Common Calibration Procedures Research Articles

Pitfalls in hydrologic model calibration in a data scarce environment with a strong seasonality: experience from the Adyar catchment, India

Process-based hydrologic models can provide necessary information for water resources management. However, the reliability of hydrological models depends on the availability of appropriate input data and proper model calibration. In this study, we demonstrate that common calibration procedures that assume stationarity of hydrological processes can lead to unsatisfactory model performance in areas that experience a strong seasonal climate. Moreover, we develop a more robust calibration procedure for the Soil and Water Assessment Tool (SWAT) in the Adyar catchment of Chennai, India. Calibration was carried out based on seasonal decomposition and by successively shifting the calibration period. Daily and monthly streamflow records were used to investigate how these different calibration procedures influence model parameterization. Results show that SWAT model performance improved when calibrated after separating the streamflow into wet and dry seasons. The wet season calibration increased the Kling Gupta Efficiency coefficient and Nash–Sutcliffe Efficiency coefficient values from 0.56 to 0.68 and 0.19 to 0.51, respectively, compared to calibration based on wet and dry seasons together. In addition, when calibration time periods were shifted, resultant sets of model parameter values and performance metrics differed. Calibration based on the 2004–2009 period resulted in an overestimation of streamflow by 8.2%, whereas the overestimation was 12.1%, 18.3%, and 20.0% for the 2004–2010, 2004–2011, and 2004–2012 periods, respectively. This study underlines that both the availability of observed streamflow data and the way these data are applied to calibration have a strong impact on model parameterization and performance.

Consistent frequency-matching calibration procedure for electromechanical shunt absorbers

Electromagnetic and piezoelectric shunt damping can be represented by an equivalent mechanical vibration absorber with a spring, dashpot, and inerter in series. A common calibration procedure for multiple electromechanical shunt absorbers is obtained by this equivalence, including a correction for the influence from residual vibration modes by additional modal terms, whose coefficients are consistently identified by frequency matching for the system with rigid absorber dashpots. The accuracy and robustness of the calibration procedure are verified numerically for an unsupported truss structure with rigid body modes.

An IMM-UKF Aided SINS/USBL Calibration Solution for Underwater Vehicles

To improve the efficiency of the calibration process and enhance the adaptability of the calibration method, an interacting multiple model and unscented Kalman filter (IMM-UKF) aided strapdown inertial navigation system (SINS)/Ultra-Short Base Line (USBL) calibration solution is proposed for the common calibration procedure, where only one transponder is employed without pre-locating. Firstly, construct the SINS/USBL calibration mechanism, where the transponder's position, level-arm and misalignment angle are estimated simultaneously utilizing the slant range, inclination angles of USBL and depth information from depthometer. Second, to mitigate the decreasing calibration accuracy caused by the single filtering parameter under the complex underwater environment, an IMM-UKF algorithm is presented to support the proposed calibration mechanism. Simulation results indicate that the proposed mechanism earns faster convergence rate and better calibration results than other solutions. Besides, the proposed solution can maintain its robustness when the observation quality changes.

Robust regression-based estimation of isocenter offset with subpixel precision in tomographic image reconstruction.

Tomographic image reconstruction requires precise geometric measurements and calibration for the scanning system to yield optimal images. The isocenter offset is a very important geometric parameter that directly governs the spatial resolution of reconstructed images. Due to system imperfections such as mechanical misalignment, an accurate isocenter offset is difficult to achieve. Common calibration procedures used during isocenter offset tuning, such as pin scan, are not able to reach precision of subpixel level and are also inevitably hampered by system imperfections. We propose a purely data-driven method based on Fourier shift theorem to indirectly, yet precisely, estimate the isocenter offset at the subpixel level. The solution is obtained by applying a generalized M-estimator, a robust regression algorithm, to an arbitrary sinogram of axial scanning geometry. Numerical experiments are conducted on both simulated phantom data and actual data using a tungsten wire. Simulation results reveal that the proposed method achieves great accuracy on estimating and tuning the isocenter offset, which, in turn, significantly improves the quality of final images, particularly in spatial resolution.

Grating monochromator wavelength calibration using an echelle grating wavelength meter.

Monochromators are a common utility for the spectral calibration of spectrometers. To guarantee traceability of characterization measurements to SI-standards, monochromators used as secondary standards must be properly calibrated. Common calibration procedures are based on the measurement of spectral lines emitted by gas-discharge lamps or lasers. Due to the nature of these light sources, the sampling of calibration points cannot be freely chosen. In this paper we present an approach where an echelle grating wavelength meter (WM) is used to traceably calibrate the emitted center wavelength of a monochromator at almost any sampling interval. In addition, it is possible to calibrate the monochromator outside the sensitive spectral range of the WM used. It is demonstrated how a WM is calibrated and then how it is used to calibrate the monochromator of DLR's Calibration Home Base (CHB) for imaging spectrometers at DLR Oberpfaffenhofen, Germany. The same approach is also used for the monochromator, which is intended for the laboratory calibration of the German hyperspectral satellite mission EnMAP.

Reversible Gap Derivatives and Their Integration.

Higher-order gap derivatives are sometimes avoided as a preprocessing method for multivariate calibration despite their numerous advantages. One reason that they are avoided is the difficulty in interpreting the complex processed spectra and the regression vectors that arise from common calibration procedures like principal components regression or partial least squares regression. In this report we offer a method of calculating gap derivatives of any order with the aim of retrieving zero-order spectral information via numerical integration. This method is also extended to the integration of the accompanying regression vectors to aid in the interpretation of multivariate calibration models.

NIMROD: The Near and InterMediate Range Order Diffractometer of the ISIS second target station

NIMROD is the Near and InterMediate Range Order Diffractometer of the ISIS second target station. Its design is optimized for structural studies of disordered materials and liquids on a continuous length scale that extends from the atomic, upward of 30 nm, while maintaining subatomic distance resolution. This capability is achieved by matching a low and wider angle array of high efficiency neutron scintillation detectors to the broad band-pass radiation delivered by a hybrid liquid water and liquid hydrogen neutron moderator assembly. The capabilities of the instrument bridge the gap between conventional small angle neutron scattering and wide angle diffraction through the use of a common calibration procedure for the entire length scale. This allows the instrument to obtain information on nanoscale systems and processes that are quantitatively linked to the local atomic and molecular order of the materials under investigation.

Designing a maximum precision interferometric particle imaging set-up

In this article, a comprehensive uncertainty analysis will be given of a popular 2D particle measuring technique called Interferometric Laser Imaging for Droplet Sizing (ILIDS) for measuring droplets and bubbles. This includes the first estimates on the influence of droplet non-sphericity. Next to this, the uncertainty on the frequency determination and the calibration procedures were also investigated. To this end, the two most common calibration procedures were experimentally compared. This showed that it often dominates the total uncertainty. Design guidelines are then derived concerning observation angle, out-focus disk size and calibration procedure which could lead to a combined uncertainty below 1.5% for droplets and 2% for bubbles.

The Influence of Various Hematology Analyzers on Component Platelet Counts

Hematology analyzers designed to count platelets in samples of whole blood are used to enumerate the total number of platelets in components prepared for transfusion. This report addresses the issue of variability in platelet counts obtained with different models of hematology analyzers. The influence of a common calibration procedure, involving one level of porcine platelets, on the extent of variability was also evaluated. Identical sets of samples of simulated and apheresis-derived human platelets were counted by multiple laboratories in 3 separate studies. In the first 2 exercises, 7 samples of both porcine platelets and modified goat erythrocytes with targeted platelets counts from 0.2 to 4.0 x 10(12)/L were counted without prior dilution. In both exercises, the samples were counted multiple times after routine calibration using instructions provided by the manufacturers of the various hematology analyzers used. In the second exercise, the samples were recounted after the hematology analyzers were recalibrated with a common calibrant consisting of porcine platelets at a targeted concentration of 0.5 x 10(12)/L. In the first and second exercises, 20 and 18 hematology analyzers were used, respectively. In the third exercise, 6 samples prepared from a single unit of apheresis platelets with targeted counts from 0.2 to 1.64 x 10(12)/L were shipped by an overnight courier and counted in triplicate on the day of arrival. Eleven hematology analyzers were used. The influence of recalibration was evaluated statistically by using the 95% prediction interval for the mean of a future set of observations. The platelet counts measured with a specific type of hematology analyzer provided the data to calculate the 95% prediction interval. With routine calibration, a wide variability in platelet counts was observed with all levels of both simulated and apheresis-derived human platelets. For example, with porcine platelets at a targeted level of 0.4 x 10 (12)/L, the platelet counts ranged from 0.31 to 0.47 x 10(12)/L. Recalibration reduced the extent of variability observed with all levels of simulated and apheresis-derived human platelets by increasing the observed platelet counts determined with a subset of hematology analyzers that produced platelet counts in the lower portion of the range. With recalibration, the mean platelet counts obtained with most hematology analyzers, especially with samples having targeted platelet levels no greater than 1.0 x 10(12)/L, were within or near the 95% prediction interval determined with the instruments that provided the highest platelet counts with routine calibration. With recalibration, the reproducibility of the platelet counts was considered to be good for all hematology analyzers with all levels of simulated and apheresis-derived human platelets for most of the instruments. The coefficient of variance did not exceed 6%, with most of the values ranging from 1% to 3%. This study therefore found that the platelet counts of platelet concentrates can be markedly influenced by the type of hematology analyzer used. A common calibration procedure designed specifically for the range of platelet counts in platelet products may be beneficial considering that many different hematology analyzers are being used to count platelets.

Comparison of the training of neural networks for quantitative x-ray fluorescence spectrometry by a genetic algorithm and backward error propagation

Neural networks are shown to be useful as empirical mathematical models in the calculation of quantitative analytical results, giving sufficient accuracy to compete successfully with various common calibration procedures. The performance of these neural-network models for calibration data from x-ray fluorescence spectrometry (XRF) was evaluated for two training methods, i.e., backward error propagation (BEP) and a genetic algorithm (GA). For a small training set (13 members) of data from Fe/Ni/Cr samples taken from the literature, the BEP-trained models compared favourably with other literature methods. The GA-trained models performed poorly for these samples. The two models performed equally well when trained on a larger data set (30 members) consisting of XRF data for thin Fe/Ni layers on a substrate, for which both the composition and the thickness were determined. The predictive power of both models for samples outside the range of the training set was unsatisfactory.

Variability in commercial electromyographic biofeedback devices

The purpose of this study was to evaluate the functional characteristics of a sample of commercial electromyographic feedback devices for the purpose of determining variability between instruments. Seventeen physical and functional characteristics (such as input impedance, filter bandwidth, and sensitivity) were evaluated on a sample of 11 instruments. Wide variability was found in several important functional characteristics. Input impedance, for example, was found to vary from 13K to more than 1 megohm and filter bandwidths ranged from 55 Hz to 2,600 Hz. Such variability makes the comparison of data from studies using different instruments quite difficult; it also suggests the need to develop equipment standards and common calibration procedures.