Calibration Method Research Articles

B-180 A Component Equation Approach to Resolving Calibration Curve Nonlinearity When Using Stable Isotope-Labeled Internal Standards for Quantifying Amino Acids With Mass Spectrometry

Abstract Background Stable isotope-labeled internal standards (SIL-IS) have been widely used with mass spectrometry to accurately quantify analytes. However, over an extended dynamic range, calibration curves calculated with the relative ratio of analytes to their corresponding SIL-IS are typically nonlinear. This makes accurate estimation of sample concentration difficult, especially at lower concentrations. Highly multiplexed clinical mass spectrometry assays routinely face this challenge. The component equation assumes interaction between an analyte and its SIL-IS causes the nonlinearity. Modeling this resulted in a linear calibration curve and high accuracy across the dynamic range. We compared the component equation with other calibration methods to quantify amino acids. Methods A total of 47 compounds were serially diluted and added with extraction solution containing a SIL-IS mixture to prepare 7 levels of calibrators. Calibrators were chromatographically separated using a Sciex ExionLC system with an Imtakt Intrada Amino Acid column and injected into a Sciex Citrine triple-quadrupole mass spectrometer. Seven different fitting methods were compared for calibration of each amino acid: non-weighted linear, quadratic and cubic models, linear models with 1/X and 1/X2 weighting, Padé[1,1] approximation, and component equation. Results Results for an example amino acid, tyrosine, are shown in the table below. Most models yield high accuracy at high concentrations, however, all models recorded significantly higher bias for the lowest calibrator than the component equation (≥55.7% vs 11.8%). The component equation outperformed all other models for mean bias (≥16.6% vs 5.9%). Similar results were obtained for the complete set of analytes. Conclusions When compared to other popular calibration methods to quantify a panel of amino acids, the component equation generated a linear curve and the greatest accuracy across all concentrations. The application of this simple equation could overcome the limitations of existing weighting and non-linear fitting approaches when using SIL-IS for quantifying analytes with mass spectrometry.

A new calibration method for radon detector in seismic systems

Radon observation is an important measurement item of seismic precursor network observation. The radon detector calibration is a key technical link for ensuring radon observation accuracy. At present, the radon detector calibration in seismic systems in China is faced with a series of bottleneck problems, such as aging and scrap, acquisition difficulties, high supervision costs, and transportation limitations of radon sources. As a result, a large number of radon detectors cannot be accurately calibrated regularly, seriously affecting the accuracy and reliability of radon observation data in China. To solve this problem, a new calibration method for radon detectors was established. The advantage of this method is that the dangerous radioactive substance, i.e., the radon source, can be avoided, but only “standard instruments” and water samples with certain dissolved radon concentrations can be used to realize radon detector calibration. This method avoids the risk of radioactive leakage and solves the current widespread difficulties and bottleneck of radon detector calibration in seismic systems in China. The comparison experiment with the traditional calibration method shows that the error of the calibration coefficient obtained by the new method is less than 5% compared with that by the traditional method, which meets the requirements of seismic observation systems, confirming the reliability of the new method. This new method can completely replace the traditional calibration method of using a radon source in seismic systems.

Research on automated verification method for temperature-related tests of electrical energy meters

Abstract Program of pattern evaluation of fixed electrical energy meters-alternating current and GB/T 17215 series of national standards for the examination of energy meter performance by the impact of temperature change, set up a variety of temperature-related test items. Systematic research is possible to conclude that temperature-related tests can be divided into two categories according to the test procedure: Hold at test temperature for a certain period of time, return to the reference temperature and then measure the relevant parameters; measurement of the relevant parameters immediately after a certain period of time at the test temperature. Relevant parameters include errors at different load points and daily timing error of the internal clock of the energy meter. Data processing is undertaken after the test mainly consists of deriving error shift and mean temperature coefficient. This automated calibration method allows you to freely set the test temperature, test duration, reference temperature, stabilization duration, detection parameters, test points and data processing according to the test requirements. The paper explains in detail the application of the automated calibration method to realize typical temperature dependence, test of time-keeping accuracy of the energy meter with temperature and climatic tests (high temperature test, low temperature test and durability test of accuracy) The method breaks the shackles of the traditional calibration method of fixed test temperature, fixed test points and fixed test duration. It can adapt to the development needs of different levels of pattern evaluation of energy meter and national standards, for the laboratory to realize automated testing to provide the basis for industry standards and product testing commissioned inspection.

Research on the calibration method of winding deformation tester

Abstract The focus of this paper is the calibration method and process for winding deformation tester, encompassing its working principle, metrological characteristics, calibration conditions and measurement methods. The calibration conditions are divided into environmental conditions and measurement standards and other equipments. The measurement methods are divided into indication error of scanning frequency and indication error of amplitude ratio. The key steps in the calibration process are elaborated, including the selection of standard equipments, error analysis, data processing. The method’s feasibility is verified through experiments.

Opportunistic Screening of Bone Fragility Using Computed Tomography.

Opportunistic screening uses existing imaging studies for additional diagnostic insights without imposing further burden on patients. We explore the potential of opportunistic computed tomography (CT) screening for osteoporosis, a condition affecting 500 million people globally and leading to significant health care costs and fragility fractures. Although dual-energy X-ray absorptiometry (DXA) remains the gold standard for diagnosing osteoporosis, > 50% of fractures occur in individuals not screened previously with DXA. With recent advancements in technology, CT has emerged as the most promising tool for opportunistic screening due to its wide use and the ability to provide quantitative measurements of bone attenuation, a surrogate of bone mineral density. This article discusses the technical considerations, calibration methods, and potential benefits of CT for osteoporosis screening. It also explores the role of automation, supervised and unsupervised, in streamlining the diagnostic process, improving accuracy, and potentially developing new biomarkers of bone health. The potential addition of radiomics and genomics is also highlighted, showcasing the synergy between genetic and imaging data for a more comprehensive understanding of osteoporosis pathophysiology and with it possible novel osteoporosis therapies. The future of opportunistic CT screening holds significant promise, with automation and advanced image processing ultimately enhancing patient care, reducing rates of osteoporotic fractures, and improving patient outcomes.

Enhancing accuracy of surgical stylus-tip tracking: A comparative calibration study

Accurate determination of the position of surgical stylus-tip is crucial for informed decision-making in computer-assisted surgery. This study assesses the accuracy of various calibration methods for stylus-tip tracking. A novel template-based calibration method is proposed, offering a practical protocol for assessing surgical stylus-tip accuracy. Relative position and orientation errors are measured using two custom-made phantoms and compared with those from existing techniques. Experimental results shows that our proposed method achieves greater positional accuracy (mean: 1.73 mm; range: 0.53-3.42 mm) compared to the geometry-based method (mean: 3.78 mm; range: 2.52-5.05 mm) and the algebraic-based method (mean: 2.47 mm; range: 1.52-3.52 mm). In terms of orientation accuracy, our method also performs slightly better (mean: 0.95 deg; range: 0-3.41 deg) than the geometry-based method (mean: 1.03 deg; range: 0-3.36 deg) and the algebraic-based method (mean: 1.01 deg; range: 0-3.22 deg). The advantages of our method are highlighted, demonstrating its potential for application in the operating room.

Calibration and Experimental Verification of Finite Element Parameters for Alfalfa Conditioning Model

Conditioning is an important step in harvesting alfalfa hay, as squeezing and bending alfalfa stems can break down the stem fibers and accelerate the drying rate of alfalfa. The quality of alfalfa hay is directly affected by the conditioning effect. The finite element method (FEM) can quantitatively analyze the interaction relationship between alfalfa and conditioning rollers, which is of great significance for improving conditioning effects and optimizing conditioning systems. The accuracy of material engineering parameters directly affects the simulation results. Due to the small diameter and thin stem wall of alfalfa, some of its material parameters are difficult to measure or have low measurement accuracy. Based on this background, this study proposed a method for calibrating the finite element parameters of thin-walled plant stems. By conducting radial tensile, shear, bending, and radial compression tests on alfalfa stems and combining with the constitutive relationship of the material, the range of engineering parameters for the stems was preliminarily obtained. By conducting a Plackett–Burman experiment, the parameters that affect the maximum shearing force of stems were determined, including Poisson’s ratio in the isotropic plane, radial elastic modulus, and the sliding friction coefficient between the alfalfa stem and steel plate. By conducting the steepest ascent experiment and Box–Behnken experiment, the optimal values of Poisson’s ratio, radial elastic modulus, and sliding friction coefficient were obtained to be 0.42, 28.66 MPa, and 0.60, respectively. Finally, the double-shear experiment, radial compression experiment, and conditioning experiment were used to evaluate the accuracy of the parameters. The results showed that the average relative error between the maximum shear and the measured value was 0.88%, and the average relative error between the maximum radial contact force and the measured value was 2.13%. In the conditioning experiment, the load curve showed the same trend as the measured curve, and the simulation results could demonstrate the stress process and failure mode of alfalfa stems. The modeling and calibration method can effectively predict the stress and failure of alfalfa during conditioning.

Methods for online calibration of Q-matrix and item parameters for polytomous responses in cognitive diagnostic computerized adaptive testing.

The ability to rapidly provide examinees with detailed and effective diagnostic information is a critical topic in psychology. Knowing what diagnostic criteria the examinees have met enables the practitioner to seek the solution to help them in a timely manner, and this can be achieved by cognitive diagnostic computerized adaptive testing (CD-CAT). However, the pervasive challenge of replenishing items in the CD-CAT item bank limits its practical application. Online calibration is a means to address item replenishment, but in CD-CAT, most existing online calibration methods that jointly calibrate the Q-matrix and item parameters of the new items are developed only for dichotomous responses and are time-consuming. Notably, previous studies pay no attention to polytomously scored items that are frequently observed in testing, even though they can offer additional evidence for the examinees' diagnosis. To fill this gap, we propose a SCAD-based method (SCAD-EM) to calibrate the Q-matrix and item parameters of the new items with polytomous response data in order to promote the application of CD-CAT in practice. The performance of the SCAD-EM was investigated in two comprehensive simulation studies and compared against the revised single-item estimation method (SIE-BIC). Results indicated that the SCAD-EM produces a higher calibration accuracy for the category-level Q-matrix and is computationally more efficient across all conditions, but it produces a lower calibration accuracy for the item-level Q-matrix. An empirical study further demonstrated the utility of the SCAD-EM and the SIE-BIC methods in calibrating new items with a real dataset. The advantages of the proposed method, its limitations, and possible future research directions are offered at the end.

Research on Calibration device of gas leakage alarm system and uncertainty analysis

Abstract This paper studies the calibration device and method of the gas leakage alarm system, and evaluates the uncertainty of the measurement results. Firstly, it analyzes the important components, parameters, and working principles of the gas leakage alarm system. Then, it designs a set of inhalation-type gas leakage alarm system calibration devices to test the indication error, repeatability, and response time of the alarm system, and evaluates the uncertainty of the calibration device. The study concludes that the relative expanded measurement uncertainty of the device calibrating the alarm system is 2.6%, which meets the accuracy requirements of national standards for calibration devices. The main factors affecting the measurement results are the resolution and repeatability of the alarm system being tested. By improving the performance of the alarm system sensor, the measurement results of the alarm system can be made closer to the true value, reducing misjudgment and improving the accuracy of the system. And during calibration, the measurement capability of the device can be enhanced by using higher grade gas standard substances.

Towards a new model-independent calibration of Gamma-Ray Bursts

Current data on baryon acoustic oscillations and Supernovae of Type Ia (SNIa) cover up to z∼2.5. These low-redshift observations play a very important role in the determination of cosmological parameters and have been widely used to constrain the ΛCDM and models beyond the standard, such as the ones with open curvature. To extend this investigation to higher redshifts, Gamma-Ray Bursts (GRBs) stand out as one of the most promising observables. In spite of being transient, they are extremely energetic and can be used to probe the universe up to z∼9.4. They exhibit characteristics that suggest they are potentially standardizable candles and this allows their use to extend the distance ladder beyond SNIa. The use of GRB correlations is still a challenge due to the spread in their intrinsic properties. One of the correlations that can be employed for the standardization is the fundamental plane relation between the peak prompt luminosity, the rest-frame end time of the plateau phase, and its corresponding luminosity, also known as the three-dimensional Dainotti correlation. In this work, we propose an innovative method of calibration of the Dainotti relation which is independent of cosmology. We employ state-of-the-art data on Cosmic Chronometers (CCH) at z≲2 and use the Gaussian Processes Bayesian reconstruction tool. To match the CCH redshift range, we select 20 long GRBs in the range 0.553≤z≤1.96 from the Platinum sample, which consists of well-defined GRB plateau properties that obey the fundamental plane relation. To ensure the generality of our method, we verify that the choice of priors on the parameters of the Dainotti relation and the modelling of CCH uncertainties and covariance have negligible impact on our results. Moreover, we consider the case in which the redshift evolution of the physical features of the plane is accounted for. We find that the use of CCH allows us to identify a sub-sample of GRBs that adhere even more closely to the fundamental plane relation, with an intrinsic scatter of σint=0.20−0.05+0.03 obtained in this analysis when evolutionary effects are considered. In an epoch in which we strive to reduce uncertainties on the variables of the GRB correlations in order to tighten constraints on cosmological parameters, we have found a novel model-independent approach to pinpoint a sub-sample that can thus represent a valuable set of standardizable candles. This allows us to extend the cosmic distance ladder presenting a new catalogue of calibrated luminosity distances up to z=5.

Improved Calibration Method of the Photonic Current Sensor for Monitoring HVDC Networks

Improved Calibration Method of the Photonic Current Sensor for Monitoring HVDC Networks

TCT-195 Enhancing Quantitative Coronary Analysis Accuracy: A Novel Calibration Method Incorporating Table Height and Projection Angle Factors

TCT-195 Enhancing Quantitative Coronary Analysis Accuracy: A Novel Calibration Method Incorporating Table Height and Projection Angle Factors

Full-field three-dimensional system calibration for composite surfaces reconstruction

The accurate calibration of composite surface measurement systems for specular and diffused surface is of great importance in a number of industrial applications. This paper addresses the challenges in calibrating composite surface reconstruction by proposing a comprehensive full-field calibration method. The principal innovation is the construction of a comprehensive reference phase and the pixel-by-pixel calibration of system parameters within the same coordinate system. The details are as follows: (1) construct a complete reference phase for the composite surfaces through external parameter constraints phase fusion and interpolation; (2) calibrate the mapping relationship coefficients, compensate the accuracy degradation of the partial reflection. Experimental results validate the accuracy of the full-field calibration data, demonstrating the effectiveness and feasibility.

Robust calibration of surround-view camera systems with Planar-Eccentric Constraint: A novel Apriltag approach

This research tackles calibrating surround view camera systems for automated driving, where traditional methods require extensive manual measurements and precise conditions. We introduce a novel automatic calibration method that ensures portability and accuracy using only custom-designed calibration boards placed in the cameras’ common view. To address visual interference from extraneous objects, we design a unique board with AprilTag 2D codes, offering clear advantages over traditional checkerboards. Additionally, we’ve developed an Adaptive Angle Projection to counteract fisheye lens distortions. We also introduce a hierarchical pose optimization strategy that transitions from local to global, incorporating a “Planar-Eccentric constraint” to leverage the calibration board’s geometric positioning. Our method achieved 4.01 cm measurement error, with 0.075°angle error and 1.18 cm translation error. Our method’s efficacy and robustness were confirmed through extensive testing on an experimental vehicle and simulation dataset, proving its superiority in achieving precise calibration and measurement with minimal manual input.

Target control point position calibration based on coordinate measuring machine and global bundling optimization algorithm.

The target-based coordinate measurement system is primarily composed of a target, a camera, and a computer, relying on image processing to achieve coordinate measurement. It finds extensive applications in spatial positioning and precision measurement, such as industrial manufacturing, robot navigation, and shipbuilding. The accuracy of the target-based coordinate measurement system is highly dependent on the calibration precision of control point positions. A new method based on the calibration of control point positions using a traditional coordinate measuring machine is proposed in this paper. This method does not require the individual calculation of spatial positions for each control point; instead, it utilizes a global bundle algorithm to obtain the positions of all the control points within the field of view, thereby simplifying the calibration process. The simulation results indicate that the key factor influencing the accuracy of visual calibration is the motion range of the measured target within the field of view, and it is positively correlated with calibration accuracy. For a large-sized target, a method of stitching control points within a near-sighted distance is proposed, which achieves higher accuracy compared to full-field calibration without requiring all the control points to be present within the field of view. Experiments demonstrate that using the proposed calibration method, the standard deviations of measurement accuracy of the target-based coordinate measurement system in the x, y, and z directions are 0.01, 0.01, and 0.08mm, respectively.

An error compensation method for on-machine measuring blade with industrial robot

To achieve the seamless integration of precision grinding blade with timely measured data, an on-machine measurement system employing industrial robot is developed. The limitation to its widespread application lies in the accuracy of measurement, prompting the proposal of an error compensation method to address the measurement error within the implemented blade on-machine measurement system. To address the pre-travel error in the measuring device of the on-machine measurement system, an analysis of the factors influencing the pre-travel error of the contact probe is conducted. Subsequently, pre-travel error data is gathered utilizing the experimental calibration method involving a standard ball, and a prediction model employing the bilinear interpolation algorithm is established to facilitate error compensation. Employing pre-travel error compensation for the analysis of the operating body error in the on-machine measurement system, a spherical center distance constraint error model is derived through closed-loop kinematic calibration of the six-degrees-of-freedom industrial robot. Kinematic parameter error identification is conducted using a hybrid algorithm combining the L-M algorithm and the adaptive factor double-variable DE algorithm. This approach diminishes the spherical center distance measurement error, reducing it from 0.081 mm to 0.016 mm. Subsequently, experiment is conducted to measure blade machining allowances using an on-machine robotic measurement system, comparing the obtained data with measurement from a blue light scanner and a coordinate measuring machine (CMM). The results reveal average absolute deviations of 0.020 mm, 0.015 mm, and 0.016 mm in the three blade cross sections for the on-machine robotic measurement system and the blue light scanner, respectively. Correspondingly, the average absolute deviations for the on-machine robotic measurement system and the CMM in the three blade sections are 0.028 mm, 0.029 mm, and 0.029 mm. Moreover, the on-machine measurement system demonstrates commendable measurement repeatability, with a standard deviation of 0.003 mm.

Parameter-Free Data Reduction for Short-Time Hypersonic Heat Flux Measurements

High-speed flows associated with hypersonics require significant, diverse, and successful ground-test campaigns before engaging in a flight test program. The present investigation focuses on demonstrating a new data reduction pathway for estimating the source heat flux using an elegant, though fragile, thin-film temperature gauge. The rapid response time of such sensors makes them well-suited for shock tunnel experiments. In such experiments, contaminated flow, composed of diaphragm debris, can often damage the sensing element. For the moment, the existence of an ideal coating (or even a hardened sensing element) is presumed that preserves the sensor’s survivability and accuracy over several test runs. A dynamic, physics-based data reduction methodology is proposed that accounts for the protective coating and that is applicable to millisecond testing times. This paper addresses three critical issues for acquiring the best estimate of the source heat flux. These issues include a) the formation of a baseline data reduction view that accounts for thin coatings; b) the development of a dynamic calibration method that removes the need for specifying thermophysical or geometrical properties; and c) the introduction of a time-scaling that allows for calibration to be performed in alternative and convenient time frames. This last point demonstrates the concept of the dimensionless time map and its novel consequences. The procedure is demonstrated on a reduced formulation, illustrating the merit of the concepts.

Data Transforms in Chemometric Calibrations Part 4B: Continuation of the Discussion of Data Transforms for Continuous-Wavelength Spectra as well as Discrete-Wavelength Models

This column is the continuation of our previous column (1) that describes and explains some algorithms and data transforms beyond those most commonly used. We present and discuss algorithms that are rarely, if ever, seen or used in practice, despite that they have been proposed and described in the literature. These comprise algorithms used in conjunction with continuous spectra, as well as those used with discrete spectra. In our previous column, we examined calibration methods based on the use of classical least squares, Karl Norris’ derivative-ratio technique, and David Haaland’s post-calibration augmented-components technology.

Research on on-orbit relative radiometric calibration method based on solar diffuse reflector hyperspectral camera

Abstract In the original image data obtained by optical remote sensing satellite sensors, there is stripe noise caused by inconsistent probe response, which will seriously affect the application effect and accuracy of the image. The importance of relative radiometric calibration is that it can eliminate the stripe noise in the image, thus improving the quality and clarity of the image. In this paper, a relative radiometric calibration method based on the data of a solar diffuse reflector downloaded from the satellite is proposed. The relative radiation calibration coefficient is calculated by using the least square method by obtaining the calibration image of the on-board diffuse reflector covering all the detectors. To verify the method proposed in this paper, the on-board relative radiometric calibration experiment is carried out by using the on-orbit hyperspectral camera of a terrestrial ecological carbon monitoring satellite, and the calibration effect of the calibration coefficient on the original image is tested, and the relative radiometric calibration accuracy is quantitatively analyzed. The experimental results show that the calibration coefficient can effectively eliminate the band noise of the original hyperspectral image. From the quantitative evaluation, the signal-to-noise ratio index of the corrected hyperspectral image is greater than 200, and the generalized noise index is better than 3%, which achieves a good calibration effect and meets the requirements of high-quality remote sensing image application. It provides a reliable guarantee for quantitative remote sensing applications during the satellite’s on-orbit operation.

A flexible camera calibration method for pose vision measurement system of roadheader

Cameras used for visual measurement in underground roadway construction sites are difficult to calibrate. Therefore, this study proposed an on-site camera calibration method that does not require manual intervention. First, the virtual point and line features on the plane target are constructed using pole-polar constraints. Second, a homography model based on point-and-line features is established. Finally, a combined objective function based on the dynamic weight coefficient is proposed to optimise the calibration results further. Relevant simulations and experiments showed that the maximum internal parameter error obtained using the proposed method was 0.463 %, and the maximum position estimation error of the roadheader was 30 mm. In addition, the results show that this method is superior to other methods in terms of calibration accuracy and robustness, solving the difficulty of camera calibration in underground roadway construction sites and guaranteeing high-precision pose vision measurement.