methods can be applied for scalar signals. The BSS will also provide a mixing model of the sources, so it will be possible to see how the evolution of the estimated sources, determined by BSS, are reflected in the original measurements. The assessment of the method on a real machine, a pump driven by an electromotor, is presented.
Proceedings of the 12th Wseas International Conference on Systems, Jul 22, 2008
ABSTRACT Independent Component Analysis (ICA) is an emerging field of fundamental research with a... more ABSTRACT Independent Component Analysis (ICA) is an emerging field of fundamental research with a wide range of applications such as remote sensing, data communications, speech processing and medical diagnosis. It is motivated by practical scenarios that involve multi-sources and multi-sensors. The key objective of ICA is to retrieve the source signals without resorting to any a priori information about the source signals and the transmission channel. ICA using second-order statistics and high-order statistics based techniques and the corresponding algorithms are presented to perform the blind separation of stationary or cyclostationary sources. In the last part of the paper, a case study with real data having as subject dams displacements monitoring will be presented.
Control Eng Practice, 1996
Google, Inc. (search). ...
2015 16th International Conference on Research and Education in Mechatronics (REM), 2015
2013 7th International Conference on Application of Information and Communication Technologies, 2013
2011 International Conference on Computational Science and Its Applications, 2011
The paper presents a new approach for machine vibration analysis and health monitoring based on b... more The paper presents a new approach for machine vibration analysis and health monitoring based on blind source separation (BSS). So, the problem is transferred from the original space of the measurements to the space of independent sources, where the reduced number of components is going to simplify the monitoring problem while the vibration analysis methods are going to be applied for scalar signals. The assessment of the approach on a real machine is presented in this paper. I. INTRODUCTION Vibration sources in machines are events that generate forces and motion during machine operation. These include: shaft imbalance, impacts (e.g. due to bearing faults), fluc- tuating forces during gear mesh (as a result of small varia- tions during machine operation or in local contact stiffness), electromagnetic forces and pressure- and flow related sources. The approach for machine vibration analysis and health mon- itoring, presented in this paper, makes use of blind source separation (BSS). Blind source separation consists in the recovering of the
2011 IEEE 54th International Midwest Symposium on Circuits and Systems (MWSCAS), 2011
Recent Patents on Signal Processing, 2014
Lecture Notes in Computer Science, 2004
The problem of change detection in the poles of signals having unknown time varying zeroes is add... more The problem of change detection in the poles of signals having unknown time varying zeroes is addressed. It is used, instead of the test statistics based upon the standard likelihood ratio approach, which is of no help in this case because of the unknown zeroes, a test statistics based on an identification method (instrumental variables), which is known to decouple the AR and MA coefficients of the model. The procedure has been used for change detection in modal characteristics of a vibrating structure, a multi-story reinforced concrete building, subject to a strong seismic motion.
2006 IEEE International Symposium on Industrial Electronics, 2006
ABSTRACT The paper presents a new approach for machine vibration analysis and health monitoring c... more ABSTRACT The paper presents a new approach for machine vibration analysis and health monitoring combining blind source separation (BSS) and change detection in source signals. So, the problem is translated from the space of the measurements to the space of independent sources, where the reduced number of components will simplify the monitoring problem and where the change detection methods are applied for scalar signals. The approach has been tested in simulation and the assessment on a real machine is presented in the last part of the paper