The Experts below are selected from a list of 36066 Experts worldwide ranked by ideXlab platform
Adrian C. Michael - One of the best experts on this subject based on the ideXlab platform.
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Online Electrochemical Detectors for Supercritical Fluid Chromatography
Analytical Chemistry, 1995Co-Authors: Shawn F. Dressman, Adrian C. MichaelAbstract:A self-contained electrochemical cell consisting of a working and a quasi-reference electrode coated with a thin film of a conductive polymer was used as a postcolumn detector for supercritical fluid chromatography (SFC-EC). Cyclic voltammetry was used to obtain chromatograms of ferrocene, anthracene, p-benzoquinone, and hydroquinone after they elution from a C 18 packed column with unmodified, acetonitrile-modified, or methanol-modified CO 2 . In unmodified CO 2 , the quantitative performance of the SFC-EC detection of ferrocene was similar to that obtained with a downstream FID with respect to detection limit, response linearity, and peak shape. The Baseline Signal of the EC detector remained flat during density gradient elution while a noticeable drift occurred in the Baseline Signal of the FID. Futhermore, whereas the FID was totally inoperable in a mobile phase containing ∼3% (v/v) of either acetonitrile or methanol, the EC detector functioned well in the modified fluids. Thus, the EC detector is compatible with both unmodified and modified CO 2 mobile phases. A valuable feature of these newly developed SFC detectors is they compatibility with a very large fraction of the rye of separation conditions that are important to SFC
V. John Mathews - One of the best experts on this subject based on the ideXlab platform.
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Data-Driven Temperature Compensation on Lamb Waves
Structural Health Monitoring 2019, 2019Co-Authors: Ahmad B. Zoubi, V. John MathewsAbstract:Active guided-wave-based structural health monitoring techniques have been widely studied for inspecting civil, aerospace and maritime structures. The vast majority of such methods estimate the change in the structures between the times a Baseline measurement and the test measurements were made. Temperature changes between Baseline and test Signal acquisition affects the propagation of the wave in nonlinear and mode-dependent ways. As a result, Baseline comparison methods fail when the test and Baseline Signals are collected at different temperatures. In this paper, we present a novel temperature compensation algorithm that corrects for temperature effects separately for different modes of propagation. Results of experimental data analysis demonstrating that the the method of this paper substantially outperforms the commonly employed Baseline Signal stretch algorithm are also presented.
Jennifer E Michaels - One of the best experts on this subject based on the ideXlab platform.
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efficient temperature compensation strategies for guided wave structural health monitoring
Ultrasonics, 2010Co-Authors: Anthony J Croxford, Paul D. Wilcox, Jochen Moll, Jennifer E MichaelsAbstract:The application of temperature compensation strategies is important when using a guided wave structural health monitoring system. It has been shown by different authors that the influence of changing environmental and operational conditions, especially temperature, limits performance. This paper quantitatively describes two different methods to compensate for the temperature effect, namely optimal Baseline selection (OBS) and Baseline Signal stretch (BSS). The effect of temperature separation between Baseline time-traces in OBS and the parameters used in the BSS method are investigated. A combined strategy that uses both OBS and BSS is considered. Theoretical results are compared, using data from two independent long-term experiments, which use predominantly A0 mode and S0 mode data respectively. These confirm that the performance of OBS and BSS quantitatively agrees with predictions and also demonstrate that the combination of OBS and BSS is a robust practical solution to temperature compensation.
Gexue Ren - One of the best experts on this subject based on the ideXlab platform.
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Baseline Signal reconstruction for temperature compensation in lamb wave based damage detection
Sensors, 2016Co-Authors: Guoqiang Liu, Yingchun Xiao, Hua Zhang, Gexue RenAbstract:Temperature variations have significant effects on propagation of Lamb wave and therefore can severely limit the damage detection for Lamb wave. In order to mitigate the temperature effect, a temperature compensation method based on Baseline Signal reconstruction is developed for Lamb wave-based damage detection. The method is a reconstruction of a Baseline Signal at the temperature of current Signal. In other words, it compensates the Baseline Signal to the temperature of current Signal. The Hilbert transform is used to compensate the phase of Baseline Signal. The Orthogonal matching pursuit (OMP) is used to compensate the amplitude of Baseline Signal. Experiments were conducted on two composite panels to validate the effectiveness of the proposed method. Results show that the proposed method could effectively work for temperature intervals of at least 18 °C with the Baseline Signal temperature as the center, and can be applied to the actual damage detection.
C. Hueglin - One of the best experts on this subject based on the ideXlab platform.
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Robust extraction of Baseline Signal of atmospheric trace species using local regression
Atmospheric Measurement Techniques, 2012Co-Authors: A. F. Ruckstuhl, S. Henne, S. Reimann, M. Steinbacher, B. Buchmann, Martin K. Vollmer, Simon O'doherty, C. HueglinAbstract:Abstract. The identification of atmospheric trace species measurements that are representative of well-mixed background air masses is required for monitoring atmospheric composition change at background sites. We present a statistical method based on robust local regression that is well suited for the selection of background measurements and the estimation of associated Baseline curves. The bootstrap technique is applied to calculate the uncertainty in the resulting Baseline curve. The non-parametric nature of the proposed approach makes it a very flexible data filtering method. Application to carbon monoxide (CO) measured from 1996 to 2009 at the high-alpine site Jungfraujoch (Switzerland, 3580 m a.s.l.), and to measurements of 1,1-difluoroethane (HFC-152a) from Jungfraujoch (2000 to 2009) and Mace Head (Ireland, 1995 to 2009) demonstrates the feasibility and usefulness of the proposed approach. The determined average annual change of CO at Jungfraujoch for the 1996 to 2009 period as estimated from filtered annual mean CO concentrations is −2.2 ± 1.1 ppb yr−1. For comparison, the linear trend of unfiltered CO measurements at Jungfraujoch for this time period is −2.9 ± 1.3 ppb yr−1.
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Robust extraction of Baseline Signal of atmospheric trace species using local regression
2010Co-Authors: A. F. Ruckstuhl, S. Henne, S. Reimann, M. Steinbacher, B. Buchmann, C. HueglinAbstract:Abstract. The identification of atmospheric trace species measurements that are representative of well-mixed background air masses is required for monitoring atmospheric composition change at background sites. We present a statistical method based on robust local regression that is well suited for the selection of background measurements and the estimation of associated Baseline curves. The bootstrap technique is applied to calculate the uncertainty in the resulting Baseline curve. The non-parametric nature of the proposed approach makes it more flexible than other commonly used statistical data filtering methods. Application to carbon monoxide (CO) measured from 1996 to 2009 at the high alpine site Jungfraujoch (Switzerland, 3580 m a.s.l.) demonstrates the feasibility and usefulness of the proposed approach. The determined average annual change for the 1996 to 2009 period as estimated from filtered annual mean CO concentrations is −2.1 ± 1.3 ppb/yr. For comparison, the linear trend of unfiltered CO measurements at Jungfraujoch for this time period is −2.9 ± 1.5 ppb/yr.