Calibration Solutions Research Articles

Development of a Modular Virtual Calibration Platform for Power Machinery

The hardware-in-the-loop (HIL)-based virtual calibration technology for power machinery significantly enhances the efficiency and flexibility of electronic controller calibration, reducing dependency on physical experiments and lowering development costs. This paper presents an independently developed modular virtual calibration platform, designed based on the ISO/IEC 42010 architecture approach and the V-Model development process. The platform adopts a modular layered architecture comprising the physical layer, communication layer, model layer, software layer, and application layer. Each layer is independently developed and seamlessly integrated, ensuring excellent scalability and maintainability. Through performance validation conducted under steady-state and transient operating conditions of the diesel/natural gas dual-fuel engine electronic control unit (ECU), experimental results demonstrated that the platform possesses high computational accuracy, rapid response capability, and stable operation across different scenarios. The experiments validated that the platform can effectively replicate the real behavior of the controlled units in a virtual environment, confirming its adaptability and reliability. The platform offers an efficient and reliable solution for power machinery controller calibration.

Comparison of different characterization approaches for monoelemental calibration solutions at two national metrology institutes.

Monoelemental calibration solutions are the most common reference in elemental analysis, linking measurement results to the International System of Units (SI). National Metrology Institutes (NMI) prepare these solutions as certified reference materials (CRM) and determine their elemental mass fraction with high accuracy. Characterization with high accuracy is one of the most critical steps in CRM production. This report compares the approaches taken by the NMIs of Türkiye (TÜBİTAK-UME) and Colombia (INM(CO)) in preparing and characterizing cadmium calibration solutions with a nominal value of 1 g kg-1. Each NMI produced CRMs using an independent batch of cadmium calibration solution and assigned mass fraction values to both their own solutions and those of the other NMIs. TÜBİTAK-UME employed a primary difference method (PDM) to assess the purity of a cadmium metal standard, quantifying all possible impurities using a combination of instrumental analytical techniques. The defined purity standard was used for both the gravimetric preparation of the CRM and the calibration of high-performance inductively coupled plasma optical emission spectrometry (ICP-OES) measurements. On the other hand, INM(CO) used gravimetric titration with EDTA to assay cadmium in the CRM solutions. The EDTA salt was previously characterized by titrimetry. Despite the fundamentally different measurement methods and independent metrological traceability paths to the SI, the measurement results exhibited excellent agreement within the stated uncertainties. This comparative analysis demonstrates the effectiveness of varied characterization approaches and underscores the reliability of the cadmium calibration solutions prepared by TÜBİTAK-UME and INM(CO). This collaborative effort highlights the reliability and adaptability of various measurement techniques in fulfilling rigorous metrological standards for elemental calibration solutions. Furthermore, this approach enhances the robustness of the measurements in the field of elemental analysis and contributes traceability to the SI.

Enhancing pointing accuracy in Risley prisms through error calibration and stochastic parallel gradient descent inverse solution method

Enhancing pointing accuracy in Risley prisms through error calibration and stochastic parallel gradient descent inverse solution method

Atomic absorption and inductively coupled plasma atomic emission determination of iron and manganese in medicinal salt mixtures

Complete extraction of analytes from samples and the homogeneity of analyzed solutions were achieved using ultrasonic treatment (20 minutes). The sensitivity, precision, and accuracy of atomic absorption determination of analytes were improved by using Triton X-100 (4%) and calibration solutions based on iron and manganese acetylacetonates. It was demonstrated that sensitivity increased by 1.7 times for manganese and 1.5 times for iron. The iron and manganese content in medicinal salt mixtures was determined using both atomic absorption and inductively coupled plasma atomic emission methods. The results obtained by these two independent methods were compared, showing that the dispersions are homogeneous and the variation in results is minor, attributed to random error. The accuracy of the atomic absorption results was verified using the standard addition method and by varying the sample weight, confirming that systematic error is negligible. The detection limits established by the atomic absorption method were Cmin=0.009 g/mL for iron (Cmin, lit=0.015 g/mL) and Cmin=0.003 g/mL for manganese (Cmin, lit=0.004 g/mL).

Microseismicity-Based Modelling of Induced Fracture Networks in Unconventional Reservoirs

A single planar hydraulic fracture is typically the primary component used to simulate hydraulic fracturing stimulation in conventional reservoirs. However, in ultra-low-permeability shale reservoirs, a large system of fracture networks must be generated to produce hydrocarbons economically. Therefore, traditional modeling approaches centered on single planar fractures are inadequate for accurately representing the intricate geometry and behavior of fractures in these reservoirs. In previous works, 2D fractal fracture networks (FFNs) have been used to generate sets of hydraulic and natural fractures based on microseismic event (MSE) data. Since microseismic data are retrieved in 3D space, the aforementioned model cannot accurately represent induced fracture properties. The objective of this paper is to study in detail the recently developed 2D FFN model and propose a novel solution by expanding the previous model to accommodate real 3D microseismic data. First, the definitions of the 2D FFN model are described, and associated calibration mechanisms are proposed. Next, the 3D FFN model and its calibration system are demonstrated. While the novel 3D calibration solution utilizes an identical matching concept to the 2D methodology, the residual distances between the nodes and the MSE are calculated in 3D spaces. Finally, a set of real microseismic data are used to calibrate the generation of 3D fractals using the proposed workflow. The interactions between microseismicity and fractured reservoir dynamics are represented through the integration of fractal fracture models and microseismic data. This work contributes to advancing the current understanding of hydraulic fracturing in unconventional reservoirs and provides a valuable framework for improving fracture modeling’s accuracy in reservoir engineering applications.

Phased Array Antenna Calibration Based on Autocorrelation Algorithm.

The problem of calibrating phased array antennas in a noisy environment using an autocorrelation algorithm is investigated and a mathematical model of the autocorrelation calibration method is presented. The proposed calibration system is based on far-field scanning of the phased array antenna in an environment with internal noise and external interference. The proposed method is applied to a phased array antenna and compared with traditional rotating-element electric-field vector methods, which involve identifying the maximum and minimum vector-sum points (REVmax and REVmin, respectively). The proposed calibration system is verified for a phased array antenna at 3 GHz. Experimental verification of the mathematical model of the proposed method demonstrates that the autocorrelation method is more accurate than the rotating-element electric-field vector methods in determining the amplitude and phase shifts. The measured peak gain of the combined beam in the E-plane increased from 7.83 to 8.37 dB and 3.57 to 4.36 dB compared to the REVmax and REVmin methods, respectively, and the phase error improved from 47° to 55.48° and 19.43° to 29.16°, respectively. The proposed method can be considered an effective solution for large-scale phase calibration at both in-field and in-factory levels, even in the presence of external interference.

A novel high-dimensional sensor calibration framework integrating thermodynamic laws in complex HVAC systems

Accurate calibration of sensors is critical for ensuring energy efficient operation of Heating, Ventilation, and Air Conditioning (HVAC) systems in buildings. Due to the high dimensionality of sensor data and the complexity of multiple-fault scenarios, calibrating sensors in large and complex HVAC systems presents significant challenges. To address this issue, this study introduces a novel sensor calibration framework that integrates thermodynamic laws for high-dimensional sensor calibration in complex HVAC systems. The traditional calibration method heavily relies on accurate data, making it difficult to apply in practical engineering projects. The innovative aspect of our method lies in its integration of thermodynamic laws, such as mass balance and energy conservation, with sensor calibration framework. This approach enables the framework to handle high-dimensional sensor measurements effectively without any training data. We compared five optimization algorithms and applied them to a central cooling system in Hong Kong. The results demonstrated that the simulated annealing (SA) is the most robust for solving the calibration problem, even in scenarios with up to 21 faulty sensors, with the calibrated sensor accuracy meeting the standards for conventional chiller plant operations. This novel framework provides a robust and reliable solution for high-dimensional sensor calibration in large and complex HVAC systems, addressing the growing need for precise sensor calibration as the number of installed sensors increases.

Online Calibration for Networked Radar Tracking of UAS

The need for effective tracking mechanisms of small unmanned aircraft systems (sUAS) has become crucial as their use has increased in populated areas. This paper presents a practical tracking solution for sUAS using a network of phased array radars. Achieving optimal system performance while tracking the sUAS requires extrinsic calibration of the individual radar systems to a common frame of reference. We propose a straightforward calibration solution based upon the orthogonal Procrustes formulation that uses radar measurements from ground-mounted radar associated with real-time-kinematic global positioning system (RTK-GPS) data. Two variations of the calibration are provided: a batch processing method, and an online method for real-time adjustments. This paper provides a practical analysis of the advantages and disadvantages associated with both calibration methods. This assessment of the calibration methods, along with an evaluation of the radar network’s sUAS tracking ability, is validated by simulation studies and hardware tests. The hardware experiments especially provide valuable insights into the practical implications of the proposed tracking solution.

Colorimetric Determination of Dissolved Oxygen: Assessment of Methodological Influences on Iodine Spectra, Isosbestic Point, Precision and Accuracy.

The colorimetric method for determining dissolved oxygen concentrations in freshwater and seawater samples essentially relies on measuring the absorbance of released I2 and I3 - in a mixed form. While this approach is relatively quick and convenient, it is susceptible to significant temperature effects during analysis, irrespective of field temperatures. Additionally, the influences of spectrophotometric absorbance wavelengths and iodine concentrations on oxygen concentration determinations are ambiguous. We found that, while iodine concentration and absorbance wavelength impart minor influences, temperature changes during sample analysis alter the fractionation of two major iodine species (I2 and I3 -) and affect their spectra, with the latter effect imparting the greatest influence on oxygen concentrations. An empirical molar extinction coefficient was defined for the mixture (consisting of 96% I3 - and 4% I2), yielding values of 2282, 1115, and 792 M-1 cm-1 at 25 °C at the most commonly used wavelengths of 430, 456, and 466 nm, respectively. Altering the temperature led to variances in absorbance by 0.33%, 0.42%, and 0.51% °C-1 at 430, 456, and 466 nm, respectively. Therefore, for absorbances measured at 456 nm, a room temperature correction can be applied to the empirical molar coefficient by 1115 M-1 cm-1 × [1 + (room temperature - 25 °C) × 0.0042]. Reducing room temperature differences between samples and calibration solutions became the most important factor in maintaining the precision and accuracy of the measurement. With these precautions, a precision of ∼0.2% (coefficient of variation) over the normal surface water oxygen concentration of around 250 μM can be readily achieved at all tested wavelengths. This method offers a linear oxygen concentration range of 0-650 μM.

An accurate measurement method for serum homocysteine measurement by ID-LC/MS/MS and the application of external quality assessment

BackgroundSerum homocysteine (Hcy) measurement accuracy is essential for detecting and diagnosing cardio-cerebrovascular illnesses. Although many different methods have been developed to determine the concentration of Hcy, those different assays showed nonequivalent results. This study aimed to develop an accurate and precise isotope dilution liquid chromatography-tandem mass spectrometry (ID-LC/MS/MS) method for serum homocysteine (Hcy) and assign values for reference materials used in external quality assessment (EQA) programs. MethodsDifferent concentrations of homocysteine calibration solutions were prepared with d4-Hcy as the internal standard. This method employed DTT to reduce protein-bound Hcy, followed by protein precipitation, and gradient elution on a Supelcosil LC-CN column for chromatographic separation, and multiple reaction monitor (MRM) mode with electrospray ionization (ESI) for mass spectrometric detection. After optimized ID-LC/MS/MS parameters, imprecision, trueness, the limit of quantification (LoQ), the limit of detection (LoD), and measurement uncertainty were evaluated to check the methodological performance. The established method was employed in assigning values to EQA samples, which were sent to 63 clinical laboratories in Beijing to measure Hcy. ResultsAt 10.69,15.99, and 37.80 μmol/L levels, the present method demonstrated analytical imprecision of 0.57 %, 0.65 %, and 0.57 %, and recoveries of 99.67 % to 100.21 %, respectively. The bias between the target values of GBW (Guojia Biaozhun Wuzhi) were − 0.79 % to 0.62 %. The LoQ and LoD for Hcy were 0.36 nmol/L and 0.27 nmol/L. The method had an uncertainty (U 95 %) of 1.34 % to 1.48 %. For the three levels of EQA samples, the percentage of laboratories meeting the trueness evaluation criteria (±10 %) was 81.67 %, 83.33 %, and 71.67 % respectively. ConclusionsWith optimal method precision and trueness, the ID-LC/MS/MS method to measure serum Hcy can be used for value assignment of EQA samples, which can provide reliable data for monitoring the accuracy of clinical laboratory for Hcy measurement.

Solvent-Based and Matrix-Matched Calibration Methods on Analysis of Ceftiofur Residues in Milk and Pharmaceutical Samples Using a Novel HPLC Method.

The matrix effect is accepted as one of the critical factors that affect trueness, and it is especially important in the analysis of critical compounds, such as drugs, toxins and pesticides, in complex matrices. Ceftiofur (CEF) is a leading drug used in dairy industry for pulmonary infections. Because milk has a complex matrix, which is rich in fats, proteins and many other compounds, the determination of CEF in milk products deals with issues of trueness. On the other hand, pharmaceuticals also have a complex composition as they contain not only the active pharmaceutical ingredient but also many excipients, such as preservatives and pH modifiers. Due to its frequent use, its residues can be found in meat products or exist as an excreted compound in urine, milk and so on. The aim of this study was to investigate the effect of different calibration methods on quantitative estimation of CEF in milk and pharmaceutical samples. CEF was analysed using a new HPLC method, in which separation was achieved on a C18 bonded fused-core silica particle column by using isocratic elution; the method was optimized by testing different chromatographic conditions and validated according to the ICH Q2(R1) and United States Pharmacopeia guidelines. Interestingly, it was found that CEF signals in milk samples were higher than the ones at the same level prepared in calibration solutions with a ratio of 11.28:1. This finding reveals the necessity of matrix-matched calibration for accurate quantitative determination of CEF in milk samples. Moreover, the milk in the market and the most used pharmaceutical formulations were analysed using the current method.

Mitigating calibration errors from mutual coupling with time-domain filtering of 21 cm cosmological radio observations

Abstract The 21 cm transition from neutral Hydrogen promises to be the best observational probe of the Epoch of Reionisation (EoR). This has led to the construction of low-frequency radio interferometric arrays, such as the Hydrogen Epoch of Reionization Array (HERA), aimed at systematically mapping this emission for the first time. Precision calibration, however, is a requirement in 21 cm radio observations. Due to the spatial compactness of HERA, the array is prone to the effects of mutual coupling, which inevitably lead to non-smooth calibration errors that contaminate the data. When unsmooth gains are used in calibration, intrinsically spectrally-smooth foreground emission begins to contaminate the data in a way that can prohibit a clean detection of the cosmological EoR signal. In this paper, we show that the effects of mutual coupling on calibration quality can be reduced by applying custom time-domain filters to the data prior to calibration. We find that more robust calibration solutions are derived when filtering in this way, which reduces the observed foreground power leakage. Specifically, we find a reduction of foreground power leakage by 2 orders of magnitude at k∥ ≈ 0.5 h Mpc−1.

Robust and efficient calibration method of liquid-crystal spatial light modulator based on the linear combination strategy

Abstract Phase-only spatial light modulators (SLMs) play a vital role in virous fields. However, its modulation accuracy is compromised by the static aberration and the phase response nonlinearity. To enhance the modulation accuracy, this paper presents an innovative full calibration method for SLMs, effectively addressing both static aberration and nonlinear phase responses using only two shots of camera. The main highlight of this paper is the binding of a novel linear combination strategy and a unique kinoform. This binding can eliminate phase distortion between two shots of camera, making our method dramatically robust in correcting phase response nonlinearity. Additionally, benefit from the accurate correction of phase response nonlinearity, the static aberration is accurately compensated by the single-shot spatial carrier phase-shifting technology. In conclusion, the proposed method's strong robustness, precision, and efficiency position it as an ideal solution for SLM calibration.

Measurement method of flexible component pose based on discrete motion actuators

Abstract In order to address the limitations of traditional large discrete motion actuator mechanisms in realizing high-precision inter-axis relationship calibration in manufacturing environments, this paper proposes a new convolutional neural network-based attitude mapping estimation method, component pose using convolutional neural network (CPCNN). The method implicitly encodes the inter-axis relation matrix into the weight parameters of the training neural network, which results in a high degree of integration with existing large discrete motion actuator mechanisms. The CPCNN-based method directly obtains the attitude change of the adjustment cabin by reading the change of each axis of the current motion actuator mechanism in its own coordinate system. This method can overcome the limitations of the experimental process in the traditional calibration methods and improve the accuracy of attitude mapping under the influence of self-weight by selecting better motion parameters through redundant degrees of freedom. The application of this new method will provide an effective solution for the high-precision inter-axis relationship calibration of large discrete motion actuator mechanisms in manufacturing environments, offering new possibilities for improving production efficiency and product quality.

Stereo Bi-Telecentric Phase-Measuring Deflectometry.

Replacing the endocentric lenses in traditional Phase-Measuring Deflectometry (PMD) with bi-telecentric lenses can reduce the number of parameters to be optimized during the calibration process, which can effectively increase both measurement precision and efficiency. Consequently, the low distortion characteristics of bi-telecentric PMD contribute to improved measurement accuracy. However, the calibration of the extrinsic parameters of bi-telecentric lenses requires the help of a micro-positioning stage. Using a micro-positioning stage for the calibration of external parameters can result in an excessively cumbersome and time-consuming calibration process. Thus, this study proposes a holistic and flexible calibration solution for which only one flat mirror in three poses is needed. In order to obtain accurate measurement results, the calibration residuals are utilized to construct the inverse distortion map through bicubic Hermite interpolation in order to obtain accurate anchor positioning result. The calibrated stereo bi-telecentric PMD can achieve 3.5 μm (Peak-to-Valley value) accuracy within 100 mm (Width) × 100 mm (Height) × 200 mm (Depth) domain for various surfaces. This allows the obtaining of reliable measurement results without restricting the placement of the surface under test.

The Thermal Structure and Composition of Jupiter's Great Red Spot From JWST/MIRI

AbstractJupiter's Great Red Spot (GRS) was mapped by the James Webb Space Telescope (JWST)/Mid‐Infrared Instrument (4.9–27.9 m) in July and August 2022. These observations took place alongside a suite of visual and infrared observations from; Hubble, JWST/NIRCam, Very Large Telescope/VISIR and amateur observers which provided both spatial and temporal context across the jovian disc. The stratospheric temperature structure retrieved using the NEMESIS software revealed a series of hot‐spots above the GRS. These could be the consequence of GRS‐induced wave activity. In the troposphere, the temperature structure was used to derive the thermal wind structure of the GRS vortex. These winds were only consistent with the independently determined wind field by JWST/NIRCam at 240 mbar if the altitude of the Hubble‐derived winds were located around 1,200 mbar, considerably deeper than previously assumed. No enhancement in ammonia was found within the GRS but a link between elevated aerosol and phosphine abundances was observed within this region. North‐south asymmetries were observed in the retrieved temperature, ammonia, phosphine and aerosol structure, consistent with the GRS tilting in the north‐south direction. Finally, a small storm was captured north‐west of the GRS that displayed a considerable excess in retrieved phosphine abundance, suggestive of vigorous convection. Despite this, no ammonia ice was detected in this region. The novelty of JWST required us to develop custom‐made software to resolve challenges in calibration of the data. This involved the derivation of the “FLT‐5” wavelength calibration solution that has subsequently been integrated into the standard calibration pipeline.

RLCFormer: Automatic roadside LiDAR-Camera calibration framework with transformer

LiDAR-Camera fusion is pivotal for perceiving and understanding complex traffic environments, particularly valuable in autonomous driving and traffic monitoring. Traditional calibration algorithms, primarily designed for onboard sensors, are inadequate for roadside setups where sensors are positioned higher and more dispersed. To address this challenge, we introduce the RLCFormer, a Transformer-based network specifically tailored for precise calibration of roadside sensors. This method innovatively integrates depth and RGB features, utilizing correlation layers and a Transformer decoder to accurately match features across modalities. Evaluated on the DAIR-V2X-I Roadside 3D detection dataset, the RLCFormer achieves an average translation error of 3.3187 cm and a rotation error of 0.0469°, surpassing existing methods. Our approach significantly enhances scene representation and calibration precision, offering a robust solution for roadside sensor calibration and advancing the state of the art in sensor fusion technology.

Characteristic study and instrument development of COD sensors consisting of LED and PN tube

The use of deuterium-tungsten lamps and spectrometers limits the miniaturization, low power consumption, and in-situ deployment of Chemical Oxygen Demand (COD) instruments. This study introduces COD sensor utilizing LED and PN tube to overcome these disadvantages. However, PN tubes detect light within 250–800 nm and output an electrical signal, causing nonlinear errors(E) between the LED-derived absorbance (ALED) and COD concentration.This study, through model analysis, reveals that the LED’s emission spectrum and the solution’s absorption spectrum significantly impact errors, and this has been validated experimentally. Additionally, during two-point calibration with deionized water and calibration solution, the measurement error is positive when the concentration of the test solution is lower than that of the calibration solution, and negative when it is higher. Thus, we proposed a calibration and compensation method to reduce errors.Moreover, we have developed a compact, low-cost COD sensor with a measurement error of less than 1.6 mg/L.

Portable temperature-controlled permeation device for the generation of formaldehyde gas standard

Formaldehyde is a major indoor air pollutant. Accurate analysis of airborne formaldehyde is essential for effective monitoring and risk assessment. For many formaldehyde analysis techniques, the accuracy of the results depends on the calibration system. Existing formaldehyde calibration methods often face limitations, such as instability over time or limited concentration range. They also lack practicality for on-field calibration either because of bulkiness or because of high gas consumption. To address these challenges, a device using a paraformaldehyde permeation tube within a custom-built, temperature-controlled system was designed and evaluated.The device weighs less than 3 kg and operates using a nitrogen source. Its low gas consumption (30–100 mL min−1) enables the use of a portable gas cylinder of pure nitrogen (<2 kg) as gas supply. Formaldehyde concentrations ranging from 8.3 to 464 µg/m−3 were successfully generated, demonstrating the device’s versatility. A custom-built high-emission permeation tube could generate concentrations from 5 940 to 49 471 µg/m−3 using the same system. Additionally, the emission rate is independent of the flow rate and follows Antoine’s law with respect to temperature, enabling accurate prediction of concentration in various conditions over the evaluated range and beyond. Furthermore, the study confirms the long-term stability (1 year) of the low-emission paraformaldehyde permeation tube, with emission rates remaining mostly within ± 5 % of the average value for each temperature.The temperature-controlled permeation system approach enabled rapid stabilisation of formaldehyde generation at various concentrations and low flow rates, eliminating the need for additional dilution equipment and facilitating on-site instrument calibration at various gas concentrations. This reliable and efficient portable formaldehyde generator offers a valuable solution for field calibration, providing accurate and stable reference gas for diverse analytical needs.

A novel mathematical method to estimate rice phenological parameters across spatial scales for the ORYZA model

While crop models are increasingly applied to large-scale areas, inadequate observation data make it difficult to calibrate the model’s phenological parameters at the regional scale. The present study proposed a simple mathematical method for estimating rice phenological parameters across spatial scales for the ORYZA model. The method establishes the cumulative function of the phenological parameters (CFPP). By fitting the CFPP with the so-called growth curve, the 4 phenological parameters of the ORYZA model were transformed into 3 fitted parameters in the equation of CFPP. Functions between the fitted parameters and several meteorological and field management factors were established. These established functions were substituted back into CFPP to construct a modified CFPP. Due to the inter-translational relationship between CFPP and the original phenological parameters, the values of phenological parameters could be estimated by the modified CFPP based on meteorological and field management factors. The newly proposed mathematical method was applied in the Yangtze River Basin (YRB), China. The results indicated that the multi-station average of the absolute value of relative errors for the rice panicle initiation, flowering, and maturity dates within the YRB were 12.3 %, 10.5 %, and 8.7 %, respectively, which were at most 4.8 % larger than that simulated using parameters calibrated using each station’s phenological data. The phenological parameters estimated by the novel mathematical method had close performance to those calibrated directly based on observed data at most stations in terms of rice phenology simulation. The present study provided a new solution for phenological parameter calibration for crop models when applied in a large-scale area.