Indirect Measurement Method Research Articles

PROBLEMS OF MEASURING LOW FEED RATES OF METAL CUTTING EQUIPMENT

The article is dedicated to the problem formulation of improving the method for measuring low feed rates in metal-cutting machines during finishing operations by using direct speed measurement sensors. The goal of the work is to review the issue of measuring low feed rates in blade machining in order to assess and minimize the uncertainties of feed rate measurements. The necessity of measurements and subsequent analysis of feed rate instabilities in metal-cutting machines within the range of 0 to 20 mm/min is demonstrated. It is shown that the uneven movement of machine tool elements can be a result of clearances in movable joints and overcoming friction forces in these clearances. The influence of the adaptive control system of the machine tool drive on the unevenness of feed rate is also presented. The effect on the unevenness of feed rate of different types of drives is described, including stepper motors, hydraulic and pneumatic drives, asynchronous motors with frequency converters, and servo motors. The main components of uncertainty arising from the indirect method of velocity measurement are described, related to uncertainties in time and distance measurement, errors in approximation during instantaneous velocity calculation, as well as errors associated with the discretization of time and distance measurements. Methods of direct feed rate measurement are discussed. It is shown that it is not possible to use sensors utilizing the Doppler effect for measuring small feed rates. It is noted that existing designs of magnetic velocity sensors have significant nonlinearity, which cannot be eliminated by adjusting measurement results. Limitations of known sensors regarding the length of the path on which the feed rate can be measured are specified. A promising direction for research on improving the method of direct measurement of small feed rates in metal cutting machines is identified.

THE METHOD OF INDIRECT TWO-PART MEASUREMENTS FOR THE CONTROL OF PRODUCTION INDICATORS

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

Study on the LAI Single Tree Model Based on Terrestrial Laser Scanning

Leaf area index (LAI) is a key parameter for studying global terrestrial ecology and environment and has great ecological significance. How to accurately measure and calculate structural parameters of trees has become an urgent matter. This paper reports the use of terrestrial laser scanning (TLS) as a measurement tool to achieve accurate LAI estimation through point cloud preprocessing measures, the LeWos algorithm, and voxel methods. The accuracy and feasibility of this indirect measurement method were explored. It is found that the single wood structure parameters extracted from TLS have a good linear relationship with manual measurement, and the extraction errors meet the requirements of real-scene conversion. The study also found when the voxel size is consistent with the minimum distance of the point cloud set by TLS instrument, it has a strong correlation with the measured value of canopy analyser. These results lay the foundation for conveniently and quickly obtaining structural parameters of trees, tree growth state detection, and canopy ecological benefit assessment.

Research on Intelligent Control Method for Radial Spinning Pressure Balance of Three-roller Spinning

Aiming at the imbalance of radial force in the traditional spinning process, an intelligent control method for radial spinning pressure balance of three-roller spinning machine is proposed. Firstly, an indirect measurement method of spinning pressure is proposed. By measuring the pressure in the two chambers of the output oil cylinder, the pressure of the rollers is calculated. Using the electro-hydraulic servo closed-loop control principle, the intelligent control of spinning pressure can be accomplished in one cycle by changing the rolling reduction of the roller. Secondly, three intelligent control methods of radial spinning pressure balance, sequential control method, simultaneous control method and immediate control method are proposed. Three evaluation indexes of workpiece wall thickness, radial runout and ellipticity are adopted. Influence rule of three different intelligent control methods of radial spinning pressure balance on workpiece spinning dimensional accuracy are studied by the evaluation indexes. The results show that the three evaluation indexes using the radial spinning pressure balance intelligent control method are significantly improved compared with the evaluation indexes without the radial spinning pressure balance control method. The size and precision of the parts are the best by the sequential control method.

ALGORITHM FOR DETERMINING THE TORQUE OF ELECTRIC MOTORS USING INDIRECT MEASUREMENT METHODS

Indirect torque measurement methods can be performed in a variety of ways, depending on the specific situation and available tools. One such way is to measure the displacement, or speed of rotation of the shaft and use this information to calculate the moment using the moment of inertia equation. For this, it is necessary to know the moment of inertia and the angular acceleration, which can be measured using a gyroscope or accelerometer. Another way is to measure the voltage and current in the electrical circuit connecting the motor and the power source by determining the power of the electric motor. However, indirect methods of measuring torques of electric motors are based on the measurement of other physical parameters that correlate with torque, such as current, voltage, rotation frequency, etc. These methods are often used because of their cost-effectiveness and ease of implementation, but they have some drawbacks. In particular: indirect methods are usually less accurate than direct methods because they depend on mathematical models and correlations between different parameters, which may be imprecise or incomplete; parameters that are measured by indirect methods may be influenced by external factors, which may affect the accuracy of measurements; calibration of devices is usually carried out in laboratory conditions, so the results may not reflect real operating conditions; the mathematical models used to determine the torque may be non-linear. This can lead to errors in measurements, especially at high or low torque values; indirect methods do not provide direct feedback about the real torque, which can lead to delays in process regulation and control. This can be critical for some applications where fast and accurate torque control is essential; indirect methods may be less efficient or unsuitable for some types of electric motors or applications. For example, when using high-frequency or multiphase motors, indirect methods may not provide sufficient accuracy or stability of measurements. The article examines algorithms for determining the rotational parameters of electric motors using indirect measurement methods. An analysis of the characteristics of electric motors according to their energy data was carried out. The measurement possibilities are determined based on the functional dependence of the torque on the power of the electric motor and the speed of rotation of its shaft. The characteristics of the power components are studied and the results of their simulation are given. An analysis of the methods of determining the angular velocity and angular acceleration of the electric motor shaft was carried out, and the role of these parameters in the determination of the torque was investigated. A two-channel network-type information and measurement system is proposed, which allows data collection and their visualization, where one channel is used to measure power, the other to measure shaft rotation speed.

Hybrid machine learning-enabled multi-information fusion for indirect measurement of tool flank wear in milling

To increase the utilization efficiency of multi-sensor signals and improve the measurement accuracy of tool wear, this study proposes an indirect tool wear measurement method based on multi-information fusion by hybrid machine learning technologies. In this method, triaxial cutting forces and vibration signals are collected and then preprocessed by wavelet packet denoising. The time, frequency, and time–frequency domain features are extracted to reduce the information redundancy, and the kernel principal component analysis is applied to fuse the most sensitive characteristics. A fusion model of least squares support vector regression and the particle swarm optimization algorithm is established to learn the dependency relationship between fused features and tool flank wear. Milling experiments under multiple working conditions are implemented to verify the effectiveness of the proposed method. Experimental results sufficiently demonstrated overall performance of the proposed method is better than that of other comparison methods.

Indirect measurement of solar array rotation angle for satellite emergency rescue

In the emergency rescue mission, the primary task is to achieve the satellite’s orientation to the sun and ensure the energy supply. For this purpose, it is necessary to determine the rotation angle of solar array relative to satellite body. However, the rotation angle cannot be measured directly by the angle sensor in case of satellite emergency. To handle this issue, an indirect measurement method of solar array rotation angle is proposed in this paper. First, the indirect point measurement value of solar array rotation angle is given via the relationship between satellite body coordinate frame and solar array coordinate frame and the Rodrigues’ rotation formula. Then, the interval analysis technique is used to determine the upper and lower bounds of rotation angle and evaluate the influence of measurement noises. Based on the determined point measurement value and the interval analysis results, a zonotopic Kalman filter-based strategy is further proposed to improve the measurement accuracy. Finally, the effectiveness and validity of the proposed approach are demonstrated by numerical simulations, which illustrate its engineering application value.

Theoretical derivation and experimental investigation of dynamic displacement reconstruction based on data fusion for beam structures

Accurately obtaining the dynamic displacement response of the beam structure is of great significance. However, it is difficult to directly measure the dynamic displacement for large structures due to the low measurement accuracy or the installation difficulty of the sensor. Therefore, it is urgent to develop an indirect measurement method for displacement based on measurable physical quantities. Since acceleration and strain contain high and low frequency displacement information respectively, this paper proposes a displacement reconstruction algorithm that can realize the data fusion of the two, which is very helpful for the research of structural health monitoring. Firstly, the stochastic subspace identification (SSI) method is adopted to calculate the strain mode, and then the displacement is derived via the mode shape superposition method. Afterwards, the strain-derived displacement and acceleration are combined by the proposed algorithm to reconstruct the dynamic displacement. Both the numerical simulation and model experiment are conducted to verify the effectiveness of the proposed algorithm. Furthermore, the influences of noise, sampling rate ratio and measurement point position are analyzed. The results show that the proposed algorithm can accurately reconstruct both high-frequency and pseudo-static displacements, and the displacement reconstructed error in the model experiment is within 5%.

Digitization in bioprocessing: The role of soft sensors in monitoring and control of downstream processing for production of biotherapeutic products

Owing to the advancement in the technologies, the vision of smart manufacturing is not implausible. Development of sophisticated measuring tools, modelling approaches, improved computational efficiency, wireless technology and emphasis on automation and digitalization has promoted soft sensor implementation in bioprocessing. With multiple driving forces including decrease in operational cost, reliable operation, ease in calibration, increased long term stability etc., soft sensor has become a central process analytical tool for accessing and maintaining real time critical quality attributes. Fundamentally, soft sensor is an indirect measurement method combining process data and a mathematical model to estimate a target quantity. The model input is primarily composed of hardware signals from inline process sensors, analytical devices, actuators, and the instruments. This article offers an overview of soft sensing techniques in downstream bioprocessing for production of biotherapeutic products. Novel possibilities that its implementation presents towards real time measurement, monitoring, modelling and control (M3C) during commercial manufacturing have been highlighted along with the technology challenges and potential solutions from a data scientist perspective.

Research on indirect measurement and estimation method of shearer drum cutting load

For the difficult problem that the shearer drum load is difficult to be detected and perceived directly, a shearer drum load indirect estimation measurement method and technique is proposed and invented. Based on the structural characteristics of the rocker arm, the basic rod system skeleton of the rocker arm is extracted. Based on the transfer route of the drum load on the rocker arm, the feasibility of using the rocker arm pin shaft load for drum load prediction is analyzed, and the correlation mechanics equation of load from the drum to the rocker arm pin shaft is constructed. To address the statically indeterminate problem in the equation, the Lagrange multiplier is introduced to construct the energy function of the rocker rod system skeleton. Based on the principle of minimum complementary energy and solving the extreme value of energy function, the statically indeterminate equation is transformed into the statically determinate equation, and a rough prediction model of drum load based on the force of the rocker arm hinged ear pin shaft is derived, and the maximum relative error of the model is 25.15 %. To address the low prediction accuracy of the model due to the dynamic characteristics of the drum rocker arm, the drum load is derived from the rocker arm hinged ear pin shaft load and the rough prediction model as input, and the experimentally measured drum load as output. The bp neural network error correction model is constructed, and the accurate estimation and perception of the drum load are realized by the prediction model and the bp neural network correction model. Finally, the accuracy of the prediction algorithm is verified by experiments. The results show that after correction by bp neural network, the average error of the drum three directional force is 0.14 × 104N ∼ 0.55 × 104N, the mean square error is 0.18 × 104N ∼ 0.65 × 104N, and the relative error is 3.99 %∼10.12 %. The average error of the drum three directional moment is 0.31 × 104N·m ∼ 0.40 × 104N·m, the mean square error is 0.16 × 104N·m ∼ 0.50 × 104N·m, and the relative error is 2.04 %∼11.44 %. The accuracy of drum load prediction is higher than 11.44 % in all cases. The research results can provide theoretical and technical support for intelligent shearer design, development, and healthy operation and maintenance.

Analysis of the non-linear relationship between Interest Rate Distortions in China’s Shadow Banking System and short-term Capital Flows

ABSTRACT Using semiparametric generalized additive models, we studied how the market-based interest rates in China’s shadow banking system and interest rate distortion affect the country’s short-term capital flows. We used big data of shadow banking products to calculate the shadow banking interest rate and the interest rate distortion index. We improved the indirect measurement method for capital flows and used the bounds testing cointegration approach to measure China’s monthly short-term capital flows. With the calculated data, we estimated the nonlinear impact of shadow banking interest rate spreads and interest rate distortion on short-term capital flows. Results indicate that a higher shadow banking interest rate spread creates greater short-term capital inflows and the degree of interest rate distortion has a non-linear inverted U-shaped effect on short-term capital flows. Thus, the Chinese government should proceed with interest rate liberalization to eliminate the current “dual-track interest rate system” and strengthen the monitoring of cross-border capital flows so as to reduce the risks of abnormal short-term capital flows.

Newly designed measurement system for the radon progeny activity size distribution based on screen diffusion battery

Accurate measurement of the activity size distribution of radon progeny is of importance for dose evaluation. To meet the increasing demand for field survey in China, a new measurement system consisting of 8 stages wire screen diffusion battery was developed, by which the unattached fraction, the fraction of particles larger than 2.5 μm, the activity size distribution and the activity concentration of each radon progeny could be measured simultaneously. To verify the activity size distribution measurement results of the new measurement system, a series of comparison experiments were carried out with an indirect measurement method in radon chamber and indoor environment. The results in radon chamber exhibited a good consistency between the two methods in activity size ranging from 73 nm to 297 nm with an average deviation of −1%, but the result measured by the new system was smaller at 551 nm due to the loss of large particles during the sampling process. Comparison results in indoors mostly showed a good agreement as the deviations were less than 10%, and some large deviations were also observed, which was mainly on account of the limitation of sensitivity and measurement uncertainty.

Estimation of arterial pressure through cuffs constructed from different fabrics using simulation modelling

Blood pressure is one of the vital signs and its accurate estimation using indirect methods of measurement is a challenge. Arterial pressure could not be estimated directly by inflatable cuffs (constructed from woven and non-woven fabrics) however those could be predicted using simulation modelling. In this investigation, three cuffs constructed from different fabrics were selected and simulation models were developed in Abaqus mimicking the phenomena of indirect blood pressure measurement. An anthropometric upper arm model was developed to validate the simulation models. The models showed good agreement with experimental results. Outcome of this study showed that it was possible to visualize pressure distribution through simulation models and to predict pressure transmission from cuff to arm and then to the artery by calculating pressure transmission ratio. This study also found that the prediction of the arterial pressure through simulation may help in identifying errors associated with current method of indirect blood pressure measurement which may help in designing of new cuffs using suitable constructing materials for accurate estimation of blood pressure.

Correcting for the clumping effect in leaf area index calculations using one-dimensional fractal dimension

The clumping effect is the main issue causing the heterogeneity in vegetation canopies and the underestimation of leaf area index (LAI) obtained using indirect measurement methods. Significant efforts have been exerted to correct for the clumping effect and derive the true LAI. Recent research has shown that the fractal dimension (FD) is directly related to the clumping effect of foliage, yet practical methods are needed to calculate field estimates. Considering that widely used LAI applications such as digital hemispherical photography (DHP), tracing radiation and architecture of canopies (TRAC), and digital cover photography (DCP) estimate LAI with one-dimensional (1D) gap probability and gap size data, we propose a method to correct for the clumping effect using 1D FD. Resulting formulae describing the relationship between LAI, CI, and 1D FD were based on the box-counting method (BCM) and a binomial distribution model. Sixty-four simulated scenes including four RAdiation transfer Model Intercomparison (RAMI) actual canopies and field measurements from nine plots (four orchard plots and five coniferous forest plots) were used to validate the novel method. Results showed good agreement with reference LAI values for simulated scenes (R2 = 0.96 and RMSE = 0.35). The 1DFD method generated higher LAI estimates compared with the LAI measured using TRAC at the four orchard plots especially at high canopy closure, while its results were more consistent with LAI obtained by litter collection than those of comparable methods at coniferous forest plots (bias from −13.5% to 9.9% for DCP images, from −3.0% to 19.7% for DHP images, and from −3.8% to 17.0% for TRAC transects). Our validation efforts indicate that the method proposed herein corrects for the clumping effect of vegetated canopies more effectively with DCP images, DHP images, and TRAC measurement when compared with traditional indirect optical methods. The 1DFD method is expected to improve indirect measurement accuracy of LAI.

An XGBoost-based model for assessment of aortic stiffness from wrist photoplethysmogram

Background and ObjectiveCarotid-femoral pulse wave velocity (cf-PWV) is the gold standard for non-invasive assessment of aortic stiffness. Photoplethysmography used in wearable devices provides an indirect measurement method for cf-PWV. This study aimed to construct a cf-PWV prediction method based on the XGBoost algorithm and wrist photoplethysmogram (wPPG) for the early screening of arteriosclerosis in primary healthcare. MethodsData from 210 subjects were used for modeling, and 100 subjects were used as an external validation set. The wPPG pulse waves were filtered by discrete wavelet transform, and various features were extracted from each waveform, including two original indexes. The extraction rate (ER) and Pearson P were calculated to evaluate the applicability of each feature for model training. The magnitude of cf-PWV was predicted by an XGBoost-based model using the selected features and basic physiological parameters (age, sex, height, weight and BMI). The level of aortic stiffness was classified by a 3-classification strategy according to the standard cf-PWV (measured by the Complior device). Bland-Altman plot, Pearson correlation analysis, and accuracy tested performance from two aspects: predicting the magnitude of cf-PWV and classifying the level of aortic stiffness. ResultsIn the external validation set (n = 100, age range 22–79), 97 subjects obtained features (ER = 97%). The predicted cf-PWV was significantly correlated with the standard cf-PWV (r = 0.927, P < 0.001). The accuracy (AC) of the 3-classification was 85.6%. The interrater agreement for assessing aortic stiffness was at least substantial (quadratically weighted Kappa = 0.833). ConclusionsThe multi-parameter fusion cf-PWV prediction method based on the XGBoost algorithm and wPPG pulse wave analysis proves the feasibility of atherosclerosis screening in wearable devices.

Measurement and automatic monitoring insulation resistance of AC/DC mixed unearthed networks

Marine industry is one of the strong sectors bringing great economic benefits in the world and especially in Vietnam. However, the control of marine aquatic environment is always a complicated problem in both solutions and implementation. Currently, monitoring systems are capable of measuring most of the indicators but still face many difficulties with special indicators such as NH3, H2S, which need to integrate many specialized equipment applications, complex measurement procedures, or waiting for results from a laboratory. Therefore, the implementation is hindered and increases the investment cost. In this article, the authors apply an indirect measurement method to determine the rate of ammonia (NH3) for an automatic monitoring system of the aquatic environment. The monitoring system will monitor the basic water indicators in the National technical regulation on aquaculture water including temperature, salinity, pH, and based on that to calculate and determine the distribution rate of NH3 – factor major cause of losses in the marine products industry. The application of this indirect measurement method aims to directly assess the fluctuation of the Ammonia NH3 index and contribute to the reduction of aquatic environmental monitoring models.

Effect of culture depth on the shell thickness of the blue mussel Mytilus edulis: a practical case study comparing direct and indirect methods of measurement

ABSTRACT Mytilus species have a fundamental role in coastal environments and constitute an important aquaculture resource. Their shell has a protective function and is affected by multiple factors, such as the size of the animal, density, environmental characteristics and presence of predators. It is crucial to accurately estimate shell thickness in order to understand the effects of the ever-changing environment on mussel physiology, morphology and ecology. This study compares a newly developed direct method for measuring shell thickness, using scanning electron microscopy (SEM), and a widely used indirect method (shell thickness index, STI), in the context of a practical case study of the blue mussel Mytilus edulis. In this study, STI did not appear as highly correlated to direct thickness measurement as in previous studies. This study also showed a weaker relationship between measured shell length and STI. In the case study, assessing the effect of culture depth on M. edulis growth and condition, STI showed a significant variation with depth, while SEM measured thickness did not. Therefore, the choice to use STI vs direct measurement of shell thickness drastically changed the results and interpretation of the case study. This work highlights the importance of a carefully designed method for measuring shell thickness and emphasizes that, before application, indirect methods should be quality controlled for the population studied. However, when high precision is needed for shell thickness measurements the application of SEM-based techniques may be necessary. This is the first study where SEM-based techniques have been used to measure shell thickness in M. edulis.

Simultaneous experimental verification of indirect thrust measurement method based on Hall-effect thruster and plasma plume

In this work, the experimental verification of the indirect thrust measurement method based on the plume of a low power Hall-effect thruster and its effect on the thruster is investigated. The Hall-effect thruster with permanent magnets was exhibited and the performance parameters and the plume parameters were introduced, and the thrust of the thruster was measured simultaneously using both direct and indirect measurement methods, which validate the effect due to thruster and the measurement devices. The experimental verification of the thrust amendment values was proposed considering the ion flux collection, the neutral atoms, and the additional momentum due to ion reflecting, and the corresponding amended thrust results were exhibited separately which show the contribution of each factor, and the modification method could provide reliable results for indirect thrust measurement.

Acoustic Roughness Measurement of Railway Tracks: Laboratory Investigation of External Disturbances on the Chord-Method with an Optical Measurement Approach

For acoustic roughness monitoring of the railway network at train travelling speed, new direct measurement methods are required. Common direct measurement methods need the blocking of track sections, as they are based on manually operated devices. Indirect measurement methods such as accelerometer or microphone measurements can be installed on the train, but require a conversion of the obtained measurement data to rail roughness. Optical measurement methods allow a direct measurement from the moving train, even at higher speeds, due to the contact-free nature of the measurement. This paper investigates the influence of various disturbances on the measurement result, which are expected on the train. The frequently used chord method deploying laser triangulation sensors is used. Four sensors are integrated into the setup, thus providing the possibility to combine the results from four chord methods. The measurements of the optical system are compared with a tactile measurement of METAS (Swiss Federal Institute of Metrology) on a test bench equipped with a reference rail segment. It is shown that dust and water on the rail have a significant influence in the range of small wavelengths. Displacements and tilting of the sensor array, as well as vibrations, can be compensated to a certain level by the chord method, while a single sensor is significantly disturbed. The combination of four different chord lengths and selection of the theoretically optimal method for each one-third octave band shows an improvement of the measurement result. Based on the observations made, recommendations for practical tests on the train are concluded.

Study of high-precision velocimetry technique based on absorption spectrum for deep space exploration

Asymmetric spatial heterodyne spectroscopy is a new ultra-high resolution remote sensing technique. Due to the advantages of large luminous flux, small size, and high precision, it is suitable for high-precision detection of detector motion speed in a deep-space exploration environment. However, even after decades of development, this technique has still not been used as a mature scientific tool for space detection. This paper deeply analyzes the Doppler Asymmetric Spatial Heterodyne (DASH) spectral velocimetry technique from the perspective of digital signal processing, establishes the corresponding mathematical model, and deduces the measurement constraint relationship. To overcome the accuracy defect of direct measurement based on the absorption spectral signal, the Background Light Synchronous Elimination (BLSE) method has been introduced as a feasible indirect measurement scheme. Through data simulation experiments, the resolution accuracy of direct and indirect measurements was verified, and it is proven that the indirect measurement method is necessary for high-precision spectral velocimetry in a deep-space environment.