The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Istvan Z Kiss - One of the best experts on this subject based on the ideXlab platform.
-
restoring Oscillatory Behavior from amplitude death with anti phase synchronization patterns in networks of electrochemical oscillations
Chaos, 2016Co-Authors: Raphael Nagao, Jurgen Kurths, Istvan Z KissAbstract:The dynamical Behavior of delay-coupled networks of electrochemical reactions is investigated to explore the formation of amplitude death (AD) and the synchronization states in a parameter region around the amplitude death region. It is shown that difference coupling with odd and even numbered ring and random networks can produce the AD phenomenon. Furthermore, this AD can be restored by changing the coupling type from difference to direct coupling. The restored oscillations tend to create synchronization patterns in which neighboring elements are in nearly anti-phase configuration. The ring networks produce frozen and rotating phase waves, while the random network exhibits a complex synchronization pattern with interwoven frozen and propagating phase waves. The experimental results are interpreted with a coupled Stuart-Landau oscillator model. The experimental and theoretical results reveal that AD Behavior is a robust feature of delayed coupled networks of chemical units; if an Oscillatory Behavior is r...
-
restoring Oscillatory Behavior from amplitude death with anti phase synchronization patterns in networks of electrochemical oscillations
Chaos, 2016Co-Authors: Raphael Nagao, Jurgen Kurths, Wei Zou, Istvan Z KissAbstract:The dynamical Behavior of delay-coupled networks of electrochemical reactions is investigated to explore the formation of amplitude death (AD) and the synchronization states in a parameter region around the amplitude death region. It is shown that difference coupling with odd and even numbered ring and random networks can produce the AD phenomenon. Furthermore, this AD can be restored by changing the coupling type from difference to direct coupling. The restored oscillations tend to create synchronization patterns in which neighboring elements are in nearly anti-phase configuration. The ring networks produce frozen and rotating phase waves, while the random network exhibits a complex synchronization pattern with interwoven frozen and propagating phase waves. The experimental results are interpreted with a coupled Stuart-Landau oscillator model. The experimental and theoretical results reveal that AD Behavior is a robust feature of delayed coupled networks of chemical units; if an Oscillatory Behavior is required again, even a small amount of direct coupling could be sufficient to restore the oscillations. The restored nearly anti-phase Oscillatory patterns, which, to a certain extent, reflect the symmetry of the network, represent an effective means to overcome the AD phenomenon.
Raphael Nagao - One of the best experts on this subject based on the ideXlab platform.
-
restoring Oscillatory Behavior from amplitude death with anti phase synchronization patterns in networks of electrochemical oscillations
Chaos, 2016Co-Authors: Raphael Nagao, Jurgen Kurths, Istvan Z KissAbstract:The dynamical Behavior of delay-coupled networks of electrochemical reactions is investigated to explore the formation of amplitude death (AD) and the synchronization states in a parameter region around the amplitude death region. It is shown that difference coupling with odd and even numbered ring and random networks can produce the AD phenomenon. Furthermore, this AD can be restored by changing the coupling type from difference to direct coupling. The restored oscillations tend to create synchronization patterns in which neighboring elements are in nearly anti-phase configuration. The ring networks produce frozen and rotating phase waves, while the random network exhibits a complex synchronization pattern with interwoven frozen and propagating phase waves. The experimental results are interpreted with a coupled Stuart-Landau oscillator model. The experimental and theoretical results reveal that AD Behavior is a robust feature of delayed coupled networks of chemical units; if an Oscillatory Behavior is r...
-
restoring Oscillatory Behavior from amplitude death with anti phase synchronization patterns in networks of electrochemical oscillations
Chaos, 2016Co-Authors: Raphael Nagao, Jurgen Kurths, Wei Zou, Istvan Z KissAbstract:The dynamical Behavior of delay-coupled networks of electrochemical reactions is investigated to explore the formation of amplitude death (AD) and the synchronization states in a parameter region around the amplitude death region. It is shown that difference coupling with odd and even numbered ring and random networks can produce the AD phenomenon. Furthermore, this AD can be restored by changing the coupling type from difference to direct coupling. The restored oscillations tend to create synchronization patterns in which neighboring elements are in nearly anti-phase configuration. The ring networks produce frozen and rotating phase waves, while the random network exhibits a complex synchronization pattern with interwoven frozen and propagating phase waves. The experimental results are interpreted with a coupled Stuart-Landau oscillator model. The experimental and theoretical results reveal that AD Behavior is a robust feature of delayed coupled networks of chemical units; if an Oscillatory Behavior is required again, even a small amount of direct coupling could be sufficient to restore the oscillations. The restored nearly anti-phase Oscillatory patterns, which, to a certain extent, reflect the symmetry of the network, represent an effective means to overcome the AD phenomenon.
Ibrahim Mustafa - One of the best experts on this subject based on the ideXlab platform.
-
two parameter continuation and bifurcation strategies for Oscillatory Behavior elimination from a zymomonas mobilis fermentation system
Chemical Engineering & Technology, 2015Co-Authors: Ibrahim MustafaAbstract:Two-parameter continuation and bifurcation analysis strategies were applied to deal with the Oscillatory phenomena of a Zymomonas mobilis ethanol fermentation system. A structured verified non-linear mathematical model considering the physiological limitations of microorganisms for a single continuous fermenter for ethanol production using Z. mobilis was built to identify the Hopf bifurcation (HB) points, which indicate the Oscillatory Behavior, using the inlet substrate concentration and the dilution rate as bifurcation parameters. The path of the HB points can be determined with different controlling operating parameters. It was found that with the addition of a small amount of cells or ethanol to the feed stream or by increasing the dilution rate, the oscillations could be eliminated and steady-state Behavior was attained. Using a two-parameter continuation strategy, the Z. mobilis fermentation system could operate at steady state without Oscillatory Behavior.
Ming Liang - One of the best experts on this subject based on the ideXlab platform.
-
auto obsd automatic parameter selection for reliable Oscillatory Behavior based signal decomposition with an application to bearing fault signature extraction
Mechanical Systems and Signal Processing, 2017Co-Authors: Huan Huang, Natalie Baddour, Ming LiangAbstract:Abstract Bearing signals are often contaminated by in-band interferences and random noise. Oscillatory Behavior-based Signal Decomposition (OBSD) is a new technique which decomposes a signal according to its Oscillatory Behavior, rather than frequency or scale. Due to the low Oscillatory transients of bearing fault-induced signals, the OBSD can be used to effectively extract bearing fault signatures from a blurred signal. However, the quality of the result highly relies on the selection of method-related parameters. Such parameters are often subjectively selected and a systematic approach has not been reported in the literature. As such, this paper proposes a systematic approach to automatic selection of OBSD parameters for reliable extraction of bearing fault signatures. The OBSD utilizes the idea of Morphological Component Analysis (MCA) that optimally projects the original signal to low Oscillatory wavelets and high Oscillatory wavelets established via the Tunable Q-factor Wavelet Transform (TQWT). In this paper, the effects of the selection of each parameter on the performance of the OBSD for bearing fault signature extraction are investigated. It is found that some method-related parameters can be fixed at certain values due to the nature of bearing fault-induced impulses. To adaptively tune the remaining parameters, index-guided parameter selection algorithms are proposed. A Convergence Index (CI) is proposed and a CI-guided self-tuning algorithm is developed to tune the convergence-related parameters, namely, penalty factor and number of iterations. Furthermore, a Smoothness Index (SI) is employed to measure the effectiveness of the extracted low Oscillatory component (i.e. bearing fault signature). It is shown that a minimum SI implies an optimal result with respect to the adjustment of relevant parameters. Thus, two SI-guided automatic parameter selection algorithms are also developed to specify two other parameters, i.e., Q-factor of high-Oscillatory wavelets and regularization parameter. Based on the index-guided parameter selection algorithms, an automatic parameter selection method is then proposed for the application of OBSD to bearing fault signature extraction. The proposed method is then validated with simulated signals and experimental data.
-
intelligent bearing fault signature extraction via iterative Oscillatory Behavior based signal decomposition iobsd
Expert Systems With Applications, 2016Co-Authors: Ming LiangAbstract:A method based on Oscillatory Behaviors is proposed for bearing fault detection.The IOBSD is developed for handling signals with multiple interferences.The strategies of Q-factor determination and tuning for TQWT are exploited.The proposed method can remove in-band interferences and noise.The proposed method requires neither prior signal knowledge nor prefiltering. A typical vibration signal from a defective bearing is composed of fault-induced transients (i.e., fault signature), resonance, multiple vibration interferences and background noise. Extracting the fault-induced transients from such signals is the primary goal for bearing fault diagnosis. This paper proposes an intelligent Oscillatory Behavior based signal decomposition (OBSD) method for this purpose. The OBSD technique exploits both the signal separation capability of morphological component analysis (MCA) and the basis creation potential of tunable Q-factor wavelet transform (TQWT). To generate proper bases for each individual signal component, the Q-factor determination and tuning strategies for the TQWT are developed in this study. In the presence of multiple interferences, one-time OBSD may not be sufficient to extract fault feature successfully. As such, an iterative OBSD (IOBSD) procedure is proposed. With the proposed method, a vibration signal can be decomposed into three signal components, i.e., low-oscillation component (fault signature presenting non-oscillation), high-oscillation component (interferences manifesting sustained oscillation) and residual (noise), according to their Oscillatory Behaviors. Bearing faults can then be reliably detected. The main features of the proposed method include: (1) it can remove in-band interference and noise that cannot be removed by the widely used frequency-based approaches, as it is frequency-independent in nature, (2) it can extract fault signatures from heavily interference-obscured signals without filtering the signals, and (3) it does not require the prior information of the signals. With these features, the IOBSD method can substantially reduce human involvement and facilitate its implementation in a fault detection expert system, particularly in an environment with various interferences. The IOBSD method has been favorably compared with one of the popular filtering techniques, i.e., SK method. The effectiveness of the proposed method has also been tested by simulation and experiments.
-
intelligent bearing fault signature extraction via iterative Oscillatory Behavior based signal decomposition iobsd
Expert Systems With Applications, 2016Co-Authors: Juanjuan Shi, Ming LiangAbstract:A method based on Oscillatory Behaviors is proposed for bearing fault detection.The IOBSD is developed for handling signals with multiple interferences.The strategies of Q-factor determination and tuning for TQWT are exploited.The proposed method can remove in-band interferences and noise.The proposed method requires neither prior signal knowledge nor prefiltering. A typical vibration signal from a defective bearing is composed of fault-induced transients (i.e., fault signature), resonance, multiple vibration interferences and background noise. Extracting the fault-induced transients from such signals is the primary goal for bearing fault diagnosis. This paper proposes an intelligent Oscillatory Behavior based signal decomposition (OBSD) method for this purpose. The OBSD technique exploits both the signal separation capability of morphological component analysis (MCA) and the basis creation potential of tunable Q-factor wavelet transform (TQWT). To generate proper bases for each individual signal component, the Q-factor determination and tuning strategies for the TQWT are developed in this study. In the presence of multiple interferences, one-time OBSD may not be sufficient to extract fault feature successfully. As such, an iterative OBSD (IOBSD) procedure is proposed. With the proposed method, a vibration signal can be decomposed into three signal components, i.e., low-oscillation component (fault signature presenting non-oscillation), high-oscillation component (interferences manifesting sustained oscillation) and residual (noise), according to their Oscillatory Behaviors. Bearing faults can then be reliably detected. The main features of the proposed method include: (1) it can remove in-band interference and noise that cannot be removed by the widely used frequency-based approaches, as it is frequency-independent in nature, (2) it can extract fault signatures from heavily interference-obscured signals without filtering the signals, and (3) it does not require the prior information of the signals. With these features, the IOBSD method can substantially reduce human involvement and facilitate its implementation in a fault detection expert system, particularly in an environment with various interferences. The IOBSD method has been favorably compared with one of the popular filtering techniques, i.e., SK method. The effectiveness of the proposed method has also been tested by simulation and experiments.
Andrew J Daugulis - One of the best experts on this subject based on the ideXlab platform.
-
the incidence of Oscillatory Behavior in the continuous fermentation of zymomonas mobilis
Biotechnology Progress, 1999Co-Authors: P J Mclellan, Andrew J DaugulisAbstract:The incidence of Oscillatory Behavior in the continuous culture of Zymomonas mobilis has been examined using a combination of experimental investigations and a predictive model. The tendency to Oscillatory Behavior was assessed by perturbing the feed substrate concentration and dilution rate in a continuous fermentation starting from a number of distinct initial conditions. The entire range of qualitative dynamic Behavior was observed: overdamped, underdamped, and sustained Oscillatory responses. The predictive capabilities of a model previously proposed by our research group were confirmed over this range of operation. A key component of this model is the inclusion of a dynamic specific growth rate term which accounts for the inhibition associated with historical ethanol concentration change rate. Parameters and relationships estimated for the model were used to identify key characteristics leading to Oscillatory Behavior. In particular, differences in the sensitivities of ethanol production rate versus specific growth rate to ethanol concentration and its rate of change dictate whether sustained oscillations will occur. Experimental evidence indicates that a change in morphology is associated with Oscillatory Behavior. The change in morphology to a more filamentous form may explain the change in specific growth and product formation characteristics.
-
experimental investigation and modeling of Oscillatory Behavior in the continuous culture of zymomonas mobilis
Biotechnology and Bioengineering, 1997Co-Authors: Andrew J Daugulis, James P MclellanAbstract:The mechanism causing oscillation in continuous ethanol fermentation by Zymomonas mobilis under certain operating conditions has been examined. A new term, “dynamic specific growth rate,” which considers inhibitory culture conditions in the recent past affecting subsequent cell Behavior, is proposed in this article. Based on this concept, a model was formulated to simulate the Oscillatory Behavior in continuous fermentation of Zymomonas mobilis. Forced oscillation fermentation experiments, in which exogenous ethanol was added at a controlled rate to generate Oscillatory Behavior, were performed in order to obtain estimates for the model parameters and to validate the proposed model. In addition, data from a literature example of a sustained oscillation were analyzed by means of the model, and excellent agreement between the model simulation and experimental results was obtained. The lag in the cells' response to a changing environment, i.e., ethanol concentration change rate experienced by the cells, was shown to be the major factor contributing to the Oscillatory Behavior in continuous fermentation of Zymomonas mobilis under certain operating conditions. © 1997 John Wiley & Sons, Inc. Biotechnol Bioeng56: 99–105, 1997.
