Precise Calibration Research Articles

A survey of offline precision calibration of industrial robots

Abstract. As the need for precision and efficiency grows in industrial manufacturing, the accuracy of industrial robots assumes paramount importance. Nevertheless, factors, such as mechanical structures and assembly processes often introduce errors, compromising robots' positioning and repeatability accuracy. Consequently, precise calibration and compensation of these errors are paramount for optimizing robots performance. A thorough analysis of error sources and the establishment of error models in industrial robots are conducted in the present study, with special attention paid to offline calibration methods. This paper reviews the robot error model building methods and offline accuracy calibration techniques, summarizes the technical difficulties of the calibration task, and proposes the future development direction for the difficulties such as the complexity of error modeling, the difficulty of non-motor calibration calculation, and the traditional stiffness compensation that does not meet the needs of the robot's operation process. The importance of this research lies in its potential to improve the accuracy and reliability of industrial robots, thus contributing to the development of industrial automation.

Development and validation of a tumor size-stratified prognostic nomogram for patients with gastric signet ring cell carcinoma.

Gastric signet ring cell carcinoma (GSRC) is a rare malignancy without a commonly acknowledged prognostic assessment and treatment system. This study aimed to determine the optimal cut-off value of tumor size (TS), and construct a prognostic nomogram in combination with other independent prognostic factors (PFs) to predict 3year and 5year overall survival (OS) in GSRC patients. From the Surveillance, Epidemiology, and End Results (SEER) database, this study collected 4744 patients diagnosed with GSRC. These patients were randomized into a training cohort (n = 2320,) and a validation cohort (n = 1142). A restricted cubic spline (RCS) was used to determine the cut-off value for TS, and univariate and multivariate Cox regression analyses were performed in the training cohort to identified significant predictors. A prognostic nomogram was constructed to predict OS at 3 and 5years. Concordance index (C index), receiver operating characteristics curve (ROC curve), area under curve (AUC), and calibration curve were used to test the predictive accuracy of the model. A non-linear relationship was observed between TS and the risk of OS in GSRC, with TS thresholds at 4.4cm and 9.6cm. Survival was significantly lower in GSRC patients with TS > 4.4cm. Age, marriage, chemotherapy, surgery, TS, SEER stage, regional lymph node status, and total number were independent predictors of OS. The C index in the training cohort was 0.748, and the AUC values for both 3- and 5-year OS were higher than 0.80. Similar results were observed in the validation cohort. In addition, the calibration curves showed good agreement between the predicted 3year and 5year OS and the actual OS. TS is a key prognostic factor for patients with GSRC, and patients with a TS of 4.4-9.6cm and > 9.6cm may have a poorer prognosis than those with a TS of < 4.4cm. The TS-stratified nomogram we constructed and validated has favorable accuracy and calibration precision, and may be helpful in predicting the survival rate of patients.

The “Lochkovian-Pragian Event” re-assessed: New data from the low latitude shelf of peri-Gondwana

In the late Lochkovian a regression is documented in several areas of the world, followed by a transgression in the early Pragian. Connected with the eustatic variation, a minor extinction event occurred (“Lochkovian-Pragian Event”), affecting several fossil groups, a strong reduction of carbonate production and sedimentary facies changes. The Carnic Alps are a key area for studying this event, because lower Devonian rocks are widely exposed, representing diverse sedimentary environments from shallow water to relatively deep shelf. Fourteen sections were measured along the Carnic Alps across the Lochkovian-Pragian boundary. In the shallower part of the basin, both the Polinik and the Seekopf formations span the boundary, but evident erosional surfaces are observable in the field at the Lochkovian-Pragian boundary. Above the unconformity, at places the so-called megaclast horizon is present in the Seekopf Formation. In intermediate settings the Rauchkofel Fm. Is unconfomably followed by the Kellerwand Fm., and different parts of the upper Lochkovian and lower Pragian are missing in the various sections. In the deeper parts of the basin the transition from the La Valute Fm. To the Findenig Fm. Is slightly diachronous from the latest Lochkovian to the earliest Pragian; however, conodonts and tentaculitids are rare in the marly boundary beds, preventing a precise chronostratigraphic calibration of these levels. At places, evidence of subaerial exposure at the formational boundary is documented. In general, the hiatus seems to be larger in the western part of the Carnic Alps, in correspondence with the shallower parts of the succession, suggesting a sea level drop in the late Lochkovian, followed by a transgression in the Pragian. Data from the Carnic Alps are compared with those of other regions of North Gondwana to demonstrate that the sea-level variation at the Lochkovian-Pragian boundary are of global importance

Quantitative estimation of optical properties in bilayer media within the subdiffusive regime using tilted fiber-optic probe diffuse reflectance spectroscopy, part 2: probe design, realization, and experimental validation.

Tissues like skin have a layered structure where each layer's optical properties vary significantly. However, traditional diffuse reflectance spectroscopy assumes a homogeneous medium, often leading to estimations that reflects the properties of neither layer. There's a clear need for probes that can precisely measure the optical properties of layered tissues. This paper aims to design a diffuse reflectance probe capable of accurately estimating the optical properties of bilayer tissues in the subdiffusive regime. Using Monte Carlo simulations, we evaluated key geometric factors-fiber placement, tilt angle, diameter, and numerical aperture-on optical property estimation, following the methodology in Part I. A robust design is proposed that balances accurate intrinsic optical property (IOP) calculations with practical experimental constraints. The designed probe, featuring eight illumination and eight detection fibers with varying spacings and tilt angles. The estimation error of the IOP calculation for bilayer phantoms is less than 20% for top layers with thicknesses between 0.2 and 1.0mm. Building on the approach from Part I and using a precise calibration, the probe effectively quantified and distinguished the IOPs of bilayer samples, particularly those relevant to early skin pathology detection and characterization.

A VIPA spectrograph with ultra-high spectral resolution, ultra-high wavelength calibration accuracy and wide spectral range

Abstract Spectrographs with ultra-high spectral resolution, ultra-high wavelength calibration accuracy, and wide spectral range hold immense potential in broad scientific frontiers, such as precise spectral measurement, femtosecond pulse shaping, and spectral beam combining, etc. In this paper, we have constructed a virtually imaged phased array (VIPA) based spectrograph, leveraging a laser frequency comb for precise wavelength calibration. The calibration methods specifically for the broadband VIPA spectrograph are presented. The spectrograph achieves a resolution exceeding 650,000, a wavelength calibration accuracy better than 0.05 pm, and a remarkable bandwidth of over 110 nm. Spectral measurements are conducted with the spectrograph, and the results validate the performance.&amp;#xD;

Utilizing the multifrequency resonances of the electron spins in diamond nitrogen-vacancy centers under strong radio frequency driving for quantum sensing

Multifrequency resonances in the pulsed-optically detected magnetic resonance (ODMR) spectra of electron spins in ensemble nitrogen-vacancy (NV) centers in diamonds are investigated under strong radio frequency (RF) driving at a MHz frequency range and weak microwave driving at a GHz frequency range in a bias static magnetic field for quantum sensing applications. First, we demonstrate that the coherent destruction of tunneling, which leads to the disappearance of the main resonance peaks, can be utilized for precise calibration of the RF amplitude. Next, we clarify the condition for enhancing the sensitivity of a DC magnetic field under strong RF driving at the RF frequency that matches the split frequency due to the hyperfine interaction between 15N nuclear spins and the NV electron spins. Our findings indicate that strong RF driving increases the sensitivity of the DC magnetic field by enhancing the ODMR contrast and reducing the linewidth. The above results contribute to certifying the quantitative accuracy of RF imaging and enhancing the sensitivity of the DC magnetic field imaging using ensemble NV centers in diamonds.

Precise Calibration of Projectile-Borne MEMS Gyroscopes Based on the EWMA-DD Method

Precise Calibration of Projectile-Borne MEMS Gyroscopes Based on the EWMA-DD Method

Ultrasonic Array-Based Multi-Source Fusion Indoor Positioning Technology

Underground mining involves numerous risks, such as collapses, gas leaks, and explosions, posing significant threats to worker safety. In this work, we develop an indoor localization system that uses Bluetooth for coarse positioning and ultrasonic arrays for precision calibration. This system is particularly useful for automated mining operations in underground environments where satellite positioning signals are unavailable. The indoor localization system consists of ultrasonic receiver arrays and an improved multi-transmitter-multi-receiver algorithm, enabling accurate localization within the mining environment. Geometric Dilution of Precision (GDOP) analysis is incorporated to optimize the network layout, and an inertial navigation module is integrated to track the posture of moving objects, enabling precise trajectory determination over large areas, such as coal mines. In the experiment, three traditional methods were compared, and the proposed tracking approach demonstrated a positioning accuracy within 10 cm, reducing error by 20% compared to conventional techniques. This high-precision indoor localization method proves beneficial for underground mining applications.

Accurate Technique for the Calibration of High-Voltage Capacitance and Dissipation Factor Bridges up to 1 kHz

This paper presents a comprehensive methodology for the precise calibration of high-voltage capacitance and dissipation factor (DF) bridges. The technique involves meticulous adjustments using a digital high-precision phase and ratio-measuring system to determine correction factors for DF and capacitance measurements. Unlike other methods that are limited to a narrow range, this approach allows calibration across the entire operational working spectrum of any bridge. While the method has been developed up to 1 kHz, its adaptability for future requirements is facilitated by the developed software. This method has been carried out by calibrating a highly accurate bridge for a capacitor ratio of up to 100, with DFs ranging from −0.01 to 0.01 and currents ranging from 0.1 mA to 1 A. Linear correction factors are established, with their accuracies being rigorously quantified. This methodology achieves expanded uncertainties as low as 3.5 µF/F (3.5 ppm) for capacitance and 2.2 × 10−⁶ for DFs, significantly enhancing measurement reliability across diverse high-voltage capacitor applications.

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.

B-115 Software Data Processing and Review LC-MS/MS Workflow Improvements for Clinical Research

Abstract Background In the field of quantitative LC-MS/MS, the need for efficient, accurate and user-friendly data review software is paramount, with the data generated in the clinical laboratory meeting local guidelines, as well as rigorous method performance characteristics defined by the FDA Bioanalytical Method Validation and CLSI C62-Ed2 guidelines. The quantitative LC-MS/MS workflow is dependent on interfacing to LMS/LIMS for sample traceability, batch analysis using matrix-matched external calibrators and quality controls for quantification and acceptance, and stable-isotope labeled internal standards to compensate for sample extraction, recovery, matrix effects and analytical variability. The demands on the laboratory to run multiplexed analyte panels and analyze a greater number of samples produces large amounts of analytical data which must still go through batch and quality review before release from the laboratory to the clinicians. The Waters Quan Review Software significantly reduces the burdensome aspects of batch quality control by introducing a series of innovative features. These include improvements in workflow, a modernized interface, and the ability to flag exceptions based on acceptance criteria. Methods Samples for three multiplexed LC-MS/MS panels with previously defined analytical method performance characteristics were acquired using Waters IVD Systems controlled by MassLynx software. The data was processed, quantified, and reviewed using both the existing TargetLynx XS IVD Application Manager and the new Quan Review Software. The three quantitative LC-MS/MS methods were the analysis of four immunosuppressants drugs in whole blood, a twelve steroid panel in plasma and a urine dilute and shoot method for a drugs of abuse panel containing greater than 80 analytes. Each method used matrix matched calibrators and QCs for quantification and batch control with performance characteristics including calibration linearity, carryover, precision and accuracy. Results The analytical performance data generated using the new MS Quan data review software met the same performance criteria as the TargetLynx XS data. For immunosuppressants, the % difference of the mean repeatability and total precision (%CV) for the individual analyte QCs processed using both software was within ±1.3% and ±4.4% respectively. The mean % bias of External Quality Assurance Samples (n=40) for each immunosuppressant processed using both software was within ±7.9%. The modernized, task-oriented accelerated workflows and focused review by exception reduced review time by up to 50%. Conclusions The new Quan Review Software generated results equivalent to the existing TargetLynx XS Application Manager. The software’s enhanced workflow capabilities streamlined the review process in a new user-friendly interface which reduced the training burden enabling scientists to generate high-quality data quickly and easily. The exception focused review functionality allowed tailored rule sets which reduced the time spent reviewing data by up to 50%. Whilst the batch-level review and task-oriented workflow improved batch acceptance and simplified the review of complicated datasets into easy tasks. By integrating these features, Data Review software offers a comprehensive solution that not only improves the efficiency and accuracy of batch quality control but also contributes to the overall reliability and integrity of quantitative LC-MS/MS analysis. For Research Use Only. Not for Use in Diagnostic Procedures.

Elastography-based AI model can predict axillary status after neoadjuvant chemotherapy in breast cancer with nodal involvement: A prospective, multicenter, diagnostic study

Objective: To develop a model for accurate prediction of axillary lymph node (LN) status after neoadjuvant chemotherapy (NAC) in breast cancer patients with nodal involvement. Methods: Between October 2018 and February 2024, 671 breast cancer patients with biopsy-proven LN metastasis who received NAC followed by axillary LN dissection were enrolled in this prospective, multicenter study. Preoperative ultrasound (US) images, including B-mode ultrasound (BUS) and shear wave elastography (SWE), were obtained. The included patients were randomly divided at a ratio of 8:2 into a training set and an independent test set, with five-fold cross-validation applied to training set. We first identified clinicopathological characteristics and conventional US features significantly associated with the axillary LN response and developed corresponding prediction models. We then constructed deep learning radiomics (DLR) models based on BUS and SWE data. Models performances were compared, and a combination model was developed using significant clinicopathological data and interpreted US features with the SWE-based DLR model. Discrimination, calibration and clinical utility of this model were analyzed using receiver operating characteristic curve, calibration curve and decision curve, respectively. Results: Axillary pathologic complete response (pCR) was achieved in 52.41% of patients. In the test cohort, the clinicopathologic model had an accuracy of 71.30%, while radiologists’ diagnoses ranged from 64.26% to 71.11%, indicating limited to moderate predictive ability for the axillary response to NAC. The SWE-based DLR model, with an accuracy of 80.81%, significantly outperformed the BUS-based DLR model, which scored 59.57%. The combination DLR model boasted an accuracy of 88.70% and a false-negative rate of 8.82%. It demonstrated strong discriminatory ability (AUC, 0.95), precise calibration (p value obtained by Hosmer–Lemeshow goodness-of-fit test, 0.68), and practical clinical utility (probability threshold, 2.5-97.5%). Conclusions: The combination SWE-based DLR model can predict the axillary status after NAC in patients with node-positive breast cancer, and thus, may inform clinical decision-making to help avoid unnecessary axillary LN dissection.

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.

Rapid and precise calibration of soil microparameters for high-fidelity discrete element models in vehicle mobility simulation

In the realm of numerical simulations concerning vehicle mobility, the establishment of a high-fidelity soil discrete element model often necessitates substantial parameter adjustments to align with the mechanical responses of actual soil. In pursuit of a rapid and precise calibration of the microparameters of the soil model, this paper describes an approach rooted in machine learning surrogate models. This method calibrates the corresponding discrete element microparameters based on the macroscopic Mohr–Coulomb parameters derived from actual soil direct shear tests. The distinct contribution lies in the creation of a dataset that bridges the soil microparameters and macroparameters through simulated direct shear tests, which serves as training data for machine learning algorithms. Additionally, an adaptive particle swarm optimization neural network algorithm is proposed to represent the nonlinear relationships among parameters within the dataset, thus achieving intelligent calibration. To verify the reliability of the proposed soil calibration model in the context of vehicle mobility simulations, a co-simulation is conducted using a vehicle multibody dynamics simulation model and the calibrated soil model, with validation conducted across multiple criteria.

Seismic response of deep soft soil sites with varying shear wave velocities

The variations in seismic response between deep soft soil sites with different shear wave velocities were not fully understood. This study focuses on the seismic response of deep soft soil sites in the lower reaches of the Yangtze River, China. A nonlinear dynamic finite element model was developed for two representative deep soft soil sites with borehole profiles and the shear wave velocity tested by the single borehole method. Two nonlinear cyclic constitutive models are used and thus compared through the site seismic response. To accurately calibrate the nonlinear cyclic model parameters, resonant column tests were conducted on 21 soil samples collected from the two boreholes. The results show that the peak ground acceleration (PGA) under low-frequency (Liuan) input motion was higher for soft soil sites compared to that under medium- and high-frequency (Kobe and Nahanni) input motions. The PGA amplification factor for deep soft soil sites under different input motions can be approximated by an exponential function. The peak ground acceleration tends to be lower as the equivalent shear wave velocity (Vse) decreases. The shapes of the spectral acceleration were similar for the two sites, despite a substantial difference in the Vse between them. Additionally, a crossover point was observed in the spectral acceleration for the two sites. The period corresponding to this crossover point increased with increasing intensity of input motions, indicating that the sites became softer with higher intensity and thus generally exhibited a longer characteristic period of the spectral acceleration. This paper also highlights the significance of selecting nonlinear constitutive models and the precise calibration of model parameters in the seismic response analysis of deep soft soil sites, providing a scientific basis for future similar site analyses.

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.

Finite Element Model Calibration with Surrogate Model-Based Bayesian Updating: A Case Study of Motor FEM Model

This paper introduces an advanced methodology for the calibration of Finite Element Models (FEM) utilizing a surrogate model-based Bayesian updating framework. The approach is exemplified through a case study on motor design, where precise FEM calibration is essential for predicting and optimizing motor performance. Traditional calibration techniques are often computationally expensive due to the iterative nature of the simulation process. To mitigate this, the proposed method integrates surrogate models to approximate FEM simulations, significantly reducing the computational burden without sacrificing accuracy. Bayesian updating is then employed to iteratively refine the surrogate model by incorporating new data, thereby enhancing prediction accuracy. This dual approach not only accelerates the calibration process but also ensures a high level of precision, making it highly suitable for complex engineering applications requiring both efficiency and reliability. The case study underscores the effectiveness of this methodology, demonstrating its potential to streamline the design process in motor development and other FEM-dependent engineering fields. The findings suggest that the surrogate model-based Bayesian updating approach achieves robust calibration with significantly fewer simulations, thereby optimizing both time and computational resources.

Extrinsic parameters optimization for fringe projection system based on standard components

Fringe projection profilometry (FPP) is a wildly used three-dimension reconstruction method, where the reconstruction accuracy is closely related to the calibration precision. However, various sources of error in the calibration process can result in inaccurate calibration results. In particular, the calibration results of extrinsic parameters are more likely to deviate from the true values, which in turn leads to low-frequency errors in the reconstruction results. In order to obtain the extrinsic parameters closer to the true values, a simple but effective method is proposed in this paper. The proposed method utilizes the standard plane and the dumbbell bat, which are commonly used in measurements, to optimize the extrinsic parameters. First, the standard plane and dumbbell bat are reconstructed using the initial calibration results to transfer the errors in the extrinsic parameters to the plane fitting residuals, as well as to the fitting residuals for the radius and the center distance of dumbbell bat. The residuals and errors are then minimized using nonlinear optimization, resulting in the more accurate extrinsic parameters. Experimental results demonstrate that the proposed method can effectively compensate the calibration error of the extrinsic parameters. The root mean square (RMS) error of planar reconstruction is reduced from 0.0291 mm to 0.0106 mm, which is reduced by about 63.6 %. The RMS error of spherical reconstruction is reduced from 0.0358 mm to 0.0166 mm, which is about 53.6 %. The measurement accuracy of the FPP system is further improved.

Calibration Methods for Large-Scale and High-Precision Globalization of Local Point Cloud Data Based on iGPS.

The point cloud is one of the measurement results of local measurement and is widely used because of its high measurement accuracy, high data density, and low environmental impact. However, since point cloud data from a single measurement are generally small in spatial extent, it is necessary to accurately globalize the local point cloud to measure large components. In this paper, the method of using an iGPS (indoor Global Positioning System) as an external measurement device to realize high-accuracy globalization of local point cloud data is proposed. Two calibration models are also discussed for different application scenarios. Verification experiments prove that the average calibration errors of these two calibration models are 0.12 mm and 0.17 mm, respectively. The proposed method can maintain calibration precision in a large spatial range (about 10 m × 10 m × 5 m), which is of high value for engineering applications.

Middle to late Miocene cooling and drying in the northern Tibetan Plateau based on evidence from plant-insect interactions

The Qaidam Basin in the northern Tibetan Plateau is currently arid, but may have had a semi-humid to semi-arid climate in Miocene times, as suggested by pollen and isotopic data; however, the lack of macroscopic fossils hinders more precise paleoclimatic calibration. In this paper, we report fossil leaves with insect damage from a late Miocene layer (HT-5) in the Huaitoutala section dated ∼11.4 Ma, and compare them with records from a middle Miocene layer (HT-1) dated ∼12.7 Ma. Results show that damage diversity dropped from 36 types in HT-1 to 24 types in HT-5, suggesting a fall in mean annual temperature. Damage frequency decreased from 70 % in HT-1 to 32 % in HT-5, pointing to a drop in the coldest month temperature. Moreover, a slight fall in the diversity of mining damage, from 5 types in HT-1 to 4 types in HT-5, suggests a shift towards a slightly more arid climate from the middle to late Miocene. The flora from HT-5 is composed mainly of Betulaceae, Populus, Ulmus, and shrubs. Based on the distribution of these taxa in modern vegetation, the climate was probably semi-humid, not entirely arid during the late Miocene. These results are corroborated by fossil mammal data from the same section. Therefore, despite a cooling and drying trend from the middle to late Miocene, the climate of the Qaidam Basin was not as extremely arid as today.