Accurate Measurement Method Research Articles

Suppression for Phase Error of Fringe Projection Profilometry Using Outlier-Detection Model: Development of an Easy and Accurate Method for Measurement

Fringe projection is an important technology in three-dimensional measurement and target recognition. The measurement accuracy depends heavily on the calibration of the absolute phase and projector pixels. An easy-to-implement calibration method based on the Random Sample Consensus (RANSAC) algorithm is proposed to exterminate the phase error data and elevate the measurement accuracy in a fringe projection system. The reconstruction experiments of a double-sphere standard demonstrate that the uncertainties in radius and sphere-distance measurement are reduced to one thousandth of the measured value or even less, and the standard deviation in multiple measurements is restricted to within 50 μm. The measurement accuracy provided by the proposed RANSAC method can be improved by up to 44% compared with that provided by traditional least squared method (LSM). The proposed calibration method is easy and simple to implement, and it does not need additional hardware, but rather a calibration board.

Design and application of soft sensors in rural sewage treatment facilities

Abstract Recently, with the growing demand for water quality monitoring, soft measurement sensors have drawn public attention, which can overcome the drawbacks of high cost and long time needed in traditional measurement methods. In this study, a machine learning-based soft monitoring sensor was developed to simultaneously monitor four water quality indicators including COD, NH4+-N, NO3--N, PO43--P. Firstly, specialized experimental equipment and calibration methods were developed to generate a matching dataset that collected over 94,000 data points. Secondly, five models including Multiple Linear Regression, Ridge Regression, AdaBoost, Decision Tree Regression, and Bagging Regression were constructed and compared. The learning accuracy of the models ranged from 0.8860 to 0.9999, among which the predicted value of Bagging Regression is highly fit to the true value. Subsequently, the fuzzy grade method was adopted to reduce the prediction error and strike a balance between efficiency and accuracy. Finally, the designed soft sensor was used for real-time monitoring at three monitoring points in Changzhou, China from September to October 2020, and the results proved the feasibility of the soft sensor in practical application. This study provided a fast and accurate method for water quality measurement, which is of great significance for the management of rural sewage treatment facilities.

A spherical neutron long counter for 4[formula omitted] neutron detection in the energy range of 0.01 eV to 20 MeV

Neutron detection using a long counter is the most commonly used method for accurate neutron flux measurement. It is desirable to design a long counter with a flat energy response and a consistent angular response. This requires counters to have neutron-energy-independent efficiency over a wide range of energies and a very slight dependence on the direction of neutron incidence in the 4π space. In this work, we designed a spherical neutron long counter using the Monte Carlo method, with a model consisting of a polyethylene ball, built-in air rings, and boron carbide material. The internal air rings enhance the energy response of thermal neutrons, spherical polyethylene improves the energy response of fast neutrons, and boron carbide material solves the problem of high local neutron energy response. We analyzed the energy response, angular response, and detection efficiency of long counters using neutron sources such as Pu–Be and Am–Be. The results show that the neutron energy response is relatively flat in the energy region of 0.01 eV to 20 MeV, the angular response is consistent in 2π space, and the maximum relative angular response deviation in 4π space is no more than 16.5%. We focus on the applicability of long counters in complex neutron fields, such as scattered neutron fields, and provide a reference for their use of long counters in neutron detection.

Multi-scale conditional diffusion model for deposited droplet volume measurement in inkjet printing manufacturing

The volume consistency of deposited droplets is regarded as a core quality evaluation to achieve zero-defect manufacturing (ZDM) in inkjet printed organic light-emitting diode (OLED). In order to improve the product quality, the causal links between printing defects and its causes should be determined. However, the collection of the defects quantified data remains a challenge due to the micrometer scale and few texture features of droplets. In this paper, an accurate measurement method for deposited droplets based on coherence scanning interferometry (CSI) is proposed. Firstly, time series signals for topography reconstruction are recorded when CSI scans droplets vertically at a constant speed. Then, a deep learning method, multi-scale conditional diffusion model (MS-CDM), is proposed to restore the time series signals’ distortions led by the chromatic dispersion. Furthermore, a self-supervised learning method is proposed to efficiently train the MS-CDM, since the labeled data is hard to be acquired in industrial environment. Finally, the printing experiment indicates the collaboration of different modules in intelligent close-loop to reduce Mura defects. The volume measurement experiments demonstrate the ability to accurately measure the volume of deposited droplets, and the measurement error reaches 1.3%. The performance experiment on several public datasets demonstrates the method’s promising feature representation ability for time series mainstream task, and the MS-CDM achieves the best performance compared to those baselines methods.

Wide field 3D optical profilometry using a diffraction Lloyd's mirror interferometer.

Interference fringe projection is used as a non-contact optical profilometry method for accurate 3D measurements. In interferometric fringe projection schemes, the maximum measurable size of the test object is limited by the optics of the interferometer. In this work, we report the application of a diffraction Lloyd's mirror interferometer (DLMI) as a wide-field sinusoidal fringe projection system for 3D shape measurement. The DLMI works on diffracted light and therefore generates interference fringes over a large area. This enables measurement of large objects using DLMI as compared to a conventional Lloyd's mirror interferometer. The performance of the proposed system is evaluated in terms of its stability and reproducibility of the results through measurement of the standard deviation in the phase values.

Automated Disease Severity Measurement Using Image Processing

Apple orchards are vital to the agricultural industry, but they face constant threats from diseases like apple scab, powdery mildew, rust, and rot. Traditional methods for measuring disease severity in apple leaves are labour-intensive, subjective, and prone to errors, limiting their practicality for large-scale agriculture. This paper introduces an innovative approach leveraging image processing techniques to automate disease severity measurement in apple leaves, offering a transformative solution for orchard management. The research aims to provide an efficient and accurate method for assessing disease severity, addressing the critical need for precise disease management and improved crop yields. Current methods relying on visual inspections by human experts are inefficient and unreliable. In contrast, the proposed method automates the measurement process, saving time and resources, enabling frequent monitoring, and enhancing early disease detection. This automation, in turn, leads to more effective disease management and increased crop yield and quality. The methodology involves image preprocessing, grayscale conversion, histogram equalization, thresholding, and defect area extraction, ultimately resulting in a quantitative disease severity index. The study utilizes a diverse dataset of apple leaf images, allowing for robust model development capable of accurate disease detection under varying conditions. This research holds significant implications for disease management and crop yield optimization, with broader applicability across agriculture. It paves the way for precision agriculture by enabling data-driven decisions on disease control measures while reducing the environmental impact of chemical inputs. Furthermore, the image processing techniques developed here can be adapted to other crops and plant diseases, promising efficient and accurate disease severity measurement methods across agricultural domains.

Device-Measured Sleep Duration Age 9–11 Years Among Urban Korean Children

Objective: Sleep duration measurement methods are expensive and inconvenient. Smart bands or wearable activity trackers have offered objective and continuous tracking over several nights in real-world conditions. This study explored device-measured sleep duration in Korean children aged 9–11 years old. Methods: This cross-sectional study, conducted between October 2022 and March 2023, enrolled 72 participants aged 9–11 years and equipped with smart bands (Xiaomi Mi Smart Band 6) for several nights lasting more than 5 days, including weekends. Sleep duration and sleep onset time were obtained using the smart bands. Results: Seventy-one children (43 girls, 28 boys), with a mean age of 9.92±0.73 were included. Sleep durations on weekdays and weekends did not show a significant difference (8.55±0.66 h vs. 8.76±0.72 h). However, significant difference was observed in sleep onset time between weekdays and weekends (p<0.001). The sleep duration on weekdays and weekends declined with age. The sleep duration on weekdays and weekends was similar in each age group; however, the sleep onset time significantly differed for all age groups (p<0.05). Conclusion: This study suggests insufficient sleep duration among the children in this study. And digital device may be an effective and fast way to evaluate children without a sleep laboratory, and suggest the need for further research to understand their implications and develop more accurate measurement methods for understanding children’s sleep.

Toward Citizen Science-Based Ocean Acidification Observations Using Smartphone Devices.

pH is a key parameter in many chemical, biological, and biogeochemical processes, making it a fundamental aspect of environmental monitoring. Rapid and accurate seawater pH measurements are essential for effective ocean observation and acidification investigations, resulting in the need for novel solutions that allow robust, precise, and affordable pH monitoring. In this study, a versatile smartphone-based environmental analyzer (vSEA) was used for the rapid measurement of seawater pH in a field study. The feasibility of the use of the vSEA algorithm for pH quantification was explored and verified. When used in conjunction with a three-dimensional (3D)-printed light-proof shell, the quality of captured images is guaranteed. The quantitative accuracy of vSEA pH measurements reached 0.018 units with an uncertainty of <0.01, meeting the requirements of the Global Ocean Acidification Observing Network (GOA-ON) for "weather" goals (permitting a maximum pH uncertainty of 0.02). The vSEA-pH system was successfully applied for on-site pH measurements in coastal seawater and coral systems. The performance of the vSEA-pH system was validated using different real-world samples, and t-test results showed that the vSEA-pH system was consistent with pH measurements obtained using a state-of-the-art benchtop spectrophotometer (t = 1.986, p = 0.7949). The vSEA-pH system is applicable to different types of smartphone devices, making it possible for vSEA-pH to be widely promoted for public citizen use. The vSEA-pH system offers a simple, accurate, and applicable method for the on-site measurement of seawater pH, assisting the large-scale monitoring of ocean acidification by allowing the contribution of citizen science-based data collection.

Density and surface tension measurements of molten Al–Si based alloys

AbstractThis study is part of a series of studies aimed at measuring the thermophysical properties of molten phase change material-type metallic thermal energy storage materials near 873 K (600°C). The target material is Al–Si based alloys. First, as a feasibility study, density measurements of the molten state of three Al–Si binary alloys (Al–12.2Si, Al–50Si and Al–90Si in atomic%) were performed. A highly accurate non-contact density measurement method based on the static magnetic field superposition electromagnetic levitation (EML) method was employed as the density measurement method. The validity of this experimental method was confirmed, and density of molten Al–Si base alloys (ADC12 and Al–5.9mass%Si–1.6mass%Fe) were measured as a function of temperature with an expanded uncertainty of 1.2%. In addition, the surface tension of the alloys was measured by the droplet oscillation method using the EML technique. The surface tension was successfully obtained as a function of temperature with expanded uncertainty of 2.3%.

A Special Robot for Precise Grading and Metering of Mushrooms Based on Yolov5

In order to accomplish accurate mushroom classification and measurement, it is necessary to optimize the existing classification algorithm and measurement devices, as well as to design a specific robot to improve classification accuracy and measurement efficiency. In order to achieve the above objectives, a research-level verification of mushroom grading using Yolov5 + OpenCV and a mushroom measuring system using a resistance strain gauge sensor was carried out. In the aspect of mushroom grading, a method based on the OpenCV visual library was used to identify the minimum quadrilateral outside the mushroom contour, allowing the size of the mushroom to be measured. The experiment’s results show that the method can assess target objects that are occluded with each other under different illumination conditions with 96% accuracy. In the measurement of mushrooms, the strain of the resistance is converted into an analog signal, and the weight of different grades of mushrooms is converted according to the linear relationship after processing by the detection circuit module. Through this method, the error range is successfully controlled within ±0.02 kg, which meets the requirements of accurate measurement of mushrooms. The results of field experiments show that the proposed accurate grading and measurement method of Lentinula edodes is effective and feasible, and provides technical support for the intelligent grading and measurement of Lentinula edodes in production units.

Clinimetric properties of a smartphone application to measure the craniovertebral angle in different age groups and positions

BackgroundCraniovertebral angle (CVA) alteration is a causative factor for the neck, shoulder, and temporomandibular joints disorders. Therefore, as an outcome measure for therapeutic intervention, measuring the craniovertebral angle with the Surgimap smartphone app is a cost-effective, easily accessible, and reliable tool. This study's objective was to assess the clinimetric properties of the Surgimap smartphone application with Surgimap system software to measure the Craniovertebral Angle in different age groups and positions. MethodNinety subjects with neck pain were randomly allocated to aged between 18 and 30 years (Group A; n = 45) and 45–60 years (Group B; n = 45). Using the Surgimap smartphone application and Surgimap system software, the craniovertebral angle was measured objectively in the sagittal plane. Intraclass correlation coefficients were used to determine validity and reliability. Receiver operating characteristic (ROC) curves and the area under the curves (AUC) were determined to distinguish participants with and without forward head posture. ResultThe result of this study shows that Smartphone Surgimap Application and Surgimap System Software correlate 0.95 and have p-values of 0.01 for diverse positions and ages. CVA measurement in the sitting position was significantly lower than in the standing position, regardless of methodology or age. Both positions demonstrated high intra-rater reliability, as evidenced by Intraclass Correlation Coefficients (ICC) between 0.972 and 0.991. The minimum detectable change (MDC) values ranged from 1.3 to 1.733, indicating high measurement accuracy. The smartphone application demonstrated outstanding diagnostic sensitivity (100.00% for Group A standing) and specificity (93.55% for Group B standing). ConclusionThe Surgimap smartphone application is a reliable and accurate method for craniovertebral angle measurement and is useful for measuring outcomes. Also standing posture was found to be better than sitting posture while measuring the CVA.

Method of Attention-Based CNN for Weighing Pleurotus eryngii

Automatic weight detection is an essential step in the factory production of Pleurotus eryngii. In this study, a data set containing 1154 Pleurotus eryngii images was created, and then machine vision technology was used to extract eight two-dimensional features from the images. Because the fruiting bodies of Pleurotus eryngii have different shapes, these features were less correlated with weight. This paper proposed a multidimensional feature derivation method and an Attention-Based CNN model to solve this problem. This study aimed to realize the traditional feature screening task by deep learning algorithms and built an estimation model. Compared with different regression algorithms, the R2, RMSE, MAE, and MAPE of the Attention-Based CNN were 0.971, 7.77, 5.69, and 5.87%, respectively, and showed the best performance. Therefore, it can be used as an accurate, objective, and effective method for automatic weight measurements of Pleurotus eryngii.

Prediction of Blade Tip Timing Sensor Waveforms Based on Radial Basis Function Neural Network

As the existing Blade Tip Timing (BTT) vibration measurement methods have serious under-sampling problems, where the blade resonance frequency is usually higher than the sampling frequency of the data acquisition system of the BTT method, resulting in large errors in the identification of blade vibration parameters, new solutions are needed to extend the capability of BTT to nonlinear and multimodal vibration analysis. Therefore, it is the current research direction to pursue new and more accurate measurement and signal processing methods. By analyzing the waveform data from the BTT sensor and using it for vibration analysis, it significantly extends the BTT database. To avoid the current problems of under-sampling and low recognition accuracy, this paper conducts a study on the recognition of rotating blade vibration parameters based on the Radial Basis Function (RBF) model by establishing a RBF neural network prediction model to analyze the static calibration experimental data and predict the waveform of the BTT sensor, and comparing the prediction curves of various models. As the results show, for the RBF model, the prediction accuracy is closely related to the source data of the sampling point data, when the source data predicted by the RBF model is close to the center of the samples, the prediction accuracy is high, meanwhile, the prediction accuracy decreases as it is far away from the center of these data. At the same time, the number of samples is too small to affect the prediction ability of the RBF model. By using this method, more waveforms under the Blade Tip Clearance (BTC) can be predicted with the available sample point data, and the errors in the experimental measurement process can be corrected.

Research on a Super-Sub-Arc Bivariate Relative Angle Thermal Deformation Testing Method without Pitch Angle Limitation

In light of the current situation where no testing equipment is available for measuring thermal deformation of objects, this paper proposes a novel method for accurate and precise measurement. The method overcomes the limitations of previous approaches that relied on pitch angle. By utilizing the principle of biplane multiple reflections, a bivariate laser spot displacement analysis algorithm is devised to attain highly precise measurements of bivariate angles. Additionally, a temperature gradient comparison algorithm is introduced to calculate the indicator test results under specific temperature conditions. To validate the effectiveness and reliability of this method, a testing system is constructed and utilized. The results demonstrate that the thermal deformation angle change test achieves an impressive accuracy of 0.015″ and a rate of thermal deformation angle change of 0.3247″/°C. These values are in close agreement with the previously simulated analysis result of 0.359″/°C, with only a relative error of 9.55%. Therefore, the test results confirm the efficacy and reliability of this testing method along with the feasibility of the algorithm processing.

Colorimetric Assay for Protein Redox Activity – a Complement to Electrochemistry

Oxidoreductases are vital biocatalytic tools for driving redox conversions that are challenging using conventional catalysts. Monooxygenases, an important class of these enzymes, have been the subject of enzyme engineering due to their high activity and versatile substrate scope. Reactions performed by these biocatalysts have long been monitored by a colorimetric method involving the coupling of a dye precursor to naphthalene hydroxylation products generated by the enzyme. Despite the popularity of this method, we found the dye product to be unstable, preventing quantitative readout. By incorporating an extraction step to solubilize the dye produced, we have improved this assay to the point where quantitation of enzyme activity is possible. Further, by incorporating spectral deconvolution, we have, for the first time, enabled independent quantification of the two possible regioisomeric products: 1-naphthol and 2-naphthol. Previously, such analysis was only possible with chromatographic separation, increasing the cost and complexity of analysis. The efficacy of our improved workflow was evaluated by monitoring the activity of a toluene-4-monooxygenase enzyme from Pseudomonas mendocina KR-1. Our colorimetric regioisomer quantification was found to be consistent with chromatographic analysis by HPLC. The development and validation of a quantitative colorimetric assay for monooxygenase activity that enables regioisomeric distinction and quantification represents a significant advance in analytical methods to monitor enzyme activity. By maintaining facile, low-cost, high-throughput readout while incorporating quantification, this assay represents an important alternative to more expensive chromatographic quantification techniques. For the electrochemistry community, the use of monooxygenases or other redox capable enzymes for biocatalysis must be complemented by a toolkit of methods for accurate enzyme activity measurement. Our approach demonstrates that accurate, mixture analysis is possible in a higher throughput using the improved colorimetric method. The relevant assay reaction, the hydroxylation of naphthalene, may be readily incorporated in the future for measurement schemes with other enzymes than the tested toluene-4-monooxygenase, thus enabling opportunities to tune these biocatalysts towards desired activities.

An accurate measurement method of gear transmission error based on a double-angle measurement device

In this paper, a geometric model of a grating and reading head was established, where the relationship between the angle deviation, which was compensated for by double reading heads, and the actual angle is deduced. A new measurement method was proposed by applying the clock pulse counting method to the measurement of the transmission error of the gear pair input-and-output angle encoder while taking into account the gear pair’s transmission error. To demonstrate the feasibility of this measurement method, a transmission error test bench of involute gear pairs was built. Based on the output gear, the counted pulses were divided into integer pulses and non-integer pulses, and a transmission error curve was obtained by processing the pulses. The transmission errors of a helical gear with untrimmed angles and a gear pair with trimmed angles were also measured. Compared with the untrimmed gear pair, the first-order amplitude of the trimmed gear pair was reduced by 25.25%, 0.79%, and 16.9%, but other whole-order full-harmonic amplitudes were excited. However, the peak value of the single tooth surface of the trimmed gear pair was generally less than that of the untrimmed gear pair. The peak transmission error and the amplitude of the tooth harmonic frequency had good repeatability, within 16%, which verified the feasibility of the transmission error test method. The measurement precision reached 1 arcsecond in the tooth frequency.

An efficient and accurate measurement method of tooth flank variations for face gears

Traditional measurement method for face gear variations is time-consuming, for it is based on a complex procedure to establish the measurement coordinate system (MCS). Moreover, errors induced by misalignment between the design coordinate system (DCS) and the MCS are not properly processed in measurement. Therefore, this work proposes an efficient and accurate method to measure face gear flank variations using the coordinate measurement machine (CMM). Firstly, the MCS establishment without the need for an iterative process, which saves measurement time. Secondly, the measurement error compensation model (MECM) relies on the MCS and utilizes the four-parameter representation, which reduces variables in the nonlinear equation system. Finally, experiments demonstrated the effectiveness and repeatability of this method, successfully reducing misalignment errors. The tooth flank normal variation improved by 3.33%, the pitch variation improved by 26.28%, and the total cumulative pitch variation improved by 19%.

Investigating the time-varying effect and accurate measurement method of wet shotcrete rheology based on eBT2 rheometer

An appropriate amount of air-entraining agent improves the wet shotcrete fluidity, and the accurate measurement of rheological parameters accurately expresses the rheological characteristics of sprayed concrete. In this paper, eBT2 rheometer was used to measure time variation of rheological parameters of high air content wet shotcrete (HACWS). At the same time, in order to investigate measurement accuracy of shotcrete rheology, the influence of rheometer operating modes (OM) on rheological parameters was studied. This paper selected four rheometer OM to comprehensively analyze the rheological characteristics and rheometer measurement accuracy of HACWS. The results showed that relative plastic viscosity (RPV) and relative yield stress (RYS) of HACWS both tended to decrease first and then increase with time. The torque measured by eBT2 rheometer remained constant at high shear rates. The rheological parameters obtained with different OM differed significantly, and OM-B was recommended to analyze the rheological properties of fresh concrete. This paper provides a reference for the selection of air-entraining agent type and rheometer OM.

Studi Komparatif Daya Dukung Pondasi Tiang Pancang Berdasarkan Hasil Pile Driving Analyzer Test dan N-SPT

The construction of the skidway in the southern part was planned using a pile foundation on the lower structure. Piles are used to channel the load received by the above part of the structure into the ground. The foundation of the structure must have a mast carrying capacity greater than the plan load that the foundation is capable of accepting. This research is important to find out whether the different methods implemented in the field produce different soil carrying capacity. This research will discuss the comparison of pile carrying capacity with field data and testing the carrying capacity of pole foundations. The method of accurate carrying capacity measurement is carried out by static loading with a test method with a loading scale of 2-3 times the planned load. Another method that can be done is HSDPT, which is a high strain dynamics pile test or a pile driving analyzer (PDA) Test. The test results of the analysis showed that there was only a 1% difference in results through an empirical approach with testing with CAPWAP and PDA tests on the southern cpp deck expansion project. The conclusion of this research that the difference in the method used does not have a large enough deviation to the results obtained when construction is carried out in the field.

Aircraft Fuel Mass Estimation Using Global Nonlinear Parametric Modeling

The accuracy of fuel measurement in aircraft tanks is directly related to flight safety and maneuverability. Capacitance gauging is widely used and is the industry accepted method for accurate measurement of the fuel quantity. In this paper, a global nonlinear parametric modeling technique is applied to estimate the fuel content using the capacitance probe data generated from 3-dimentional models of the aircraft fuel tanks. Automatic Net generation Tool for Structural Analysis (ANSA) software is used to create the fuel tank solid models. Using truth tables generated from ANSA software, several 3 rd order polynomial models are developed. The fuel estimation algorithm is implemented in real time using Microcontroller based electronic unit.