Measurement Range Research Articles

Design of optical fiber delay line with large delay range and low insertion loss

For the application of continuously adjustable optical fiber delay lines, a large delay range can increase the instrument’s measurement range. Increased insertion loss of components will reduce the signal-to-noise ratio of the collected signal, ultimately limiting the measurement accuracy of the instrument. In order to take into account both large delay range and low insertion loss in design, a spatial light transmission and fiber coupling model based on scalar diffraction theory was established and the insertion loss was equivalently calculated through the coupling efficiency of the coupling lens. Then, we analyze the impact of optical fiber delay line’s structural parameters and adjustment errors on coupling efficiency. By optimizing lens group parameters and limiting adjustment tolerances, we can reduce the insertion loss of optical fiber delay lines in a large delay range and conduct experimental verification. Considering various influencing factors, we use a lens group with a focal length of 12 mm, achieving a coupling efficiency of no less than 92.7% within the delay range of 0–1 m. This theoretical model provides a new quantitative analysis method for improving the performance of the optical fiber delay line.

A Method for Reconstruction of Size Distributions from 3D Drone Image Analysis: A Case Study

AbstractThis paper describes a novel procedure to assess fragmentation from automatic analysis of 3D photogrammetric models with a commercial software. The muckpiles from 12 blasts were photographed with a conventional drone to build 3D photogrammetric models; the flights were made with a relatively constant ground sampling distance (GSD) of 6.2 sd 0.92 mm (mean and standard deviation, respectively). A comparison with already published mass-based size distributions from 11 of these blasts, shows a good performance of automatic 3D-fragmentation measurements in the coarse range (P ≥ 60%), while deviations between mass-based and 3D model fragmentation analysis grow towards the central-fines range. As a solution, the Swebrec function is fitted to the reliable part of the size distributions, well above the GSD, and then is extended towards the fines, down to a percentage passing of 5–10%. The suitable fitting range is obtained iteratively from the mass-based fragmentation data; the lower fragment size considered is independent of the model’s resolution (i.e. GSD) with mean of 357 mm (equivalent to a passing in the range 66–86%, and well above the GSD of our models). The resulting distributions match properly mass-based size distributions with relative errors in percentile sizes of 15.5 sd 3.4%, and they can be represented with the simplest form of the fragmentation-energy-fan. As a guideline for reconstruction of size distributions and fines assessment when mass-based data is not available, the lower-fitting limit of 357 mm yields reasonable results (mean errors in pass in the range 5–36%) for the present case. The errors are limited enough to keep a sound description of the variation of fragmentation with change in blast design.

A Bayesian nonparametric meta-analysis model for estimating the reference interval.

A reference interval represents the normative range for measurements from a healthy population. It plays an important role in laboratory testing, as well as in differentiating healthy from diseased patients. The reference interval based on a single study might not be applicable to a broader population. Meta-analysis can provide a more generalizable reference interval based on the combined population by synthesizing results from multiple studies. However, the assumptions of normally distributed underlying study-specific means and equal within-study variances, which are commonly used in existing methods, are strong and may not hold in practice. We propose a Bayesian nonparametric model with more flexible assumptions to extend random effects meta-analysis for estimating reference intervals. We illustrate through simulation studies and two real data examples the performance of our proposed approach when the assumptions of normally distributed study means and equal within-study variances do not hold.

Machine-Learning-Assisted Instantaneous Frequency Measurement Method Based on Thin-Film Lithium Niobate on an Insulator Phase Modulator for Radar Detection.

A simple microwave photonic, reconfigurable, instantaneous frequency measurement system based on low-voltage thin-film lithium niobate on an insulator phase modulator is put forward and experimentally demonstrated. Changing the wavelength of the optical carrier can realize the flexibility of the frequency measurement range and accuracy, showing that during the ranges of 0-10 GHz, 3-15 GHz, and 12-18 GHz, the average measurement errors are 26.9 MHz, 44.57 MHz, and 13.6 MHz, respectively, thanks to the stacked integrated learning models. Moreover, this system is still able to respond to microwave signals of as low as -30 dBm with the frequency measurement error of 62.06 MHz, as that low half-wave voltage for the phase modulator effectively improves the sensitivity of the system. The general-purpose, miniaturized, reconfigurable, instantaneous frequency measurement modules have unlimited potential in areas such as radar detection and early warning reception.

Enhancing Smart Irrigation Efficiency: A New WSN-Based Localization Method for Water Conservation

The shortage of water stands as a global challenge, prompting considerable focus on the management of water consumption and irrigation. The suggestion is to introduce a smart irrigation system based on wireless sensor networks (WSNs) aimed at minimizing water consumption while maintaining the quality of agricultural crops. In WSNs deployed in smart irrigation, accurately determining the locations of sensor nodes is crucial for efficient monitoring and control. However, in many cases, the exact positions of certain sensor nodes may be unknown. To address this challenge, this paper presents a new localization method for localizing unknown sensor nodes in WSN-based smart irrigation systems using estimated range measurements. The proposed method can accurately determine the positions of unknown nodes, even when they are located at a distance from anchors. It utilizes the Levenberg–Marquardt (LM) optimization algorithm to solve a nonlinear least-squares problem and minimize the error in estimating the unknown node locations. By leveraging the known positions of a subset of sensor nodes and the inexact distance measurements between pairs of nodes, the localization problem is transformed into a nonlinear optimization problem. To validate the effectiveness of the proposed method, extensive simulations and experiments were conducted. The results demonstrate that the proposed method achieves accurate localization of the unknown sensor nodes. Specifically, it achieves 19% and 58% improvement in estimation accuracy when compared to distance vector-hop (DV-Hop) and semidefinite relaxation-LM (SDR-LM) algorithms, respectively. Additionally, the method exhibits robustness against measurement noise and scalability for large-scale networks. Ultimately, integrating the proposed localization method into the smart irrigation system has the potential to achieve approximately 28% reduction in water consumption.

Study on Grid-Connected Power Quality Improvement of Wind Farms Based on Repetitive Controller

The project highlights the wind energy and the process followed in the wind farms in order to generate the energy by using wind power and wind capacity as well. Moreover, it has been observed that wind energy is also considered one of the most effective electrical energy sources. The application of wind energy can be beneficial for different aspects of the business sectors of different countries across the globe and this is possible because of its cost-effectiveness. Furthermore, this study encompasses the strategies employed within wind farms to preserve and efficiently harness wind power for the generation of electrical energy. Notably, the project delineates the utilization of a diverse array of instruments, each instrumental in the conversion of wind power into valuable wind energy. Beyond the realm of technology, wind farms grapple with a spectrum of formidable challenges, stemming from the inherently capricious nature of wind. In addition, various issues concerning power quality and the stability of the power system have also been identified within these wind farms. To ameliorate these multifaceted challenges, the project introduces a range of meticulous control measures for implementation.

Perinatal anxiety disorders screening study: a study protocol

BackgroundThe anxiety and their related disorders (AD) are the most common of all mental health conditions, and affect approximately 20% of pregnant and postpartum people. They are associated with significant distress and life interference for sufferers, as well as negative consequences for fetal and infant development. At present, little if any routine screening for prenatal AD is being conducted and data regarding the most effective tools to screen for these disorders is lacking. The majority of screening studies suffer from methodological difficulties which undermine the confidence needed to recommend measures for population distribution. The primary purpose of this research is to identify the most accurate self-report tool(s) to screen for perinatal AD.MethodsA large, prospective cohort of pregnant people (N = 1,000) is being recruited proportionally across health service delivery regions in British Columbia (BC). The screening accuracy of a broad range of perinatal AD self-report measures are being assessed using gold standard methodology. Consenting individuals are administered online questionnaires followed by a semi-structured diagnostic interview between 16- and 36-weeks’ gestation, and again between 6 and 20 weeks postpartum. Questionnaires include all screening measures, measures of sleep and unpaid family work, and questions pertaining to demographic and reproductive history, COVID-19, gender role burden, and mental health treatment utilization. Interviews assess all current anxiety disorders, as well as obsessive–compulsive disorder, and posttraumatic stress disorder.DiscussionThis research is in response to an urgent demand for accurate perinatal AD screening tools based on high quality evidence. AD among perinatal people often go unidentified and untreated, resulting in continued suffering and life impairment. Findings from this research will inform healthcare providers, policymakers, and scientists, about the most effective approach to screening for anxiety and related disorders in pregnancy in the postpartum period.

Investigation of the Influence of Data Collection and Analysis Procedures on Aerosol Filtration Model Development

Fibrous air filters are common devices used to remove airborne particles. Their performance is typically measured through their resistance to airflow and captured particle mass. Models describing the evolution of filter performance have been heavily researched; however, the need for improvement remains. Experimental work is irreplaceable in the development of high-fidelity models, yet the estimation of necessary variables is not trivial and may be influenced by selected measurement instruments and analysis methodologies. Therefore, the purpose of this work is to propose a framework to investigate the response of common aerosol measurement instruments, their corresponding analysis methodologies, and the application of their data. A Scanning Mobility Particle Sizer (SMPS) and Laser Aerosol Spectrometer (LAS) were selected for consideration, and their recorded data were compared against baseline measurements. The results of the experiments indicated that the SMPS and LAS yielded a ratio of estimated mass concentrations to the baseline mass concentrations of approximately 1.175 and 0.749, respectively. Regarding the SMPS, it was suggested that the measurable size range, application of a coverage factor, dynamic shape factor, and association between the curve fits and histograms were influential in the final estimates. For the LAS, the application of a curve fit, its association to the histograms, and the selection of the sampling periods were influential. Considering the results, the impact of these factors may not be considered negligible and may skew reproducibility between studies and fossilize confounding factors. Therefore, the proposed methodologies are useful in addressing potential errors in data collection and analysis.

Double Asteroid Redirection Test (DART): Navigating to obliteration

DART is NASA’s demonstration of an asteroid deflection using a kinetic impactor. The spacecraft launched aboard a SpaceX Falcon 9 on November 24th 2021, on a direct collision with the binary asteroid system Didymos planned for September 26th 2022. By impacting the small moon, Dimorphos, DART’s objective was to alter the moon’s orbit about the larger asteroid by several minutes.The navigation of a ballistic mission is usually relatively simple. Other than heading to a violent demise, this mission had a number of unconventional aspects which gave the navigation team interesting challenges: a tight propellant budget for part of the mission, no reaction wheels which resulted in a noisy spacecraft with the Nav team having to rely heavily on Delta Differential One-way Ranging measurements to identify off line-of-sight Delta-V, and critical operations in the last 30 days of the mission under a new thrusting control mode regime. Optical navigation was a critical element in the success of this mission, contributing to the determination of the spacecraft and target ephemerides for refined targeting maneuvers. After strategic decisions in the final weeks of the missions, DART could have comfortably hit the larger asteroid, Didymos, which increased the probably of impact with its moon Dimorphos.

An investigation of the on-board microwave radiometer of satellite Altimetry for studying the atmosphere variability

Since its first launching, the ability of satellite Altimetry in providing reliable and accurate ocean geophysical information of the sea surface height (SSH), significant wave height (SWH), and wind speed has been proven by numerous researchers, as it was designed for observing the ocean dynamics through nadir range measurement between satellite and the sea surface. However, to achieve high level accuracy, environmental and geophysical effects on the range measurement must be accurately determined and corrected, particularly the effects from the atmospheric water vapor which can divert altimeter range up to 3–45 cm. Thus, satellite Altimetry is originally equipped with the on-board microwave radiometer to measure the water vapour content for correcting the range measurement. To our knowledge, no one has attempted to apply the on-board radiometer for atmospheric studies. In this present work, we attempt to optimize the on-board radiometer data for studying the atmosphere variability due to the El Niño–Southern Oscillation (ENSO) phenomena. We convert the on-board water vapor data into the precipitable water vapour (PWV), and we then investigate whether the derived PWV can capture the variability of ocean–atmosphere phenomena due to ENSO as accurate as the conventional Altimetry-derived sea level anomaly (SLA). Based on our analysis using the empirical orthogonal function (EOF), the results show convincing argument that Altimetry-derived PWV are reliable in examining the atmospheric fluctuation as the correlation of its primary principal component time series (PC1) with Oceanic Nino Index (ONI) is higher (0.87) than SLA (0.80). These results may reinforce the confidence in the ability of satellite Altimetry for ocean–atmospheric studies.Graphical

The Assessment of PM2.5 and PM10 Immission in Atmospheric Air in a Climate Chamber during Tests of an Electric Car on a Chassis Dynamometer

Electric cars, like internal combustion vehicles, emit particulate pollution from non-exhaust systems, i.e., tires and brakes, which is included in the Euro 7 emission standard planned for implementation. Tests conducted on chassis dynamometers are accompanied by particulate emissions from non-exhaust systems, which are introduced into the ambient air on the test bench. Particulate emissions tests from non-engine systems on chassis dynamometers are mainly aimed at measuring the mass or number of particulates from tires and brakes. In contrast, little attention is paid to the immission of particulate matter from tires and brakes on the dynamometer during tests, which in the case of electric cars include, for example, measurements of energy consumption or range. Therefore, in order to draw attention to the problem of these emissions, the authors carried out measurements of PM2.5 and PM10 immissions into the air in the climatic chamber during tests of an electric car on a chassis dynamometer. The car tests were carried out in accordance with the WLTC (Worldwide harmonized Light duty Test Cycle) and at constant speed. Based on the test results, a model was proposed for the immission of particulate matter in laboratory air from tire and brake abrasion, taking traffic parameters into account. The results and the developed model show that air quality, in terms of particulate content, deteriorates significantly during testing.

GRVINS: Tightly Coupled GNSS-Range-Visual-Inertial System

Bridge inspection is currently a labor intensive task. Utilizing unmanned aerial vehicles (UAVs) to assist in inspection tasks is a promising direction. However, enabling UAVs for autonomous inspection involves the UAV state estimation problems. Since parts of UAV sensors could be unavailable, how to estimate states via sensor fusion is the key. In this paper, we propose a tightly-coupled nonlinear optimization-based system that integrates four kinds of sensors: camera, IMU, Ultra-wideband (UWB) range measurements, and global navigation satellite system (GNSS). Due to the tightly-coupled multi-sensor fusion method and system design, the system takes the advantage of the four sensors, and can seamlessly respond to indoor and outdoor GNSS and UWB loss or reacquisition. It can effectively reduce the long-term trajectory drift and provide smooth and continuous state estimation. The experimental results show that the proposed method outperforms the state-of-the-art approaches.

Indoor Environmental Quality In Preschool Buildings In an Andean City In Ecuador

ABSTRACT Indoor environmental quality has been associated with the health and wellbeing of building occupants; nevertheless, there is limited evidence in this regard for Latin American schools. This research aimed to characterize indoor environmental quality in public and private preschools in an Andean city in Ecuador. Data collection comprised onsite monitoring for the thermal-humidity microclimate of 90 classrooms in 30 preschools in Cuenca-Ecuador (March-August 2018). Infrared thermography and direct observation were applied to determine dampness. Classrooms seemed to be inadequate thermal-humidity microclimates; only a few maintained a comfortable temperature (6%) and relative humidity (11%) throughout the shift. When comparing public and private schools, in private schools, temperatures below the comfort range (61.3% in private schools vs 31.4% in public schools, p<0.001) and relative humidity measures above the comfort range were more frequent (74.3% in private schools vs. 58.6% in public schools, p<0.001). Hollow blocks were the primary construction material in private and public schools. Sixty-four per cent of private schools operated in adaptive, reused buildings, vs 19% in public schools (p<0.05). Infrared thermography confirmed dampness in 26% (n=23) of the classrooms in the covering structures indoors (15% in public vs 33% in private schools, p<0.05). This research reveals the urgent need to develop specific regulations and control mechanisms for building sustainable and healthy environments for preschools in Ecuador.

Non-Destructive Thin Film Thickness Measurement based on Coplanar Capacitive Sensor and Printed Circuit Board Platform

This paper presents a compact design of a coplanar capacitive sensor based on a printed circuit board (PCB) to apply in non-contact and non-destructive thin film thickness measurement. The capacitive sensor design is structured by two coplanar capacitors, including a reference coplanar capacitor and a sensing coplanar capacitor. Using this structure, the thin film thickness could be estimated through the imbalance voltage produced between the two signals from the reference capacitor and sensing capacitor. The size of the proposed sensor is 9.99 × 9.99 mm and the capacitor electrodes structured by shapes of spiral, interdigital, and round are studied and optimized. Those electrode structures have been modelled and simulated and the simulation results reveal that the spiral structure gives the best performance. The experiment was conducted using plastic thin films with thickness ranging from 10 to 230 µm and dielectric constants ranging from 1.375 to 3.19 to investigate the working principle of the sensor. Experiment results show the approximate linearity of the output voltage corresponding to the various thickness at measurement range from 0 to 90 µm. The sensitivity of the sensor is 13.5 and 29 mV/µm corresponding to the 1.375 and 3.19 dielectric constants of the thin films, respectively. The proposed coplanar capacitive sensor is fabricated based on the PCB platform and shows good performance with a minimum cost. The experiment results demonstrate that this sensor has a high potential to be applied in several biomedical and industrial thin film thickness measurement applications.

Group-based positive psychotherapy for people living with acquired brain injury: a protocol for a feasibility study

BackgroundAcquired brain injury (ABI) and other chronic conditions are placing unprecedented pressure on healthcare systems. In the UK, 1.3 million people live with the effects of brain injury, costing the UK economy approximately £15 billion per year. As a result, there is an urgent need to adapt existing healthcare delivery to meet increasing current and future demands. A focus on wellbeing may provide an innovative opportunity to reduce the pressure on healthcare services while also supporting patients to live more meaningful lives. The overarching aims of the study are as follows: (1) evaluate the feasibility of conducting a positive psychotherapy intervention for individuals with ABI and (2) ascertain under what conditions such an intervention would merit a fully powered randomised controlled trial (RCT) compared to a standard control group (TAU).Methods and analysisA randomised, two-arm feasibility trial involving allocation of patients to either a treatment group (positive psychotherapy) or control group (treatment as usual) group, according to a 1:1 ratio. A total of 60 participants at three sites will be recruited including 20 participants at each site. Assessments will be conducted at baseline, on completion of the 8-week intervention and 3 months following completion. These will include a range of questionnaire-based measures, psychophysiology and qualitative outcomes focusing on feasibility outcomes and participant experience. This study has been approved by the Wales Research Ethics Committee (IRAS project ID: 271,251, REC reference: 19/WA/0336).DiscussionThis study will be the first to examine the feasibility of an innovative, holistic positive psychotherapy intervention for people living with ABI, focused on individual, collective and planetary wellbeing, and will enable us to determine whether to proceed to a full randomised controlled trial.Trial registrationISRCTN12690685, registered 11th November 2020.

High resolution and large measurement range voltage sensing based on an optoelectronic oscillator utilizing an unbalanced Mach-Zehnder interferometer.

A voltage sensor with high resolution and large measurement range based on an optoelectronic oscillator (OEO) is proposed and experimentally demonstrated. The key component in the cavity to select the oscillating signal is a finite impulse response (FIR)-microwave photonic filter (MPF) which consists of a sinusoidal broadband optical signal, an unbalanced Mach-Zehnder interferometer (MZI), a section of dispersion compensating fiber, and a photodetector. The center frequency of the FIR-MPF is mainly determined by the free spectral range (FSR) of the FIR-MPF. In the lower arm of the MZI, a cylindrical piezoelectric ceramic (PZT) wrapped with a section of optical fiber acts as voltage sensing head. Due to the inverse piezoelectric effect of PZT, the variation of the voltage will cause radial deformation of the cylindrical PZT and then lead to the change of the FSR of the MZI, determining the shift of center frequency of FIR-MPF as well as the frequency of the oscillating signal of the OEO. Thus, by monitoring the shift of the oscillation frequency of the OEO using an electric spectrum analyzer or a digital signal processor, a high-speed interrogation and high-resolution voltage measurement can be realized. Additionally, in the proposed scheme, an infinite impulse response (IIR)-MPF consisting of a fiber ring resonator is cascaded with the FIR-MPF to ensure the single-mode oscillation of the OEO. The experimental results show that a total range of 1700 V voltage sensing from - 200 V to 1500 V is accomplished with the voltage sensitivity of 0.25 GHz/100 V and the resolution of 0.3 V. By adjusting the proportion of the length of single mode fiber between two branches of MZI, the impact of temperature can be greatly reduced. The proposed sensor offers advantages such as a large measurement range, high resolution, high-speed interrogation, and stability to temperature disturbances, making it highly suitable for sensing applications in smart grids.

Reliability and construct validity of the ACTIVLIM-Hemo and Haemophilia Activities List (HAL) questionnaires in individuals with haemophilia.

The objective of this study is to assess the reliability and construct validity of ACTIVLIM-Hemo, a newly developed Rasch-built questionnaire designed to evaluate activity limitations in people with haemophilia (PwH), in comparison with the Haemophilia Activities List (HAL), which was developed using Classical Test Theory. A total of 130 participants with haemophilia A or B were included. They underwent various assessments, including joint health scoring (HJHS), functional tests (TUG and 2MWT) and completed questionnaires such as the BPI, IPAQ, HAL and ACTIVLIM-Hemo. Reliability indices and the minimum detectable change (MDC95) were determined for ACTIVLIM-Hemo and for HAL. Construct validity was evaluated through correlations and multiple linear regression, considering demographic and clinical factors. Both ACTIVLIM-Hemo (Person Separation Index=0.92) and HAL (Cronbach's α=0.98) demonstrated high reliability. The MDC95 for ACTIVLIM-Hemo represented 11.6% of its measurement range, while for HAL, it amounted to 18/100 score points. Activity limitations measured by both instruments were significantly correlated with demographic and clinical factors. Joint health (HJHS), pain severity (BPI) and walking performance (2MWT) emerged as the main predictors of activity limitations, explaining 75% of the variance in ACTIVLIM-Hemo and 60% in HAL. ACTIVLIM-Hemo stands as a reliable and valid instrument for assessing activity limitations in PwH. Both instruments exhibited significant correlations with demographic and clinical factors, but ACTIVLIM-Hemo displayed a more homogeneous construct. Given its linear scale and lower MDC95 and better targeting, ACTIVLIM-Hemo shows promise as a patient-centric instrument for assessing responsiveness to treatment during individual follow-up.

Language Acquisition in the Longitudinal Cambridge UK BabyRhythm Cohort

The Cambridge UK BabyRhythm project is a study of 122 infants as they age from 2 – 30 months, investigating cortical tracking and sensorimotor synchronisation to acoustic and visual rhythm in relation to language acquisition. As there are few standardised language tasks appropriate for this age range, the BabyRhythm project adapted a range of parent-report and infant-led experimental measures that could be used within a home testing environment. Here we present a rich description of infant performance on tasks intended to sample 5 linguistic domains: semantics, phonology, grammar, rhythmic timing and gesture. For each task we describe infant performance (mean, median, range), and we also report performance by sex (N female = 57) and by monolingual (N = 91) versus multilingual (N = 31) home environments. We report relations between measures. We share our unique longitudinal database (all data available on OSF), and ‘lessons learned’ on adapting language assessments for very young children. Critically, we identify the language tasks that will be utilised in our longitudinal brain-behaviour analyses, providing the benchmark upon which future neural and behavioural markers will be measured.

Environmental enrichment promotes adaptive responding during tests of behavioral regulation in male heterogeneous stock rats

Organisms must regulate their behavior flexibly in the face of environmental challenges. Failure can lead to a host of maladaptive behavioral traits associated with a range of neuropsychiatric disorders, including attention deficit hyperactivity disorder, autism, and substance use disorders. This maladaptive dysregulation of behavior is influenced by genetic and environmental factors. For example, environmental enrichment produces beneficial neurobehavioral effects in animal models of such disorders. The present study determined the effects of environmental enrichment on a range of measures related to behavioral regulation using a large cohort of male, outbred heterogeneous stock (HS) rats as subjects. Subjects were reared from late adolescence onwards either in pairs in standard housing with minimal enrichment (n = 200) or in groups of 16 in a highly enriched environment consisting of a large multi-level cage filled with toys, running wheels, and shelters (n = 64). Rats were subjected to a battery of tests, including: (i) locomotor response to novelty, (ii) light reinforcement, (iii) social reinforcement, (iv) reaction time, (v) a patch-depletion foraging test, (vi) Pavlovian conditioned approach, (vii) conditioned reinforcement, and (viii) cocaine conditioned cue preference. Results indicated that rats housed in the enriched environment were able to filter out irrelevant stimuli more effectively and thereby regulate their behavior more efficiently than standard-housing rats. The dramatic impact of environmental enrichment suggests that behavioral studies using standard housing conditions may not generalize to more complex environments that may be more ethologically relevant.

Pose Measurement Method Based on Machine Vision and Novel Directional Target

Aiming at the shortcomings of the existing machine vision pose measurement technology, a pose measurement method based on monocular vision and a cooperative target is proposed. A planar target designed with circles and rings as the main body is dedicated to object pose measurement, and a feature point coordinate extraction and sorting algorithm is designed for this target to effectively extract image features on the target. The RANSAC algorithm and topology-based fitting for the intersection method are used to optimise data processing, further improving the accuracy of feature point coordinate extraction and ultimately achieving high-precision measurement of object poses. The experimental results show that the measurement accuracy of the roll angle perpendicular to the optical axis can reach 0.02°, and the repeatability can reach 0.0004° after removing the systematic error; the measurement accuracy of the pitch angle can reach 0.03°, and the repeatability can go to 0.002° after removing the systematic error. The measurement range of the pitch angle is [−30°, +30°]; the measurement range of the roll angle is [−179°, +179°]. The experimental results show that the system has high measurement accuracy and meets the requirements of high-precision measurement.