The Experts below are selected from a list of 42876 Experts worldwide ranked by ideXlab platform
Andrew Ball - One of the best experts on this subject based on the ideXlab platform.
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autocorrelation Ensemble Average of larger amplitude impact transients for the fault diagnosis of rolling element bearings
Energies, 2019Co-Authors: Andrew BallAbstract:Rolling element bearings are one of the critical elements in rotating machinery of energy engineering systems. A defective roller of bearing moves in and out of the load zone during each revolution of the cage. Larger amplitude impact transients (LAITs) are produced when the defective roller passes the load zone centre and the defective area strikes the inner or outer races. A series of LAIT segments with higher signal to noise ratio are separated from a continuous vibration signal according to the bearing geometry and kinematics. In order to eliminate the phase errors between different LAIT segments that can arise from rotational speed fluctuations and roller slippages, unbiased autocorrelation is introduced to align the phases of LAIT segments. The unbiased autocorrelation signals make the Ensemble averaging more accurate, and hence, archive enhanced diagnostic signatures, which are denoted as LAIT-AEAs for brevity. The diagnostic method based on LAIT separation and autocorrelation Ensemble Average (AEA) is evaluated with the datasets captured from real bearings of two different experiment benches. The validation results of the LAIT-AEAs are compared with the squared envelope spectrums (SESs) yielded based on two state-of-the-art techniques of Fast Kurtogram and Autogram.
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early detection of rolling bearing faults using an auto correlated envelope Ensemble Average
International Conference on Automation and Computing, 2017Co-Authors: Xiaoli Tang, Andrew BallAbstract:Bearings have been widely used with the broad application of rotating machines. Hence, in order to increase the efficiency, reliability and safety of rotating machinery, condition monitoring of bearings is significant during the operation. However, due to the influence of high background noise and components slippage, incipient faults are difficult to detect. With the continuous research on the bearing system, the modulation effects have been well known and the demodulation based on optimal frequency bands is approved as a promising method in condition monitoring. For the purpose of enhancing the performance of demodulation analysis, a robust method, Ensemble Average autocorrelation based stochastic subspace identification (SSI), is introduced to determine the optimal frequency bands. Furthermore, considering that both the Average and autocorrelation functions can reduce noise, auto-correlated envelope Ensemble Average (AEEA) is proposed to suppress noise and highlight the localised fault signature. In order to examine the performance of this method, the slippage of bearing signals is modelled as a Markov process in the simulation study. Based on the analysis results of simulated bearing fault signals with white noise and slippage and an experimental signal from a planetary gearbox test bench, the proposed method is robust to determine the optimal frequency bands, suppress noise and extract the fault characteristics.
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fault detection of rolling bearings using an Ensemble Average autocorrelation based stochastic subspace identification
24th International Congress on Sound and Vibration, 2017Co-Authors: Li Haiyang, Dong Zhen, Ibrahim Rehab, Andrew BallAbstract:Rolling bearings are the crucial parts of rotating machines. The detection and diagnoses of their defects at early stages are significant for ensuring safety and efficient operations. Usually, the vibration feature associated with bearing faults are submerged by the heavy background noise and nonstationary impacts. To enhance detection performance, this pa-per proposes a novel method developed based on Ensemble Average autocorrelation and stochastic subspace identification (SSI) techniques. It establishes the theoretical basis of the method based on the general characteristics of bearing vibration signals under faults. Then it examines the robustness of techniques under different level noise, which leads to an optimal selection of centre frequencies that have high signal to noise ratio and thereby high accuracy of envelope analysis for fault diagnosis. Both simulation and experimental results show that the proposed method is able to extract bearing fault signatures at very low signal to noise ratio (<-20dB) and consequently produces accurate detection.
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a robust method to detect faults of rolling bearings using Ensemble Average autocorrelation based stochastic subspace identification
30th International Congress & Exhibition on Condition Monitoring and Diagnostic Engineering Management, 2017Co-Authors: Pieter Van Vuuren, Xiaoli Tang, Andrew BallAbstract:Envelope analysis plays an important role in the field of bearing faults detection. Since the development of this technique, the determination of optimal bands has been a prior challenge. Fast Kurtogram (FK) is an outstanding approach to select an optimal band for further analysis; however, fast Kurtogram is not robust enough to withstand the influence of white noise and large aperiodic impulses. Hence, a more robust method is introduced to extract the narrow bands for envelope analysis, which is Ensemble Average autocorrelation based stochastic subspace identification (SSI). The detector performs well in denoising and highlighting the periodic impulses owing to the outstanding characteristics of autocorrelation function and stochastic subspace identification. Considering the results of simulation study and experimental evaluation, it can be concluded that the proposed method is more effective and robust to detect bearing faults than fast Kurtogram.
Nongjian Tao - One of the best experts on this subject based on the ideXlab platform.
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transition from stochastic events to deterministic Ensemble Average in electron transfer reactions revealed by single molecule conductance measurement
Proceedings of the National Academy of Sciences of the United States of America, 2019Co-Authors: Hui Wang, Zixiao Wang, Yanjun Qiao, Jens Ulstrup, Hong Yuan Chen, Gang Zhou, Nongjian TaoAbstract:Electron transfer reactions can now be followed at the single-molecule level, but the connection between the microscopic and macroscopic data remains to be understood. By monitoring the conductance of a single molecule, we show that the individual electron transfer reaction events are stochastic and manifested as large conductance fluctuations. The fluctuation probability follows first-order kinetics with potential dependent rate constants described by the Butler–Volmer relation. Ensemble averaging of many individual reaction events leads to a deterministic dependence of the conductance on the external electrochemical potential that follows the Nernst equation. This study discloses a systematic transition from stochastic kinetics of individual reaction events to deterministic thermodynamics of Ensemble Averages and provides insights into electron transfer processes of small systems, consisting of a single molecule or a small number of molecules.
Rachid Deriche - One of the best experts on this subject based on the ideXlab platform.
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Ensemble Average propagator estimation of axon diameter in diffusion mri implications and limitations
International Symposium on Biomedical Imaging, 2016Co-Authors: Mauro Zucchelli, Rachid Deriche, Rutger Fick, Gloria MenegazAbstract:Diffusion Magnetic Resonance Imaging (dMRI) has been used to infer the axon diameter of the tissues using biophysical models of diffusion. In recent years, a new method was proposed for estimating axon diameter directly from the Ensemble Average propagator (EAP), and in particular from one of its derived index, the return to the axis probability (RTAP). In this work we study the effect that different acquisition parameters have on the estimation of the axon diameter with three different EAP models: diffusion tensor imaging (DTI), 3D-SHORE, and MAPMRI. We quantify the effect that moving from the long diffusion time condition has on the diameter estimation by simulating the diffusion signal inside impermeable cylinders. Results on in-vivo data shows that EAP models estimation of axon diameter is heavily influenced by extra-axonal water and incoherence of fiber orientation, which hides the intra-axonal signal.
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A Temperature Phantom to Probe the Ensemble Average Propagator Asymmetry: an In-Silico Study
2015Co-Authors: Marco Pizzolato, Demian Wassermann, Tanguy Duval, Jennifer S. W. Campbell, Timothé Boutelier, Julien Cohen-adad, Rachid DericheAbstract:The detection and quantification of asymmetry in the Ensemble Average Propagator (EAP) obtained from the Diffusion-Weighted (DW) signal has been shown only for theoretical models. EAP asymmetry appears for instance when diffusion occurs within fibers with particular geometries. However the quan-tification of EAP asymmetry corresponding to such geometries in controlled experimental conditions is limited by the difficulty of designing fiber geometries on a micrometer scale. To overcome this limitation we propose to adopt an alternative paradigm to induce asymmetry in the EAP. We apply a temperature gradient to a spinal cord tract to induce a corresponding diffusivity profile that alters locally the diffusion process to be asymmetric. We simulate the EAP and the corresponding complex DW signal in such a scenario. We quantify EAP asymmetry and investigate its relationship with the applied experimental conditions and with the acquisition parameters of a Pulsed Gradient Spin-Echo sequence. Results show that EAP asymmetry is sensible to the applied temperature-induced diffusivity gradient and that its quantification is influenced by the selected acquisition parameters.
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AxTract: microstructure-driven tractography based on the Ensemble Average propagator
2015Co-Authors: Gabriel Girard, Rachid Deriche, Maxime Descoteaux, Rutger Fick, Demian WassermannAbstract:We propose a novel method to simultaneously trace brain white matter (WM) fascicles and estimate WM microstructure character- istics. Recent advancements in diffusion-weighted imaging (DWI) allow multi-shell acquisitions with b-values of up to 10,000 s/mm2 in human subjects, enabling the measurement of the Ensemble Average propagator (EAP) at distances as short as 10 μm. Coupled with continuous models of the full 3D DWI signal and the EAP such as Mean Apparent Propagator (MAP) MRI, these acquisition schemes provide unparalleled means to probe the WM tissue in vivo. Presently, there are two complementary limitations in tractography and microstructure measurement techniques. Tractography techniques are based on models of the DWI signal geometry without taking specific hypotheses of the WM structure. This hinders the tracing of fascicles through certain WM areas with complex organisation such as branching, crossing, merging, and bottlenecks that are indistinguishable using the orientation-only part of the DWI signal. Microstructure measuring techniques, such as AxCaliber, require the direc- tion of the axons within the probed tissue before the acquisition as well as the tissue to be highly organized. Our contributions are twofold. First, we extend the theoretical DWI models proposed by Callaghan et al. to characterize the distribution of axonal calibers within the probed tissue taking advantage of the MAP-MRI model. Second, we develop a simultaneous tractography and axonal caliber distribution algorithm based on the hypothesis that axonal caliber distribution varies smoothly along a WM fascicle. To validate our model we test it on in-silico phantoms and on the HCP dataset.
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Exploiting the Phase in Diffusion MRI for Microstructure Recovery: Towards Axonal Tortuosity via Asymmetric Diffusion Processes
2015Co-Authors: Marco Pizzolato, Demian Wassermann, Timothé Boutelier, Rachid DericheAbstract:We derive the Ensemble Average Propagator (EAP) for the case of straight axons (White Matter tissue elongation) and for undulated axons having different tortuosity rates (WM tissue compression). We show that under the hypothesis of having both the Magnitude and Phase of the dMRI signal we can quantify the asymmetry of the EAP which is related to the rate of tortuosity variation in the compressed axon.
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Tractography via the Ensemble Average Propagator in diffusion MRI
2012Co-Authors: Sylvain Merlet, Anne-charlotte Philippe, Rachid Deriche, Maxime DescoteauxAbstract:It's well known that in diffusion MRI (dMRI), fibre crossing is an important problem for most existing diffusion tensor imaging (DTI) based tractography algorithms. To overcome these limitations, High Angular Resolution Diffusion Imaging (HARDI) based tractography has been proposed with a particular emphasis on the the Orientation Distribution Function (ODF). In this paper, we advocate the use of the Ensemble Average Propagator (EAP) instead of the ODF for tractography in dMRI and propose an original and efficient EAP-based tractography algorithm that outperforms the classical ODF-based tractography, in particular, in the regions that contain complex fibre crossing configurations. Various experimental results including synthetic, phantom and real data illustrate the potential of the approach and clearly show that our method is especially efficient to handle regions where fiber bundles are crossing, and still well handle other fiber bundle configurations such as U-shape and kissing fibers.
Ali Ercan - One of the best experts on this subject based on the ideXlab platform.
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fractional Ensemble Average governing equations of transport by time space nonstationary stochastic fractional advective velocity and fractional dispersion ii numerical investigation
Journal of Hydrologic Engineering, 2015Co-Authors: Sangdan Kim, M. L. Kavvas, Ali ErcanAbstract:AbstractIn this paper, the second in a series of two, the theory developed in the companion paper is applied to transport by stationary and nonstationary stochastic advective flow fields. A numerical solution method is presented for the resulting fractional Ensemble Average transport equation (fEATE), which describes the evolution of the Ensemble Average contaminant concentration (EACC). The derived fEATE is evaluated for three different forms: (1) purely advective form of fEATE, (2) moment form of the fractional Ensemble Average advection-dispersion equation (fEAADE) form of fEATE, and (3) cumulant form of the fractional Ensemble Average advection-dispersion equation (fEAADE) form of fEATE. The Monte Carlo analysis of the fractional governing equation is then performed in a stochastic flow field, generated by a fractional Brownian motion for the stationary and nonstationary stochastic advection, in order to provide a benchmark for the results obtained from the fEATEs. When compared to the Monte Carlo sim...
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Fractional Ensemble Average Governing Equations of Transport by Time-Space Nonstationary Stochastic Fractional Advective Velocity and Fractional Dispersion. I: Theory
Journal of Hydrologic Engineering, 2015Co-Authors: M. L. Kavvas, Sangdan Kim, Ali ErcanAbstract:AbstractIn this study, starting from a time-space nonstationary general random walk formulation, the pure advection and advection-dispersion forms of the fractional Ensemble Average governing equations of solute transport by time-space nonstationary stochastic flow fields were developed. In the case of the purely advective fractional Ensemble Average equation of transport, the advection coefficient is a fractional Ensemble Average advective flow velocity in fractional time and space that is dependent on both space and time. As such, in this case, the time-space nonstationarity of the stochastic advective flow velocity is directly reflected in terms of its mean behavior in the fractional Ensemble Average transport equation. In fact, the derived purely advective form represents the Lagrangian derivation of the Ensemble Average mass conservation equation for solute transport in fractional time-space. In the case of the fractional Ensemble Average advection-dispersion transport equation, the moment and cumula...
Robert J Silbey - One of the best experts on this subject based on the ideXlab platform.
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theory of single molecule spectroscopy beyond the Ensemble Average
Annual Review of Physical Chemistry, 2004Co-Authors: Eli Barkai, Younjoon Jung, Robert J SilbeyAbstract:Single-molecule spectroscopy (SMS) is a powerful experimental technique used to investigate a wide range of physical, chemical, and biophysical phenomena. The merit of SMS is that it does not require Ensemble averaging, which is found in standard spectroscopic techniques. Thus SMS yields insight into complex fluctuation phenomena that cannot be observed using standard Ensemble techniques. We investigate theoretical aspects of SMS, emphasizing (a) dynamical fluctuations (e.g., spectral diffusion, photon-counting statistics, antibunching, quantum jumps, triplet blinking, and nonergodic blinking) and (b) single-molecule fluctuations in disordered systems, specifically distribution of line shapes of single molecules in low-temperature glasses. Special emphasis is given to single-molecule systems that reveal surprising connections to Levy statistics (i.e., blinking of quantum dots and single molecules in glasses). We compare theory with experiment and mention open problems. Our work demonstrates that the theory of SMS is a complementary field of research for describing optical spectroscopy in the condensed phase.