Measurement Accuracy Research Articles

Stereo digital image correlation using binocular super-resolution

Abstract The spatial resolution and measurement accuracy of the digital image correlation (DIC) method are constrained by camera resolution. This limitation is primarily determined by hardware costs. However, in current stereo DIC measurements, only the gray level or its gradient from two images is used for integer-pixel matching and sub-pixel optimization. It implicitly treats the two images from different viewpoints as independent entities before correlating them. However, the inherent structural information has not been fully utilized. This previously overlooked structural information provides a novel approach to enhancing the accuracy of DIC by leveraging the inherent correlations between the stereo image pairs. The realization of binocular super-resolution typically requires a relatively small parallax. Moreover, the DIC method can achieve image window pairing with small parallax through pre-matching. This implies that binocular super-resolution and stereo-DIC can complement each other by sharing information. In this paper, the DIC method is employed for whole-pixel image matching, while the binocular super-resolution method, based on deep learning, is applied to process the matched image pairs. Building on previous experiments, extensive datasets containing diverse experimental scenes and various speckle patterns were compiled and utilized. Furthermore, the DIC method can establish training datasets with minimal parallax through integer-pixel matching, thereby achieving highly effective super-resolution results.Experimental results demonstrate that super-resolution images with a higher signal-to-noise ratio can be obtained. Additionally, it effectively provides more image details, which enhance the calculation accuracy and resolution of DIC.

Simulation of Fluid Flow through Orifice Meter

The modeling of fluid flow using an orifice meter is an engineering endeavor aimed at thoroughly investigating and optimizing fluid flow measurement in various industrial applications. Orifice meters are highly regarded for their accurate measurement of fluid flow rates as they pass through a specifically designed orifice plate, utilizing the principles of fluid dynamics. The primary objective of this project is to develop a computational fluid dynamics (CFD) model capable of simulating the intricate fluid flow through an orifice meter. The simulation encompasses detailed geometric features of the orifice meter, including the precise dimensions of the orifice plate, pipe diameter, and any relevant taper angles. Additionally, the model takes into account various fluid parameters, boundary conditions, and factors such as velocity and pressure at different points within the system. The comprehensive study visualizes and quantifies key fluid properties, such as velocity profiles, pressure differentials, and flow velocities, across the entire length of the orifice meter using CFD analysis. This in-depth analysis provides crucial insights into the dynamic performance of the orifice meter. The obtained information holds significant potential to revolutionize flow rate measurement accuracy, efficiency, and cost-effectiveness in diverse industries, including water management, chemical processing, and oil and gas. The project's methodology for simulating fluid flow through orifice meters can bring about substantial improvements in the understanding and optimization of fluid flow in industrial processes.

Research on the Measurement Technology for Pretension Stress on Small-Sized Bolts Based on the Piezoelectric Ultrasonic Resonance Method

With the widespread application of small-sized bolts in aerospace and other fields, the demand for measuring their connection structures is increasing. Currently, although ultrasonic longitudinal wave methods are commonly used for bolt pretension stress measurement, their accuracy is limited for small-sized bolts. This paper proposes a piezoelectric acoustic resonance method (PZTAR) for small-sized bolt pretension stress measurement based on acoustic elasticity theory, ultrasonic resonance principles, and a bolt stress–strain model. The method involves analyzing the ultrasonic time-domain signals of small-sized bolts under load in the frequency domain to better evaluate the changes in the ultrasonic frequencies under different pretension stress. The effectiveness of this method is verified through pretension stress measurement experiments. The results indicate that the proposed ultrasonic resonance method achieves an average error of less than 5% for M5 specification bolts. Compared to traditional ultrasonic time delay methods, the proposed method demonstrates higher measurement accuracy. Additionally, the ultrasonic resonance method exhibits better robustness during the measurement process.

How to take and record a manual blood pressure measurement.

Accurate measurement of a patient's blood pressure (BP) is essential to identify hypotension or hypertension and to inform subsequent management and treatment decisions. The auscultatory, or manual, method remains the gold standard for non-invasive BP measurement, so it is vital that nurses are able to undertake this procedure accurately. This article explains how to take and record a manual BP measurement using an aneroid sphygmomanometer and a stethoscope. Nurses and nursing students undertaking this procedure must be equipped with the knowledge and skills to do so proficiently and work within their scope of practice. • BP measurement comprises two pressure readings, systolic and diastolic, which are measured in millimetres of mercury (mmHg) and expressed in documentation as a 'fraction'. • Inaccurate BP measurement, whether overestimation or underestimation, can result in diagnostic errors and incorrect risk assessment and decision-making. • Various factors can influence the accuracy of BP measurement, including patient positioning, cuff size, arm position and correct use of the stethoscope. • It is vital to ensure regular maintenance and recalibration of BP measuring equipment, in accordance with the manufacturer's instructions, to ensure accuracy of readings. REFLECTIVE ACTIVITY: 'How to' articles can help to update your practice and ensure it remains evidence based. Apply this article to your practice. Reflect on and write a short account of: • How this article might improve your practice when taking a manual BP measurement. • How you could use this information to educate nursing students or your colleagues on the appropriate steps when taking and recording a manual BP measurement.

Optimization of Centrifugal Pump Properties to Improve the Accuracy of Water Discharge and Pump Head Measurements

Centrifugal pumps are extensively used in industries and water management systems, where accurate measurements of water flow rate and pump head are essential for evaluating performance. However, inaccuracies arising from suboptimal designs of training kits present challenges in educational environments. This study aimed to optimize a centrifugal pump training kit to enhance measurement accuracy and reliability. The research was conducted over four months, involving modifications to the impeller, casing, and pressure measurement systems, along with rigorous calibration to minimize errors. Measurements of suction pressure, discharge pressure, water flow rate, and pump head were repeated under standardized conditions to ensure data consistency. The results demonstrated significant improvements, with consistent measurements of suction pressure (21 inHg), discharge pressure (15 PSI), water flow rate (0.5 L/s), and pump head (1.38 mH₂O). These optimizations reduced system inefficiencies, such as backflow and turbulence, and enhanced the kit’s ability to replicate real-world operating conditions. The improved training kit provides students with a reliable tool for practical learning, bridging theoretical concepts with real-world applications in fluid mechanics. This study underscores the importance of continual enhancement of laboratory teaching tools to support effective education and industrial relevance.

Carbon dioxide removal (CDR) potential in temperate macroalgal forests: A comparative study of chemical and biological net ecosystem production (NEP)

The carbon dioxide removal (CDR) capacity of macroalgae, a crucial component in climate regulation, has gained increasing attention. However, accurately estimating the CDR potential of macroalgae in natural conditions remains challenging, necessitating the use of multiple independent methods to reduce the uncertainties in these estimates. In this study, we compared two methods for estimating net ecosystem production (NEP), a key parameter in determining CDR potential: 1) NEPChem., derived from seawater carbonate chemistry and 2) NEPBiol., based on photorespiratory measurements using benthic tent incubation. This study, conducted in a macroalgal forest dominated by Ecklonia cava, involved simultaneous measurements of NEPChem. and NEPBiol. over a course of one year. Our findings revealed that NEPBiol. was 1.23 times higher than NEPChem., with an annual rate of 3.69 tons CO2 ha−1 yr−1. These results suggest that both independent methods are reliable and can be used complementarily to improve the accuracy of NEP measurements, thereby enhancing estimates of the CDR potential of macroalgae.

Temperature-Based Long-Term Stabilization of Photoacoustic Gas Sensors Using Machine Learning

In this study, we address the challenge of estimating the resonance frequency of a photoacoustic detector (PAD) gas cell under varying temperature conditions, which is crucial for improving the accuracy of gas concentration measurements. We introduce a novel approach that uses a long short-term memory network and a self-attention mechanism to model resonance frequency shifts based on temperature data. To investigate the impact of the gas mixture temperature on the resonance frequency, we modified the PAD to include an internal temperature sensor. Our experiments involved multiple heating and cooling cycles with varying methane concentrations, resulting in a comprehensive dataset of temperature and resonance frequency measurements. The proposed models were trained and validated on this dataset, and the results demonstrate real-time prediction capabilities with a mean absolute error of less than 1 Hz for frequency shifts exceeding 30 Hz over four-hour periods. This approach allows continuous, real-time tracking of the resonance frequency without interrupting the laser operation, significantly enhancing gas concentration measurements and contributing to the long-term stabilization of the sensor. The results suggest that the proposed approach is effective in managing temperature-induced frequency shifts, making it a valuable tool for improving the accuracy and stability of gas sensors in practical applications.

Scanning Micromirror Calibration Method Based on PSO-LSSVM Algorithm Prediction

Scanning micromirrors represent a crucial component in micro-opto-electro-mechanical systems (MOEMS), with a broad range of applications across diverse fields. However, in practical applications, several factors inherent to the fabrication process and the surrounding usage environment exert a considerable influence on the accuracy of measurements obtained with the micromirror. Therefore, it is essential to calibrate the scanning micromirror and its measurement system. This paper presents a novel scanning micromirror calibration method based on the prediction of a particle swarm optimization-least squares support vector machine (PSO-LSSVM). The objective is to establish a correspondence between the actual deflection angle of the micromirror and the output of the measurement system employing a regression algorithm, thereby enabling the prediction of the tilt angle of the micromirror. The decision factor (R2) for this model at the x-axis reaches a value of 0.9947.

Robust-DefReg: a robust coarse to fine non-rigid point cloud registration method based on graph convolutional neural networks

Abstract Point cloud registration is a critical process in computer vision and measurement science, aimed at determining transformations between corresponding sets of points for accurate spatial alignment. In particular, non-rigid registration involves estimating flexible transformations that map a source point cloud to a target point cloud, even under conditions of stretching, compression, or other complex deformations. This task becomes especially challenging when addressing measurement-specific issues like varying degrees of deformation, noise, and outliers, all of which can impact measurement accuracy and reliability. This paper introduces Robust-DefReg, a novel method for non-rigid point cloud registration that applies graph convolutional networks (GCNNs) within a coarse-to-fine registration framework. This end-to-end pipeline harnesses global feature learning to establish robust correspondences and precise transformations, enabling high accuracy across different deformation scales and noise levels. A key contribution of Robust-DefReg is its demonstrated resilience to various challenges, such as substantial deformations, noise, and outliers, factors often underreported in existing registration literature. In addition, we present SynBench, a comprehensive benchmark dataset specifically designed for evaluating non-rigid point cloud registration in realistic measurement scenarios. Unlike previous datasets, SynBench incorporates a range of challenges, making it a valuable tool for the fair assessment of registration methods in measurement applications. Experimental results on SynBench and additional datasets show that Robust-DefReg consistently outperforms state-of-the-art methods, offering higher registration accuracy and robustness, even with up to 45% outliers. SynBench and the Robust-DefReg source code are publicly accessible for further research and development at https://doi.org/10.11588/data/R9IKCF and https://github.com/m-kinz/Robust-DefReg, respectively.

Single plant segmentation and growth parameters measurement of maize seedling stage based on point cloud intensity

Maize growth parameters are key pieces of information describing the growth, development and yield of plants, and they are of great significance for high quality and high yield maize breeding. Plants counting, row spacing, and plant spacing are closely related to maize sowing quality and yield. Plant height is closely related to maize photosynthetic rate and biomass. The main problem with measuring phenotypic parameters during the maize seedling stage is that maize plants are small, making it difficult to segment maize plant point clouds from ground point clouds, and there is a lack of automatic methods for measuring growth parameters. A point cloud intensity segmentation and improved Euclidean clustering method for single plant segmentation was proposed based on terrestrial laser scanning (TLS) technical, and an automatic measuring method of growth parameters of maize seedling stage was realized. First, TLS was used to scan maize plants at two planting densities at V1 (first leaf is fully expanded) and V2 (second leaf is fully expanded) stages. Second, the segmentation based on point cloud intensity method and the improved Euclidean clustering single plant segmentation method were used to achieve the segmentation of a single maize plant. Finally, the automatic measurement of maize plants counting, row spacing, plant spacing, and plant height were realized. When plants counting of maize, the percentage error was lower than 1.70%. In the measurement of row spacing, plant spacing and plant height of maize plants, the mean absolute percentage error (MAPE) were lower than 1.50%, 5.50% and 3.10%, respectively. These results demonstrate that the point cloud intensity segmentation and growth parameters measurement method is feasible for maize V1 and V2 stages and different planting densities. The automatic measurement values of the number of maize plants, row spacing, plant spacing and plant height has high measurement accuracy and small error. This study provides a rapid, automatic and accurate measurement method for researchers to measure maize growth parameters.

Vibration monitoring of rotating shafts using DIC and compressed sensing

Monitoring vibrations in rotating shafts is essential for diagnosing and detecting mechanical faults. Digital image correlation (DIC), an optical full-field measurement technique, is increasingly employed in experimental mechanics. This study introduces a novel measurement approach that combines DIC with compressed sensing to monitor high-speed rotating shafts accurately. Traditionally, analyzing rotating shafts requires high-speed sampling devices, which increases experimental costs and reduces spatial resolution. To overcome these limitations, a random exposure sampling method was developed to capture speckle images on the shaft surface with a low frame-rate camera. By leveraging compressed sensing and DIC, the method reconstructs high-speed vibration signals from captured images. Step motion experiments demonstrated that the DIC system achieves a measurement accuracy of 10 µm. Experimental validation was conducted using various setups, including low-speed motors, high-speed rotating shafts, and milling machines, demonstrating the effectiveness of the approach. The measurement results of rotating shafts at 1200 rpm and 6000 rpm, compared with those obtained from laser Doppler vibrometry, demonstrated the effectiveness of the method in vibration measurement. Additionally, experiments on a milling machine showed that vibrations reconstructed using compressed sensing closely matched those measured with a high-speed camera. This measurement system shows significant potential for accurately assessing vibrations in high-speed rotating shafts, offering valuable insights for machinery monitoring and fault diagnosis.

An seamless stitching method for large field equivalent center projection image based on rotating camera

Digital cameras are limited by a narrow field of view and a large photosensitive unit, resulting in images with a small frame size and low resolution. This reduces the acquisition range and measurement accuracy of stereo vision in close-range photogrammetry, making it difficult to meet the requirements for precise close-range photogrammetry in high-precision industrial engineering fields, and limiting the significant development of digital close-range photogrammetry. For this reason, based on the characteristics of ground close-range photogrammetry, this paper proposes a large-format image acquisition method for rotating cameras. By designing a simple and structurally relaxed rotating camera, a rigorous seamless stitching model for large-format images is constructed, forming a large-format equivalent central projection image acquisition mechanism that meets the requirements of precise close-range photogrammetry. Finally, the effectiveness of the proposed method is verified through experiments. The results show that the proposed method effectively increases the coverage of a single camera station. The large-format image obtained through three degrees of rotation increases the image size from 916 × 687 pixels in a single image to 4977 × 671 pixels in a large-format image. This method solves the problem of the small view field of digital cameras, complementing the theory of precision close-range photogrammetry and providing necessary theoretical support for technological development in the field of precision industrial engineering.

Online review based IPA and IPCA: the case of Korean mobile banking apps

PurposeThis study introduces a novel approach to conducting importance-performance analysis (IPA) and importance-performance competitor analysis (IPCA) by utilizing online reviews as an alternative to traditional survey-based marketing research.Design/methodology/approachIn order to conduct IPA and IPCA utilizing online reviews, the following three steps were executed: (1) Extract key attributes of the product/service with latent Dirichlet allocation (LDA) topic modeling. (2) Measure the importance of each attribute with keyword analysis. (3) Measure the performance of each attribute with KoBERT-based sentiment analysis.FindingsBy utilizing LDA, we were able to identify significant attributes identified by real users’ reviews. The approach of evaluating attribute importance using keyword metrics offers the advantage of straightforward computations, reducing computational expenses and facilitating intuitive metric assessments. The evaluation of BERT-based performance involved adapting pre-trained language models to the specific analysis domain, resulting in substantial time savings without compromising accuracy, ultimately bolstering the dependability of the metrics. Lastly, the case study’s findings indicate a growing emphasis on the aesthetic aspects of mobile banking apps in South Korea while highlighting the pressing need for enhancements in critical areas such as stability and security, which are particularly pertinent to the finance industry.Originality/valuePrevious studies have limitations in assessing significance solely based on sentiment scores and review ratings, resulting in an inability to independently measure satisfaction and importance metrics. This research addresses these limitations by introducing a keyword frequency-based importance metric, enhancing the accuracy and suitability of these measurements independently. In the context of performance measurement, this study utilizes pre-trained large language models (LLMs), which provide a cost-effective alternative to previous methods while preserving measurement accuracy. Additionally, this approach demonstrates the potential for industry-wide competitive analysis by enabling comparisons among multiple competitors. Furthermore, the study extends the application of review data-based IPA and IPCA, traditionally used in the tourism sector, to the evaluation of financial mobile applications. This innovation expands the scope of these methodologies, indicating their potential applicability across various industries.

A Data-Assisted and Inter-Symbol Spectrum Analysis-Based Speed Estimation Method for Radiated Signals from Moving Sources

Aiming at the problem of estimating the speed of M-ary Phase Shift Keying (MPSK) communication radiated sources and their carrying platform targets, this paper proposes a data-assisted and inter-symbol spectrum analysis-based speed estimation method for MPSK communication radiated sources. The method first demodulates a signal-carrying message symbol from the received MPSK signal; then segments the signal according to the symbol synchronization information and the symbol period; and then compensates the phase of the symbol waveform corresponding to the message data according to the demodulated message symbol; finally combines the phase-compensated symbol waveform data into a two-dimensional matrix and finds the Doppler frequency of the data at the same sampling moment of different symbols using the vertical Fourier transform to obtain the moving target speed. The speed measurement accuracy and anti-noise performance of the method are analyzed through simulation experiments, and the simulation results show that the speed measurement accuracy of the method is 98.5%.

Ultrasonic measurement of oil slick thickness using a remotely operated vehicle (ROV) as a platform in various sea wave states

To overcome the difficulty of estimating the oil slick thickness using remote sensing techniques, the feasibility of applying the proposed ultrasonic method for measuring the thickness of the oil slick in open water was experimentally investigated by conducting tests in various sea wave states. The second cross-correlation method was implemented to calculate the time of flight (TOF). The influences of sea waves on measurement accuracy were deeply evaluated by calculating the difference of the average thickness in the sea wave state compared with the average thickness in the calm sea state (no waves). The results showed a high measurement accuracy with a maximum difference ∼17.3%, and most of the tests (10 in 15) had a difference within ±10%. The measurement accuracy was further improved by correcting singular thicknesses caused by the ROV's pitch and roll, and surface waves. The study will advance the development and transition of this method to be implemented in open water.

Calibration of pressures measured via tubing systems: Accounting for laboratory environmental variations between tubing response measurement and wind tunnel testing

Accurate pressure measurements on structures via tubing systems during wind tunnel tests are crucial for precise estimation of wind loads. While calibration studies have traditionally focused on the contribution of tubing configuration to pressure distortion, they often overlook the effects of environmental parameter changes between the measurement of tubing response and aerodynamic pressure on structures. However, higher atmospheric pressure and lower ambient temperature can substantially increase tubing response distortion. To address this, this study introduces a dynamic calibration approach that accounts for such laboratory environmental changes. This method integrates the experimental transfer function, obtained under specific environmental conditions, with numerical estimates of the impact of environmental changes, to derive transfer functions for the desired environmental conditions. The effectiveness of this approach was validated using experimental and numerical transfer functions under two distinct environmental conditions. A case study for outdoor open-circuit laboratories revealed that neglecting environmental conditions during dynamic pressure calibrations could lead to overall average deviations in peak pressures across the channels on a building face of up to ≈ 5%, with local maximum deviations reaching ≈ 10%, respectively. Therefore, the proposed calibration method can significantly enhance the accuracy of pressure measurements via tubing systems, particularly when the tubing response and the pressures are measured under different environmental conditions.

Harmonics suppression in frequency domain for fringe projection profilometry with arbitrary phase shifts

In phase-shifting fringe projection profilometry, nonlinearities of the used devices affect measurement accuracy by induing harmonics in fringe signals. The resulting errors are manifested as ripple artifacts in the measured phase maps. Especially when phase shifts are not uniform, the error artifacts have unpredictable profiles and complicated frequency components thus being not easy to eliminate. To solve this problem, this paper suggests a method for suppressing effects of fringe harmonics when using arbitrary phase shifts. For doing it, this paper derives the frequency transfer function that explicitly represents the response of the phase-shifting algorithm to each order of fringe harmonics, and then uses this function to deduce a method that allows one to estimate the coefficients of harmonics from spectrum of the calculated complex fringe pattern. By iteratively subtracting off the estimated harmonics from the calculated complex fringe pattern, fringe phases are calculated accurately. Simulation and experimental results demonstrate that this method significantly suppresses the influence of fringe harmonics on measurement results and, simultaneously, it preserves edges and details of the measured object from being blurred.

Design and analysis of terrestrial laser scanner based on a 3-SPR parallel mechanism for improved anti-occlusion scanning

Abstract Laser scanner technology swiftly captures point cloud data of objects and their surrounding environments, proving extensive applications across various sectors. However, it often encounters challenges related to incomplete point clouds due to occlusion from stationary objects. This paper presents a terrestrial laser scanning system based on a 3-SPR (3-Spherical Joint-Active Prismatic Joint-Rotating Joint) parallel mechanism (TLS-PM), specifically designed to enhance scanning coverage during single-station measurements, reduce positioning and workload during multi-station measurements, and mitigate point cloud gaps caused by occlusions.
Initially, a simulation model of the TLS-PM was developed, and both forward and inverse kinematic analysis were performed. Subsequently, the workspace was computed for different spherical joints using this model. An introduction to the TLS-PM’s error and the registration algorithm employed was then provided. Finally, through comparative analysis of simulations and experimental results, the device's measurement accuracy and its capability to resist occlusions were validated. Additionally, the TLS-PM’s anti-occlusion performance was evaluated under various scenarios in a simulated setting. The experimental results demonstrate that, when employing the same conventional point cloud processing algorithms, the TLS-PM significantly improves the background scanning coverage.

Dynamic response and tension estimation of stay cables with disturbed images acquired from vision sensors

ABSTRACT This study introduces a novel approach to measure cable responses of such bridges using a vision sensor comprising a digital camcorder mounted on a tripod. Prioritizing simplicity and efficiency, this setup requires minimal equipment. The sensor is strategically positioned to ensure the target cable remains within the camcorder’s field of view. However, operational bridge imagery is frequently disturbed by vehicular traffic, leading to defocusing and blurring due to the camcorder’s automatic focus adjustments. These disturbances complicate the identification of reference points essential for accurate cable response measurements, potentially skewing results. To address this, we apply an image quality evaluation method to distinguish reference points from disturbed images, mitigating the impact of these disturbances on measurement accuracy. We evaluated the method’s effectiveness in estimating cable tension under disturbances by capturing images of an operational cable-stayed bridge experiencing ambient vibrations. Cable tension estimations were derived from the analysed responses using the vibration method and validated against data from a long-term monitoring accelerometer. This comparison highlights the potential of the proposed vision sensor method to enhance the accuracy of cable tension measurements in cable-stayed bridges, even in the presence of disturbed images.

A Versatile Gyro Inclinometer, Adaptive to the Borehole Trajectory, Based on a Uniaxial Angular Rate Sensor

Introduction. An approach to designing a gyroscopic inclinometer (GI) based on a single uniaxial angular rate sensor (ARS) is developed. It is argued that such an ARS should be considered a modification of a longitudinal GI scheme, preserving the well-known disadvantages of its performance characteristics. The latter include a lack of adaptability to the trajectory, i.e., commensurability of GI errors at different zenith angles. This work sets out to develop a scheme with one ARS in order to achieve a multiple increase in the accuracy of azimuth measurements for vertical and adjacent-to-the-vertical boreholes when the GI is operated in continuous mode.Aim. To make a GI based on a uniaxial angular velocity sensor more adaptive to the borehole trajectory thought its design modification and a comparative analysis of errors.Materials and methods. Algorithms for ideal operation of the proposed scheme in continuous mode are synthesized based on matrix transformations of coordinates and Euler equations. The properties of orientation errors are examined using linearization methods, integral calculus, fundamentals of the calculus of variations, and the theory of linear differential equations.Results. The adaptivity of the modified GI scheme to the borehole trajectory was achieved by means of a structurally provided deviation of the ARS sensitivity axis by a certain angle of non-orthogonality to the GI longitudinal axis. When designing a GI based on the developed approach, it is possible to realize the value of this angle of 20°. For this angle, the increase in the compassing error does not exceed the uncertainty of the ARS drift statistical characteristics, while achieving an effective level of adaptivity to the borehole trajectory in continuous mode.Conclusion. The developed scheme makes it possible to significantly reduce the influence of the ARS drift on the accuracy of azimuth calculation in the transitional zenith angles area (from vertical to directional boreholes) in comparison with the well-known longitudinal scheme, thereby maintaining an increased initial azimuth accuracy during movement in the initial alignment at the wellhead.