Journal articles: 'Measurement error'

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Kroc, Edward. "Generalized measurement error: Intrinsic and incidental measurement error." PLOS ONE 18, no. 6 (June 29, 2023): e0286680. http://dx.doi.org/10.1371/journal.pone.0286680.

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In this paper, we generalize the notion of measurement error on deterministic sample datasets to accommodate sample data that are random-variable-valued. This leads to the formulation of two distinct kinds of measurement error: intrinsic measurement error, and incidental measurement error. Incidental measurement error will be recognized as the traditional kind that arises from a set of deterministic sample measurements, and upon which the traditional measurement error modelling literature is based, while intrinsic measurement error reflects some subjective quality of either the measurement tool or the measurand itself. We define calibrating conditions that generalize common and classical types of measurement error models to this broader measurement domain, and explain how the notion of generalized Berkson error in particular mathematicizes what it means to be an expert assessor or rater for a measurement process. We then explore how classical point estimation, inference, and likelihood theory can be generalized to accommodate sample data composed of generic random-variable-valued measurements.

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Qin, Lihou, Qijing Liu, Maozhen Zhang, and Sajjad Saeed. "Effect of measurement errors on the estimation of tree biomass." Canadian Journal of Forest Research 49, no. 11 (November 2019): 1371–78. http://dx.doi.org/10.1139/cjfr-2019-0034.

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Diameter at breast height (DBH) is commonly used to predict the aboveground biomass (AGB) of forests and to derive biomass models for single trees; however, there is evidence that measurement errors of DBH have not been previously considered. In this study, two types of measurement errors were evaluated: errors in national forest inventory data (NFID) and errors in a calibration data set (CDS). Using Monte Carlo simulations, the uncertainties arising from these two measurement errors were quantified. In addition, the effects of measurement errors on estimates under different error assumptions were analyzed to determine how these two uncertainties change with increasing errors. The results show that CDS measurement error contributes more to the total uncertainty, whereas NFID measurement error has a negligible effect on estimating the biomass of regional forests. The uncertainties of both types of measurement error increased with increasing error assumptions; however, the uncertainties caused by CDS measurement error were noticeably larger than those caused by NFID measurement error. Thus, the greatest potential for reducing uncertainties caused by measurement error lies in increasing the accuracy of DBH measurements in CDS.

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Iskenderzade, E. B., E. D. Suleymanova, and H. S. Veliyev. "THE METHOD OF INDIRECT TWO-PART MEASUREMENTS FOR THE CONTROL OF PRODUCTION INDICATORS." Kontrol'. Diagnostika, no. 295 (January 2023): 30–32. http://dx.doi.org/10.14489/td.2023.01.pp.030-032.

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A method of indirect two-part measurements of production indicators, including two independent measurements, has been developed. An elementary example of such measurements is the measurement of rectangular areas, determination of the specific gravity of the material, etc. According to the proposed method, minimization of the total random error of indirect two-part measurement can be carried out in two cases: 1) if it is known about the equality of the total error in both measurements, but the sum of systematic errors is limited from above, then it is possible to solve the problem of determining systematic errors separately, which minimizes the total random error of a two-part indirect measurement; 2) if it is known about the equality of systematic errors in both measurements, but the sum of systematic errors is limited from above, then it is possible to solve the problem of determining the total errors separately, which minimizes the total random error of an indirect two-part measurement.

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Masse, J., J. M. Bland, J. R. Doyle, and J. M. Doyle. "Measurement error." BMJ 314, no. 7074 (January 11, 1997): 147. http://dx.doi.org/10.1136/bmj.314.7074.147.

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Luchette, Matthew, and Alireza Akhondi-Asl. "Measurement Error." Pediatric Critical Care Medicine 25, no. 3 (March 2024): e140-e148. http://dx.doi.org/10.1097/pcc.0000000000003420.

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Wu, Lei, Xizhe Zang, Guanwen Ding, Chao Wang, Xuehe Zhang, Yubin Liu, and Jie Zhao. "Joint Calibration Method for Robot Measurement Systems." Sensors 23, no. 17 (August 26, 2023): 7447. http://dx.doi.org/10.3390/s23177447.

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Robot measurement systems with a binocular planar structured light camera (3D camera) installed on a robot end-effector are often used to measure workpieces’ shapes and positions. However, the measurement accuracy is jointly influenced by the robot kinematics, camera-to-robot installation, and 3D camera measurement errors. Incomplete calibration of these errors can result in inaccurate measurements. This paper proposes a joint calibration method considering these three error types to achieve overall calibration. In this method, error models of the robot kinematics and camera-to-robot installation are formulated using Lie algebra. Then, a pillow error model is proposed for the 3D camera based on its error distribution and measurement principle. These error models are combined to construct a joint model based on homogeneous transformation. Finally, the calibration problem is transformed into a stepwise optimization problem that minimizes the sum of the relative position error between the calibrator and robot, and analytical solutions for the calibration parameters are derived. Simulation and experiment results demonstrate that the joint calibration method effectively improves the measurement accuracy, reducing the mean positioning error from over 2.5228 mm to 0.2629 mm and the mean distance error from over 0.1488 mm to 0.1232 mm.

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Chesher, Andrew, and Christian Schluter. "Welfare Measurement and Measurement Error." Review of Economic Studies 69, no. 2 (April 2002): 357–78. http://dx.doi.org/10.1111/1467-937x.00209.

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Adamczak, Stanisław, Jacek Świderski, and Urszula Kmiecik-Sołtysiak. "Estimation of the uncertainty of the roundness measurement with a device with rotary spindle." Mechanik 90, no. 10 (October 9, 2017): 912–14. http://dx.doi.org/10.17814/mechanik.2017.10.145.

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The paper presents the estimation of uncertainty of roundness measurement using the Talyrond 73 by analyzing the sources of measurement errors such as measuring noise, signal drift, radial spindle error, repeatability, sensor gain error and uncertainty of measurement standards. The study included the following measurements: roller bearing, glass hemisphere and flick standard.

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Fang, Yiming, Zhaoyao Shi, Yanqiang Sun, and Pan Zhang. "Gear Integrated Error Determination Using the Gaussian Template Convolution-Facet Method." Applied Sciences 14, no. 3 (January 24, 2024): 1004. http://dx.doi.org/10.3390/app14031004.

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A gear integrated error, a combination of individual and composite errors, carries richer information and has long been a key target of classic gear error measurement techniques. However, in the age of intelligent manufacturing, the classic methods for gear integrated error measurement are no longer able to meet the emerging requirements of large-scale gears and real-time online measurement. To address this gap, a novel approach to obtaining the gear integrated error based on GTC−Facet (Gaussian template convolution-Facet) is proposed. This method accurately pinpoints the sub-pixel contour of gears in images, enabling a quick derivation of the gear integrated error curve. From this curve, other individual and composite errors can be analyzed. The gear error information obtained through our method has higher measurement accuracy, achieving a positioning accuracy of 3.6 μm for the gear profile. Moreover, during the measurement process, the measured gear remains unclamped, and the entire measurement process can be completed within 0.35 s, which is much faster than classic methods. Our method meets the demands of online measurements and provides a new avenue for gear error measurement.

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Jacob, Vinodkumar, M. Bhasi, and R. Gopikakumari. "Impact of Human Factors on Measurement Errors." International Journal of Measurement Technologies and Instrumentation Engineering 1, no. 4 (October 2011): 28–44. http://dx.doi.org/10.4018/ijmtie.2011100103.

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Measurement is the act or the result, of a quantitative comparison between a given quantity and a quantity of the same kind chosen as a unit. It is for observing and testing scientific and technological investigations and generally agreed that all measurements contain errors. In a measuring system where both a measuring instrument and a human being taking the measurement using a preset process, the measurement error could be due to the instrument, the process or human error. This study is devoted to understanding the human errors in measurement. Work and human involvement related factors that could affect measurement errors have been identified. An experimental study has been conducted using different subjects where the factors were changed one at a time and the measurements made by them recorded. Errors in measurement were then calculated and the data so obtained was subject to statistical analysis to draw conclusions regarding the influence of different factors on human errors in measurement. The findings are presented in the paper.

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ISKANDAROV, NABI, ELMIN BAGISHOV, and ELCHIN ISGANDARZADA. "EFFECT OF SURFACE SENSOR AND EXTERNAL REFERENCE NODE ON PROCESS TEMPERATURE MEASUREMENT ACCURACY." Computational Nanotechnology 9, no. 1 (March 28, 2022): 145–53. http://dx.doi.org/10.33693/2313-223x-2022-9-1-145-153.

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As we know, one of the most important and important issues in the implementation of technological processes is the implementation of accurate and correct temperature measurements. During the research, attention was paid to the measurement errors in temperature measurements of technological processes using thermocouples and methods of minimizing those errors. In addition, errors in thermocouple temperature measurements were briefly discussed, and for temperatures limited to a certain range, the T-type thermocouple achieved several times less error than the allowable error specified in the normative documents. It is known that when describing thermocouples in the technical literature, first of all, industrial devices with high temperature coefficient and medium class accuracy are considered. Also, as we know, in domestic applications, the temperature difference between the measurement and the reference node varies mainly within the minimum threshold range. Therefore, if the main source of error is the internal reference temperature compensation in the measuring instrument, it is almost impossible to determine the proportion of errors due to the thermocouple itself. The study found that the measurement error can be significantly reduced when determining the temperature of technological processes using an external reference node. At the same time, since the special application of temperature measurements of technological processes covers the measurement of indoor and outdoor temperatures, the errors due to the effect of radiation on the sensor from the surrounding surfaces are many times higher than the allowable error. For this reason, tools have been proposed to assess the radiation effects on typical thermocouples, along with proposals for modification of thermocouple sensors to reduce the potential radiation exposure and thus increase measurement accuracy.

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Yu, Shuang, Haoran Guo, Wenlong Yang, Yanqiao Zhao, Haibin Wu, Xiaoming Sun, and Xiaoyang Yu. "Depth Measurement Error Analysis and Structural Parameter Correction of Structured Light Depth Imager." Photonics 11, no. 5 (April 24, 2024): 396. http://dx.doi.org/10.3390/photonics11050396.

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Considering that structured light depth imagers are difficult to use for precision measurements due to their limited measurement accuracy, we propose an innovative method for correcting structural parameters of structured light depth imagers to reduce the depth measurement error caused by structural parameter errors. For the structured light depth imager, the analytical imaging model is established, and the model of depth error caused by structural parameter errors is established based on the analysis of the depth measurement error analysis. Then, structural parameters are corrected according to the depth measurement error analysis and processing based on experimental depth imaging data of the standard reference plane at the maximum depth. As a result, the corrected analytical imaging model and corrected depth measurement values are obtained. Experimental results have demonstrated the success of this proposed method and its simplicity and convenience.

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13

Chen, Peng, and Huang. "A New Error Model and Compensation Strategy of Angle Encoder in Torsional Characteristic Measurement System." Sensors 19, no. 17 (August 30, 2019): 3772. http://dx.doi.org/10.3390/s19173772.

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For systems of measurement, geometric errors such as manufacturing and assembly errors could have a significant impact on the accuracy of the angle encoders of the system. In this study, an error model of angular measurement with geometric errors of a torsional characteristic measurement system was developed based on multibody system theory, the aim of which was to reveal the impact of geometric errors on angular measurement and to compensate the measurement error. According to the principle of spatial error transfer, the decomposition of geometric errors is illustrated and the error matrix of geometric errors is constructed by the Denavit–Hartenberg (DH) method. Subsequently, an error compensation function can be obtained and the impact of geometric error on angular measurement is discussed. Finally, we demonstrate by the experimental results of an ultra-autocollimator that the proposed error compensation method reduced the angular measurement error from 3.7% to 0.7%, which shows that the proposed error model can effectively predict the angular measurement error. In addition, it can be seen from the measurement results of the RV reducer that the error of the torsional characteristic measurement system decreased significantly.

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14

Deaton, Michael, and Wayne A. Fuller. "Measurement Error Models." Technometrics 31, no. 1 (February 1989): 112. http://dx.doi.org/10.2307/1270371.

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Papaioannou, T., and W. A. Fuller. "Measurement Error Models." Biometrics 46, no. 2 (June 1990): 542. http://dx.doi.org/10.2307/2531463.

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Stefanski, L. A., Wayne Fuller, and John Wiley. "Measurement Error Models." Journal of Business & Economic Statistics 6, no. 3 (July 1988): 399. http://dx.doi.org/10.2307/1391893.

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JENNINGS, BONNE MOWINSKI, and SANDRA ROGERS. "Managing Measurement Error." Nursing Research 38, no. 3 (May 1989): 186???187. http://dx.doi.org/10.1097/00006199-198905000-00023.

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Deaton, Michael. "Measurement Error Models." Technometrics 31, no. 1 (February 1989): 111–12. http://dx.doi.org/10.1080/00401706.1989.10488482.

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Gunst, Richard F. "Measurement Error Models." Journal of Quality Technology 21, no. 4 (October 1989): 294–95. http://dx.doi.org/10.1080/00224065.1989.11979192.

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Corbett, Margaret, and Wayne A. Fuller. "Measurement Error Models." Statistician 37, no. 1 (1988): 83. http://dx.doi.org/10.2307/2348385.

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Satorra, Albert, and Wayne A. Fuller. "Measurement Error Models." Journal of Educational Statistics 13, no. 4 (1988): 351. http://dx.doi.org/10.2307/1164709.

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Buonaccorsi, John, and Wayne A. Fuller. "Measurement Error Models." Journal of the American Statistical Association 83, no. 403 (September 1988): 910. http://dx.doi.org/10.2307/2289335.

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Hayman, Simon. "Daylight measurement error." Lighting Research and Technology 35, no. 2 (June 1, 2003): 101–10. http://dx.doi.org/10.1191/1477153503li086oa.

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Stefanski, L. A. "Measurement Error Models." Journal of the American Statistical Association 95, no. 452 (December 2000): 1353–58. http://dx.doi.org/10.1080/01621459.2000.10474347.

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Gleser, Leon Jay. "Measurement error models." Chemometrics and Intelligent Laboratory Systems 10, no. 1-2 (February 1991): 45–57. http://dx.doi.org/10.1016/0169-7439(91)80033-m.

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Jiang, Zhichao, and Peng Ding. "Measurement errors in the binary instrumental variable model." Biometrika 107, no. 1 (November 21, 2019): 238–45. http://dx.doi.org/10.1093/biomet/asz060.

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Summary Instrumental variable methods can identify causal effects even when the treatment and outcome are confounded. We study the problem of imperfect measurements of the binary instrumental variable, treatment and outcome. We first consider nondifferential measurement errors, that is, the mismeasured variable does not depend on other variables given its true value. We show that the measurement error of the instrumental variable does not bias the estimate, that the measurement error of the treatment biases the estimate away from zero, and that the measurement error of the outcome biases the estimate toward zero. Moreover, we derive sharp bounds on the causal effects without additional assumptions. These bounds are informative because they exclude zero. We then consider differential measurement errors, and focus on sensitivity analyses in those settings.

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Roy, Surupa, and Tathagata Banerjee. "Generalized Linear Measurement-Error Models with Multivariate t-Measurement Error." Calcutta Statistical Association Bulletin 51, no. 3-4 (September 2001): 191–204. http://dx.doi.org/10.1177/0008068320010303.

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Wan, Peng, Jun Jie Guo, and Hai Tao Li. "Study on the Method of Error Identification and Compensation for Gear Measuring Center." Advanced Materials Research 482-484 (February 2012): 1821–28. http://dx.doi.org/10.4028/www.scientific.net/amr.482-484.1821.

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Gear Measuring Center(GMC) is commonly used to test error of the tooth surface of the gear, whose geometric accuracy directly impacts on the accuracy of measurement. How to quickly and accurately detect space geometric error of the measuring machine and compensate becomes the essential means of high-precision measurements. According to the problem above, in the paper, three-beams laser detection technology is proposed. The detection of the geometric errors of the linear axis was achieved. The accurate measurement for the position and attitude of the plane mirror on measurement seat was achieved based on laser telemetry principle. The positioning error, the pitching angle errors, the deflection angle errors and the straightness errors were separated. And then based on multi-body system theory, by using of homogeneous coordinate transformation, the error compensation model of 4-axis measuring machine which includes three shifting pairs and one revolute pair was established, and the algorithm was given in the paper. The theoretical foundation for real-time compensation of 4-axis GMC was established. The geometric errors of GMC can be improved by the method of the error detection and compensation. The method plays a very important role in high-precision measurements.

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Wolf, Matthew B. "Hemoglobin-Dilution Method: Effect of Measurement Errors on Vascular Volume Estimation." Computational and Mathematical Methods in Medicine 2017 (2017): 1–5. http://dx.doi.org/10.1155/2017/3420590.

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The hemoglobin-dilution method (HDM) has been used to estimate changes in vascular volumes in patients because direct measurements with radioisotopes are time-consuming and not practical in many facilities. The HDM requires an assumption of initial blood volume, repeated measurements of plasma hemoglobin concentration, and the calculation of the ratio of hemoglobin measurements. The statistics of these ratio distributions resulting from measurement error are ill-defined even when the errors are normally distributed. This study uses a “Monte Carlo” approach to determine the distribution of these errors. The finding was that these errors could be closely approximated with a log-normal distribution that can be parameterized by a geometric mean (X) and a dispersion factor (S). When the ratio of successive Hb concentrations is used to estimate blood volume, normally distributed hemoglobin measurement errors tend to produce exponentially higher values ofXandSas the SD of the measurement error increases. The longer tail of the distribution to the right could produce much greater overestimations than would be expected from the SD values of the measurement error; however, it was found that averaging duplicate and triplicate hemoglobin measurements on a blood sample greatly improved the accuracy.

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Andersen, C. M., R. Bro, and P. B. Brockhoff. "Quantifying and handling errors in instrumental measurements using the measurement error theory." Journal of Chemometrics 17, no. 12 (December 2003): 621–29. http://dx.doi.org/10.1002/cem.830.

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Sato, Ryuta, and Kotaro Nagaoka. "Motion Trajectory Measurement of NC Machine Tools Using Accelerometers." International Journal of Automation Technology 5, no. 3 (May 5, 2011): 387–94. http://dx.doi.org/10.20965/ijat.2011.p0387.

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NC controllers use different types of compensation systems to improve motion accuracy of feed drive systems against pitch error, friction, backlash, and elastic deformation. Compensators for static error, such as pitch and squareness errors, are tuned semiautomatically. However, for dynamic error such as quadrant glitches and vibration, parameter tuning takes too much time. In this study, motion trajectory measurement for parameter tuning using accelerometers has been proposed. In the methods, displacements of each axis can be obtained from measured accelerations along each axis. Although the obtained displacements include some errors, such as setting error, sensitivity error, and integral error in numerical integration, the errors can be compensated for based on the feedback positions measured simultaneously. To confirm the feasibility of the proposed methods, measurement tests using a grid encoder are carried out. Results of the measurements confirm that the circular trajectories and vibrations can be measured by the proposed method. Automatic parameter tuning method for the backlash compensator is also proposed.

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Xie, Yuyang, Tao Yang, Xiaofeng Wang, Xi Chen, Shuxin Pang, Juan Hu, Anxian Wang, Ling Chen, and Zehao Shen. "Applying a Portable Backpack Lidar to Measure and Locate Trees in a Nature Forest Plot: Accuracy and Error Analyses." Remote Sensing 14, no. 8 (April 8, 2022): 1806. http://dx.doi.org/10.3390/rs14081806.

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Accurate tree positioning and measurement of structural parameters are the basis of forest inventory and mapping, which are important for forest biomass calculation and community dynamics analyses. Portable backpack lidar that integrates the simultaneous localization and mapping (SLAM) technique with a global navigation satellite system receiver has greater flexibility for tree inventory than terrestrial laser scanning, but it has never been used to measure and map forest structure in a large area (>101 hectares) with high tree density. In the present study, we used the LiBackpack DG50 backpack lidar system to obtain the point cloud data of a 10 ha plot of subtropical evergreen broadleaved forest, and applied these data to quantify errors and related factors in the diameter at breast height (DBH) measurements and positioning for more than 1900 individual trees. We found an average error of 4.19 cm in the DBH measurements obtained by lidar, compared with manual field measurements. The incompleteness of the tree stem point clouds was the main factor that caused the DBH measurement errors, and the field DBH measurements and density of the point clouds also had significant impacts. The average tree positioning error was 4.64 m, and it was significantly affected by the distance and route length from the measured trees to the data acquisition start position, whereas it was affected little by the habitat complexity and characteristics of tree stems. The tree positioning measurement error led to increases in the mean value and variability of paired-tree distance error as the sample plot scale increased. We corrected the errors based on the estimates of predictive models. After correction, the DBH measurement error decreased by 31.3%, the tree positioning error decreased by 44.3%, and the paired-tree distance error decreased by 56.3%. As the sample plot scale increased, the accumulated paired-tree distance error stabilized gradually.

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Mehtätalo, Lauri, and Annika Kangas. "An approach to optimizing field data collection in an inventory by compartments." Canadian Journal of Forest Research 35, no. 1 (January 1, 2005): 100–112. http://dx.doi.org/10.1139/x04-139.

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This study presents models for the expected error of the total volume and saw timber volume due to sampling errors of stand measurements. The measurements considered are horizontal point sample plots, stem numbers from circular plots, sample tree heights, sample order statistics (i.e., quantile trees), and sample tree heights from the previous inventory. Different measurement strategies were constructed by systematically varying the numbers of these measurements. A model system developed for this study was used in a data set of 170 stands to predict the total volume and saw timber volume of each stand with each measurement strategy. The errors of these volumes were modeled using stand characteristics and the numbers of measurements as predictors. The most important factors affecting the error in the total volume were the number of horizontal point sample plots and height sample trees. In addition, the number of quantile trees had a strong effect on the error of saw timber volume. The errors were slightly reduced when an old height measurement was used. There were significant interactions between stand characteristics and measurement strategies. Thus, the optimal measurement strategy varies between stands. A demonstration is provided of how constrained optimization can be used to find the optimal strategy for any one stand.

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Shettles, Michael, Thomas Hilker, and Hailemariam Temesgen. "Examination of uncertainty in per unit area estimates of aboveground biomass using terrestrial LiDAR and ground data." Canadian Journal of Forest Research 46, no. 5 (May 2016): 706–15. http://dx.doi.org/10.1139/cjfr-2015-0265.

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In estimating aboveground forest biomass (AGB), three sources of error that interact and propagate include (i) measurement error, the quality of the tree-level measurement data used as inputs for the individual-tree equations; (ii) model error, the uncertainty about the equations of the individual trees; and (iii) sampling error, the uncertainty due to having obtained a probabilistic or purposive sample, rather than a census, of the trees on a given area of forest land. Monte Carlo simulations were used to examine measurement, model, and sampling errors and to compare total uncertainty between models and between a phase-based terrestrial laser scanner (TLS) and traditional forest inventory instruments. Input variables for the equations were diameter at breast height, total tree height (defined the height from the uphill side of the tree to the tree top), and height to crown base; these were extracted from the terrestrial LiDAR data. Relative contributions for measurement, model, and sampling errors were 5%, 70%, and 25%, respectively, when using TLS, and 11%, 66%, and 23%, respectively, when using the traditional inventory measurements as inputs into the models. We conclude that the use of TLS can reduce measurement errors of AGB compared with traditional inventory measurements.

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Avišāne, Anita, Janis Rudzitis, Gunārs Upītis, and Janis Vilcāns. "Influence of Flexible Body Contact Deformation on the Linear Dimension Measurement Precision." Solid State Phenomena 199 (March 2013): 321–25. http://dx.doi.org/10.4028/www.scientific.net/ssp.199.321.

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The common measurement error when measuring the component geometrical dimensions using universal contact measurement instruments is caused by different factors, such as error of the measurement instrument, personal reading errors, effect of surface roughness on the measuring line deviation, influence of contact deformation measurement force, and others. The present article examines one of these factors, i.e. contact deformations under the influence of measurement force. To make precise measurements it is essential to find out the effect of roughness of measured components. High roughness creates additional measurement errors. It is particularly important in the measurement of thin components, flexible materials and films, as well as for components with nanocoating. Flexible bodies in the meaning of this article are components of different shape and sizes made of rubber or soft plastic. This article studies principles of error formation based on the deformation of surface roughness and basic material.

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Hong, Hanwoom, Sung K. Ahn, and Sinsup Cho. "Estimation of error correction model with measurement errors." Journal of Statistical Computation and Simulation 90, no. 9 (April 3, 2020): 1661–80. http://dx.doi.org/10.1080/00949655.2020.1743991.

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Zhang, Yan, Huajia Wang, Danwen Yu, Liu Yang, Wenjun Cao, and Yongxin Yang. "Influencing Factor and Error Analysis of Operating Capacitor Voltage Transformer Harmonic Measurement." Journal of Physics: Conference Series 2121, no. 1 (November 1, 2021): 012013. http://dx.doi.org/10.1088/1742-6596/2121/1/012013.

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Abstract With the increasing demands of power quality monitoring and management, the problem of harmonic measurement error caused by the widespread operation of capacitor voltage transformers (CVT) in high-voltage power grids has been unavoidable. This paper analyses the influence of environmental factors on harmonic measurement error of CVT, and proposes a new method for analysing the harmonic measurement errors of operating CVT, which explains the unstable phenomenon of CVT measurement errors based on field comparison test, and provides a progressing screening method of effective analysis data. the CVT harmonic error characteristic analysis method proposed in this paper considers the impact of field installation conditions, electromagnetic environment, and other actual operating environment, which can reflect the actual harmonic error characteristics of CVT in field operation. A CVT harmonic measurement system is established based on the proposed method. The validation and effectiveness of the proposed method is illustrated on a field measurements of 1000kV CVT in Shandong Province.

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He, C. Y., W. M. Li, and T. Huang. "A New Method for Single-Measurement and Compensating the Position Errors of a Three-Axis Machine Tool." Materials Science Forum 697-698 (September 2011): 314–19. http://dx.doi.org/10.4028/www.scientific.net/msf.697-698.314.

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There is great practical significance in error compensation of CNC machine tools. In this dissertation, the measurement theory and application methods of some advanced measure were analyzed. From those measurement methods, we found the drawback of comprehensive error measurement. Further more, this paper has detailed a new defined as single-measurement for the sake of the double-frequency laser interferometer to measure 14 geometric errors of three-axis system. The method facilitates measurements and shortens the machine shutdown time.

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Wan, Zhenhua, Kaichun Zhao, Haoyuan Cheng, and Peng Fu. "Measurement Modeling and Performance Analysis of a Bionic Polarimetric Imaging Navigation Sensor Using Rayleigh Scattering to Generate Scattered Sunlight." Sensors 24, no. 2 (January 13, 2024): 498. http://dx.doi.org/10.3390/s24020498.

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The bionic polarimetric imaging navigation sensor (BPINS) is a navigation sensor that provides absolute heading, and it is of practical engineering significance to model the measurement error of BPINS. The existing BPINSs are still modeled using photodiode-based measurements rather than imaging measurements and are not modeled systematically enough. This paper proposes a measurement performance analysis method of BPINS that takes into account the geometric and polarization errors of the optical system. Firstly, the key error factors affecting the overall measurement performance of BPINS are investigated, and the Stokes vector-based measurement error model of BPINS is introduced. Secondly, based on its measurement error model, the effect of the error source on the measurement performance of BPINS is quantitatively analyzed using Rayleigh scattering to generate scattered sunlight as a known incident light source. The numerical results show that in angle of E-vector (AoE) measurement, the coordinate deviation of the principal point has a greater impact, followed by grayscale response inconsistency of CMOS and integration angle error of micro-polarization array, and finally lens attenuation; in degree of linear polarization (DoLP) measurement, the grayscale response inconsistency of CMOS has a more significant impact. This finding can accurately guide the subsequent calibration of BPINS, and the quantitative results provide an important theoretical reference for its optimal design.

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Feathers, David, Victor Paquet, and Colin Drury. "Effects of Level of Automation on Errors and Consistency in Two- and Three-Dimensional Anthropometry." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 46, no. 13 (September 2002): 1215–19. http://dx.doi.org/10.1177/154193120204601344.

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This study investigated some potential sources of error, and their consequences, across different types of anthropometric measurement methods. The measurement methods included use of traditional anthropometric instruments, as well as two versions of an electromechanical approach that recorded three-dimensional locations of body parts. Several errors were hypothesized to be from aspects related to human information processing and their interaction with differing methods. Measurements obtained with the traditional approach and two versions of the electromechanical approach were then compared for two experienced anthropometrists who each took 72 measurements on a cadaveric forearm while it was clothed and unclothed. ANOVA demonstrated that there were differences in measurement consistency between individuals, measurement methods and clothing conditions. This study was an initial attempt to investigate the potential sources of error within anthropometric measurements via focusing on the information presented to the measurer and the application of this information to the consistency of measurement. The findings provide information about the causes of error and the saviors of consistency.

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Zaporozhets, Artur, and Denys Kataiev. "Method of compensating for instrumental uncertainty in measurements using a coordinate measuring ARM." System Research in Energy 2024, no. 1 (February 16, 2024): 45–53. http://dx.doi.org/10.15407/srenergy2024.01.045.

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Due to the influence of dynamic factors in various measurement configurations, the degree of uncertainty in measurements using a Coordinate Measuring Arm (CMA) is directly related to the measurement configuration. However, existing models for compensating CMA errors do not account dynamic factors, which impose certain limits for improving the accuracy of CMAs. To solve this issue, a method for residual error correction based on a polynomial model for single-point measurements was proposed. The influence of the CMA configuration on the residual probe error was analyzed. To enhance accuracy, a polynomial model has been developed by studying the relationship between the rotation angles of the CMA's moving elements and the probe coordinates in a cylindrical coordinate system. Experimental results demonstrate that the residual error correction method significantly compensates for instrumental uncertainty, greatly improving the accuracy of measurements using CMAs. Keywords: coordinate measuring arm, measurement error, coordinate measurements, calculation method, single-point residual correction, compensation.

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Schifeling, Tracy, Jerome P. Reiter, and Maria Deyoreo. "Data Fusion for Correcting Measurement Errors." Journal of Survey Statistics and Methodology 7, no. 2 (May 25, 2018): 175–200. http://dx.doi.org/10.1093/jssam/smy010.

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AbstractOften in surveys, key items are subject to measurement errors. Given just the data, it can be difficult to determine the extent and distribution of this error process and, hence, to obtain accurate inferences that involve the error-prone variables. In some settings, however, analysts have access to a data source on different individuals with high-quality measurements of the error-prone survey items. We present a data fusion framework for leveraging this information to improve inferences in the error-prone survey. The basic idea is to posit models about the rates at which individuals make errors, coupled with models for the values reported when errors are made. This can avoid the unrealistic assumption of conditional independence typically used in data fusion. We apply the approach on the reported values of educational attainments in the American Community Survey, using the National Survey of College Graduates as the high-quality data source. In doing so, we account for the sampling design used to select the National Survey of College Graduates. We also present a process for assessing the sensitivity of various analyses to different choices for the measurement error models. Supplemental material is available online.

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Romanova, M. A., and M. V. Mamchenko. "Method and Algorithm for Estimating the Maximum Total Error of an Automotive LiDAR." Journal of Physics: Conference Series 2096, no. 1 (November 1, 2021): 012179. http://dx.doi.org/10.1088/1742-6596/2096/1/012179.

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Abstract The article proposes a method and an appropriate algorithm for estimating the error of the measurements of the LiDAR as a technical measurement system to “include” this evaluation in the given accuracy. A generic model for the LiDAR’s measurements is described, a mathematical model of the measurements with the total values of random and systematic errors is given. Based on this method the algorithm for estimating the maximum total error (not exceeding the accuracy of the measurement) is formed. The algorithm complies both with the mathematical description presented in the article, and the methodology described in Russian standard GOST R 8.736-2011. On the basis of the calculated estimate of the weighted average error, it is possible to construct a technical device, that provides a three-fold reserve in terms of measurement accuracy.

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Ni, J., P. S. Huang, and S. M. Wu. "A Multi-Degree-of-Freedom Measuring System for CMM Geometric Errors." Journal of Engineering for Industry 114, no. 3 (August 1, 1992): 362–69. http://dx.doi.org/10.1115/1.2899804.

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A precision multi-degree-of-freedom measuring (MDFM) system has been developed and implemented for the simultaneous measurement of straightness, pitch, yaw, and roll errors of the moving axes of a CMM. The system is based on the principles of laser alignment and autocollimator. Its measurement principles and the influence of laser beam drifts on its measurement quality have been investigated and some improvement schemes have been implemented. Through the measurements of actual as well as artificially created geometric errors of the CMM, it has been found that the system’s accuracy of measuring straightness error components is better than 1 μm and its accuracy for angular error measurements is better than 0.5 arcsec.

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Tu, Jia, Defeng Gu, Yi Wu, and Dongyun Yi. "Error Modeling and Analysis for InSAR Spatial Baseline Determination of Satellite Formation Flying." Mathematical Problems in Engineering 2012 (2012): 1–23. http://dx.doi.org/10.1155/2012/140301.

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Spatial baseline determination is a key technology for interferometric synthetic aperture radar (InSAR) missions. Based on the intersatellite baseline measurement using dual-frequency GPS, errors induced by InSAR spatial baseline measurement are studied in detail. The classifications and characters of errors are analyzed, and models for errors are set up. The simulations of single factor and total error sources are selected to evaluate the impacts of errors on spatial baseline measurement. Single factor simulations are used to analyze the impact of the error of a single type, while total error sources simulations are used to analyze the impacts of error sources induced by GPS measurement, baseline transformation, and the entire spatial baseline measurement, respectively. Simulation results show that errors related to GPS measurement are the main error sources for the spatial baseline determination, and carrier phase noise of GPS observation and fixing error of GPS receiver antenna are main factors of errors related to GPS measurement. In addition, according to the error values listed in this paper, 1 mm level InSAR spatial baseline determination should be realized.

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Zhao, Xiaowei, Huifu Du, and Daguo Yu. "Improving Measurement Accuracy of Deep Hole Measurement Instruments through Perspective Transformation." Sensors 24, no. 10 (May 16, 2024): 3158. http://dx.doi.org/10.3390/s24103158.

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Deep hole measurement is a crucial step in both deep hole machining and deep hole maintenance. Single-camera vision presents promising prospects in deep hole measurement due to its simple structure and low-cost advantages. However, the measurement error caused by the heating of the imaging sensor makes it difficult to achieve the ideal measurement accuracy. To compensate for measurement errors induced by imaging sensor heating, this study proposes an error compensation method for laser and vision-based deep hole measurement instruments. This method predicts the pixel displacement of the entire field of view using the pixel displacement of fixed targets within the camera’s field of view and compensates for measurement errors through a perspective transformation. Theoretical analysis indicates that the perspective projection matrix changes due to the heating of the imaging sensor, which causes the thermally induced measurement error of the camera. By analyzing the displacement of the fixed target point, it is possible to monitor changes in the perspective projection matrix and thus compensate for camera measurement errors. In compensation experiments, using target displacement effectively predicts pixel drift in the pixel coordinate system. After compensation, the pixel error was suppressed from 1.99 pixels to 0.393 pixels. Repetitive measurement tests of the deep hole measurement instrument validate the practicality and reliability of compensating for thermal-induced errors using perspective transformation.

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George, Benny, and N. Muthuveerappan. "Error Estimation of Measured Exhaust Gas Temperature in Afterburner Mode in an Aero Gas Turbine Engine." Defence Science Journal 72, no. 1 (January 5, 2022): 10–17. http://dx.doi.org/10.14429/dsj.72.16824.

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In a turbofan engine, thrust is a key parameter which is measured or estimated from various parameters acquired during engine testing in an engine testbed. Exhaust Gas Temperature (EGT) is the most critical parameter used for thrust calculation. This work presents a novel way to measure and correct the errors in EGT measurement. A temperature probe is designed to measure EGT in the engine jet pipe using thermocouples. The temperature probe is designed to withstand the mechanical and temperature loads during the operation. Structural analysis at the design stage provided a strength margin of 90% and eigenfrequency margin of more than 20%. Thermal analysis is carried out to evaluate maximum metal temperature. Errors are quite high in high-temperature measurements which are corrected using the available methodologies. The velocity error, conduction error, and radiation error are estimated for the measured temperature. The difference of 97 K between the measured gas temperature and calculated gas temperature from measured thrust is explained. The estimated velocity error is 1 K, conduction error is 3 K, and radiation error is 69 K. Based on the error estimation, the measurement error is brought down to 24 K. After applying the above corrections, the further difference of 24 K between measured and estimated value can be attributed to thermocouple error of +/-0.4% of the reading for class 1 accuracy thermocouple, other parameter measurement errors, and analysis uncertainties. The present work enables the designer to calculate the errors in high-temperature measurement in a turbofan engine.

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Gui, Mingzhen, Hua Yang, Dangjun Zhao, Mingzhe Dai, and Chengxi Zhang. "Analysis and Compensation of Sun Direction Error on Solar Disk Velocity Difference." Mathematics 11, no. 17 (August 29, 2023): 3716. http://dx.doi.org/10.3390/math11173716.

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Solar disk velocity difference is an emerging celestial navigation measurement acquired through four spectrometers positioned on the four corners of the quadrangular pyramid. The alignment of the pyramid’s axis with the direction from the sun to the spacecraft is crucial. However, the sun sensor measurement error inevitably leads to the sun direction error, which both significantly affect navigation accuracy. To address this issue, this article proposes an augmented state sun direction/solar disk velocity difference integrated navigation method. By analyzing the impact of the sun direction error on sun direction and solar disk velocity difference measurements, the errors of the solar elevation and azimuth angle are extended to the state vector. The navigation method establishes state and measurement models that consider these errors. Simulation results show that the position error and velocity error of the proposed method are reduced by 97.51% and 96.91% compared with those of the integrated navigation with the sun direction error, respectively. The result demonstrates that the proposed method effectively mitigates the impact of sun direction error on navigation performance. In addition, the proposed method can maintain a satisfactory error suppression effect under different sun direction error values.

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Cai, Mengyang, Huiqin Mao, Cuihong Chen, Xvpeng Wei, and Tianqi Shi. "Measuring Greenhouse Gas Emissions from Point Sources with Mobile Systems." Atmosphere 13, no. 8 (August 6, 2022): 1249. http://dx.doi.org/10.3390/atmos13081249.

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The traditional least squares method for the retrieval of CO2 emissions from CO2 emission sources is affected by the nonlinear characteristics of the Gaussian plume model, which leads to the optimal estimation of CO2 emissions easily falling into local minima. In this study, ACA–IPFM (ant colony algorithm and interior point penalty function) is proposed to remedy the shortcomings of the traditional least squares method, which makes full use of the global search property of the ant colony algorithm and the local exact search capability of the interior point penalty function to make the optimal estimation of CO2 emissions closer to the global optimum. We evaluate the errors of several parameters that are most likely to affect the accuracy of the CO2 emission retrieval and analyze these errors jointly. These parameters include wind speed measurement error, wind direction measurement error, CO2 concentration measurement error, and the number of CO2 concentration measurements. When the wind speed error is less than 20%, the inverse error of CO2 concentration emission is less than 1% and the uncertainty is less than 3%, when the wind direction error is less than 55 degrees, the inverse error is less than 1% and the uncertainty is less than 3%, when the CO2 concentration measurement error is less than 10%, the inverse error is less than 1% and the uncertainty is less than 3.3%, and when the measurement quantity is higher than 60, the inverse error is less than 1% and the uncertainty is less than 3%. In addition, we simulate the concentration observations on different paths under the same conditions, and invert the CO2 emissions based on these simulated values. Through the retrieval results, we evaluate the errors caused by different paths of measurements, and have demonstrated that different paths are affected by different emission sources to different degrees, resulting in different inversion accuracies for different paths under the same conditions in the end, which can provide some reference for the actual measurement route planning of the mobile system. Combined with the characteristics of the agility of the mobile system, ACA–IPFM can extend the monitoring of CO2 emissions to a wider area.

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Sandomirski, S. G. "Dependence of the Correlation Coefficient Between the Results of a Parameter Measurement and Its True Values on the Reduced Measurement Error." Devices and Methods of Measurements 10, no. 1 (March 15, 2019): 90–98. http://dx.doi.org/10.21122/2220-9506-2019-10-1-90-98.

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Magnetic testing of steels' mechanical properties is based on their correlation with steels' magnetic parameters. The purpose of this work was to establish dependence of the attainable correlation coefficient Rmax between measurement results and the parameter values a on the reduced error of its measurement. The article proposes a model of the correlation field between the parameter true values and the results of its measurement with a given reduced error δ. The merits and legitimacy of using the model for estimation of the achievable correlation coefficient Rmax are substantiated. Analysis of influence of δ parameter measurement in different ranges d of its change on Rmax is carried out. Results are compared with the previous analysis for the relative measurement error. It has been established in this work that the coefficient Rmax calculated for the reduced measurement error is always smaller than Rmax one calculated for the relative measurement error. However in the practically important range of variation of d with δ ≤ 0.05 the difference between the Rmax values calculated for the reduced and relative measurement errors is not large. This allows us to use the developed formula for the dependence Rmax = Rmax (δ, d) at Rmax ≥ 0.8 for both relative and reduced measurement errors δ. The obtained result allows us using the reduced measurement error of a metrologically certified measuring instrument to obtain the maximum attainable correlation coefficient between the true values and the results of measuring a parameter in a given range of its change without measurements. As an example, we define the conditions for the non-destructive testing of steels under which one can use measuring of magnetic parameters with the installation certified based on the reduced measurement error.

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Journal articles on the topic 'Measurement error'

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