Measurement Data Processing Research Articles

Spatiotemporal Diurnal Modulation Characteristic of Wind Speed and Power Generation Revealed by Its Measured Data Processing.

Atmospheric turbulence is an intrinsic factor that causes uncertainty of wind speed and its power generation by wind turbine. The research of atmospheric turbulence characteristics of wind farms can be used to reduce this uncertainty. In this paper, enough measurement data getting from actual wind farms is used for information processing to quantitatively analyze the daily variation of wind speed and its power output characteristics. Furthermore, the concept of spatiotemporal diurnal modulation characteristics of atmospheric turbulence is proposed with a global scope, which is an intrinsic property of wind. Besides the daily variation characteristics, the average hourly wind speed has a short-term modulation effect on its turbulence and provides a modulation characteristic on wind speed uncertainty. Moreover, the long-term modulation process is affected by seasonal and regional factors, indicating that it has spatiotemporal characteristics. This atmospheric turbulence characteristic has similar effects on characteristic description parameters. However, the characteristics description parameters of wind speed and wind power variation fail to reflect such intrinsic characteristics that are not affected by the spatiotemporal diurnal modulation characteristics of atmospheric turbulence. This indicates that they do not have diurnal characteristics. Finally, a time-varying model combined with the spatiotemporal diurnal modulation characteristics of wind speed and its power generation is discussed by applying on the evaluation of frequency control in power systems. It is shown that the results obtained by measured data processing could improve the power generation quality of large-scale wind power effectively.

Robust Quantum State Tomography Method for Quantum Sensing.

Reliable and efficient reconstruction of pure quantum states under the processing of noisy measurement data is a vital tool in fundamental and applied quantum information sciences owing to communication, sensing, and computing. Specifically, the purity of such reconstructed quantum systems is crucial in surpassing the classical shot-noise limit and achieving the Heisenberg limit, regarding the achievable precision in quantum sensing. However, the noisy reconstruction of such resourceful sensing probes limits the quantum advantage in precise quantum sensing. For this, we formulate a pure quantum state reconstruction method through eigenvalue decomposition. We show that the proposed method is robust against the depolarizing noise; it remains unaffected under high strength white noise and achieves quantum state reconstruction accuracy similar to the noiseless case.

Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements

This article presents the process of the construction and testing a remote, fully autonomous system for measuring the operational parameters of fans. The measurement results obtained made it possible to create and verify mathematical models using linear regression and neural networks. The process was implemented as part of the first stage of an innovative project. The article presents detailed steps of constructing a system to collect and process measurement data from fans installed in actual operating conditions and the results of analysis of this data. In particular, a measurement infrastructure was developed, defined, and implemented. Measuring equipment was mounted on selected ventilation systems with relevant fans. Systems were implemented that allowed continuous measurement of ventilation system parameters and remote transmission of data to a server where it was regularly analysed and selected for use in the process of modelling and diagnostics. Pearson’s correlation analysis for p < 0.05 indicated that all seven parameters (suction temperature, discharge temperature, suction pressure, current consumption, rotational speed, humidity, and flow) were significantly correlated with efficiency (p < 0.001). A satisfactory level of correlation between the selected parameters measured in actual conditions and the characteristics of the fan and the ventilation system was experimentally verified. This was determined by finding 4 statistically significant parameters at a confidence level of 95%. This allowed the creation of two mathematical models of the fan system and the ventilation system using linear regression and neural networks. The linear regression model showed that the suction temperature, discharge temperature, and air humidity did not affect the fan efficiency (they are statistically insignificant, p > 0.05). The neural model, which considered all measured parameters, achieved the same accuracy as the model based on four significant parameters: suction pressure, current consumption, rotational speed, and flow.

The GUM Tree Calculator: A Python Package for Measurement Modelling and Data Processing with Automatic Evaluation of Uncertainty

There is currently interest in the digitalisation of metrology because technologies that can measure, analyse, and make critical decisions autonomously are beginning to emerge. The notions of metrological traceability and measurement uncertainty should be supported, following the recommendations in the Guide to the Expression of Uncertainty in Measurement (GUM). However, GUM offers no specific guidance. Here, we report on a Python package that implements algorithmic data processing using ‘uncertain numbers’, which satisfy the general criteria in GUM for an ideal format to express uncertainty. An uncertain number can represent a physical quantity that has not been determined exactly. Using uncertain numbers, measurement models can be expressed clearly and succinctly in terms of the quantities involved. The algorithms and simple data structures we use provide an example of how metrological traceability can be supported in digital systems. In particular, uncertain numbers provide a format to capture and propagate detailed information about quantities that influence a measurement along the various stages of a traceability chain. More detailed information about influence quantities can be exploited to extract more value from results for users at the end of a traceability chain.

Универсальный метод оценки вероятности лазерной индикации затопленных инженерных конструкций

Object and purpose of research. Laser diagnostics, analysis of reflected laser signal from fixed underwater objects, improvement of laser optical methods, technologies and tools for underwater object studies, development of laser detection systems, determination of laser indication probability for fixed underwater objects. Materials and methods. Laser detection systems, analytical and computational methods, software programs, analytical tools for measurement data processing, laser diagnostics of reflected laser signal from underwater objects taking into account dissipation and absorption in atmosphere and hydrosphere. Main results. Improvement of technology and methods for diagnostics of reflected laser signal (back-scattering), determination of reliable detection limits for laser signals reflected from fixed underwater objects, software programs, laser diagnostics, efficiency analysis of laser detection systems. Conclusion. The study showed that high efficiency of laser detection systems considerably depends on the selected tech- nology, reflected laser signal display and processing techniques, and also on the probabilistic methods adopted to estimate the reflected signal luminance and the knowledge of hydrodsphere parameters.

Application of an improved testing device for the study of alumina dissolution in silicate slag

This study entailed a dissolution study of alumina fine ceramics in a CaO–Al2O3–SiO2–MgO silicate slag system with a CaO/SiO2 weight ratio of 0.65. Finger-test experiments with several corrosion steps were carried out in a contemporary continuous wear testing device at 1450, 1500, and 1550 °C with 200 rpm. The corroded sample profiles were measured using a high-resolution laser scanner, and the processed measurement data were used to extract the dissolution parameters (i.e. corroded volume, surface area, mean radius, tip radius and immersion length). The diffusivity determination method using Sherwood relations was developed for the dynamic finger-test setup. The diffusivities for all corrosion steps were determined from these dissolution parameters, and those obtained from the Sherwood relations were compared with the ones received by a simulation approach that includes deviations from the cylindrical shape. The results obtained using Sherwood relations are sufficiently accurate in several cases.

Underwater 3D Measurements with Advanced Camera Modelling

A novel concept of camera modelling for underwater 3D measurements based on stereo camera utilisation is introduced. The geometrical description of the ray course subject to refraction in underwater cameras is presented under assumption of conditions, which are typically satisfied or can be achieved approximately. Possibilities of simplification are shown, which allow an approximation of the ray course by classical pinhole modelling. It is shown how the expected measurement errors can be estimated, as well as its influence on the expected 3D measurement result. Final processing of the 3D measurement data according to the requirements regarding accuracy is performed using several kinds of refinement. For example, calibration parameters can be refined, or systematic errors can be decreased by subsequent compensation by suitable error correction functions. Experimental data of simulations and real measurements obtained by two different underwater 3D scanners are presented and discussed. If inverse image magnification is larger than about one hundred, remaining errors caused by refraction effects can be usually neglected and the classical pinhole model can be used for stereo camera-based underwater 3D measurement systems.

Research on Roundness Error Evaluation of Connecting Rod Journal in Crankshaft Journal Synchronous Measurement

The crankshaft is the core part of an automobile engine, and the accuracy requirements of various shape and position errors are very high. On the basis of a synchronous measurement system, the connecting rod journal is deeply studied, including data processing and roundness evaluation. Firstly, according to the measuring processes of connecting rod journals, the real sampling angle distribution function was established, and the corresponding Gaussian weight function of each sampling angle was calculated. The weight function and the collected data corresponding to the angle were subjected to discrete cyclic convolution operation in the spatial domain to obtain the filtered effective circular contour data. Secondly, the particle swarm optimization algorithm was improved, and its inertia weight was set to decrease nonlinearly to speed up the convergence. A calculation process suitable for the evaluation of journal errors was designed. Then, the improved particle swarm optimization algorithm was used to evaluate the roundness of the corrected rod journal contour data. At last, through multiple measurement experiments, the feasibility and effectiveness of the synchronous measurement scheme and data processing method proposed in this paper are verified.

Flexible Mechanical Metamaterials Enabled Electronic Skin for Real‐Time Detection of Unstable Grasping in Robotic Manipulation

AbstractElectronic‐skin (E‐skin) has been investigated extensively for robotic tactile sensing. However, E‐skin sensors based on flexible metamaterials are still challenging to achieve. Moreover, the implementation of E‐skin sensor arrays in the actual monitoring of robotic grasping and manipulation conditions are rather limited due to the difficulty in data processing. Herein, high‐performance E‐skin strain sensors based on flexible auxetic metamaterials are reported, which endow the sensors with the capability of measuring both compressive (40%) and tensile (>80%) strain in a wide range and superior sensitivity, as compared with sensors without the structure. With perception data collected by the sensors, a generic method for real‐time detection of unstable robotic grasping is established. Through this method, the complicated problem of processing large‐scale arrayed sensor signals is simplified into the calculation of two indices, which extract both time and frequency domain characteristics of the signals. The total detection time (including sensor measurement response and data processing) can be as short as 100 ms, in line with human skin response in slippage perception. Accurate detections in real‐time during various grasping and manipulation tasks are presented, demonstrating the great value of the sensors and the detection approach in robotic perception and dexterous manipulation.

Historical data of atmospheric electric field observations in Japan

AbstractThe Kakioka Magnetic Observatory (KMO) of the Japan Meteorological Agency (JMA) made atmospheric electric field observations at Kakioka and Memambetsu beginning in 1929 and 1949, respectively, and ending in February 2021 and December 2010, respectively. The digital numerical data are available on the KMO website, although not all observation periods are covered. In this article, we introduce the available datasets and summarize the metadata regarding the observations, such as measurement instruments, maintenance methods and data processing.

A Quality Improvement Bundle to Improve Outcomes in Extremely Preterm Infants in the First Week.

Our objective with this quality improvement initiative was to reduce rates of severe intracranial hemorrhage (ICH) or death in the first week after birth among extremely preterm infants. The quality improvement initiative was conducted from April 2014 to September 2020 at the University of Alabama at Birmingham's NICU. All actively treated inborn extremely preterm infants without congenital anomalies from 22 + 0/7 to 27 + 6/7 weeks' gestation with a birth weight ≥400 g were included. The primary outcome was severe ICH or death in the first 7 days after birth. Balancing measures included rates of acute kidney injury and spontaneous intestinal perforation. Outcome and process measure data were analyzed by using p-charts. We studied 820 infants with a mean gestational age of 25 + 3/7 weeks and median birth weight of 744 g. The rate of severe ICH or death in the first week after birth decreased from the baseline rate of 27.4% to 15.0%. The rate of severe ICH decreased from a baseline rate of 16.4% to 10.0%. Special cause variation in the rate of severe ICH or death in the first week after birth was observed corresponding with improvement in carbon dioxide and pH targeting, compliance with delayed cord clamping, and expanded use of indomethacin prophylaxis. Implementation of a bundle of evidence-based potentially better practices by using specific electronic order sets was associated with a lower rate of severe ICH or death in the first week among extremely preterm infants.

On-Line Monitoring of Biological Parameters in Microalgal Bioprocesses Using Optical Methods

Microalgae are promising sources of fuels and other chemicals. To operate microalgal cultivations efficiently, process control based on monitoring of process variables is needed. On-line sensing has important advantages over off-line and other analytical and sensing methods in minimizing the measurement delay. Consequently, on-line, in-situ sensors are preferred. In this respect, optical sensors occupy a central position since they are versatile and readily implemented in an on-line format. In biotechnological processes, measurements are performed in three phases (gaseous, liquid and solid (biomass)), and monitored process variables can be classified as physical, chemical and biological. On-line sensing technologies that rely on standard industrial sensors employed in chemical processes are already well-established for monitoring the physical and chemical environment of an algal cultivation. In contrast, on-line sensors for the process variables of the biological phase, whether biomass, intracellular or extracellular products, or the physiological state of living cells, are at an earlier developmental stage and are the focus of this review. On-line monitoring of biological process variables is much more difficult and sometimes impossible and must rely on indirect measurement and extensive data processing. In contrast to other recent reviews, this review concentrates on current methods and technologies for monitoring of biological parameters in microalgal cultivations that are suitable for the on-line and in-situ implementation. These parameters include cell concentration, chlorophyll content, irradiance, and lipid and pigment concentration and are measured using NMR, IR spectrophotometry, dielectric scattering, and multispectral methods. An important part of the review is the computer-aided monitoring of microalgal cultivations in the form of software sensors, the use of multi-parameter measurements in mathematical process models, fuzzy logic and artificial neural networks. In the future, software sensors will play an increasing role in the real-time estimation of biological variables because of their flexibility and extendibility.

Using Signal Phase in Computerized Systems of Non-destructive Testing

Abstract Phase methods of measuring physical quantities and phase measuring equipment are widely used in various fields of science and technology. The article proposes a signal processing methodology based on a combination of the discrete Hilbert transform (DHT) and deterministic, as well as statistical methods of phase measurement. This methodology makes it possible to more fully use the information resource of the measuring signal phase in a wide range of the signal-to-noise ratio. It can be used both in computerized measurement and testing systems, as well as in the processing of measurement data. The benefits of the DHT are considered. The possibility of using statistics of directional data for phase measurements is shown. Circular statistics, such as the mean ring value, circular variance and the resulting vector length, were proposed for use in the phase measurements. Some examples of the use of this methodology in measurements and non-destructive testing are given.

High-Throughput Legume Seed Phenotyping Using a Handheld 3D Laser Scanner

High-throughput phenotyping involves many samples and diverse trait types. For the goal of automatic measurement and batch data processing, a novel method for high-throughput legume seed phenotyping is proposed. A pipeline of automatic data acquisition and processing, including point cloud acquisition, single-seed extraction, pose normalization, three-dimensional (3D) reconstruction, and trait estimation, is proposed. First, a handheld laser scanner is used to obtain the legume seed point clouds in batches. Second, a combined segmentation method using the RANSAC method, the Euclidean segmentation method, and the dimensionality of the features is proposed to conduct single-seed extraction. Third, a coordinate rotation method based on PCA and the table normal is proposed to conduct pose normalization. Fourth, a fast symmetry-based 3D reconstruction method is built to reconstruct a 3D model of the single seed, and the Poisson surface reconstruction method is used for surface reconstruction. Finally, 34 traits, including 11 morphological traits, 11 scale factors, and 12 shape factors, are automatically calculated. A total of 2500 samples of five kinds of legume seeds are measured. Experimental results show that the average accuracies of scanning and segmentation are 99.52% and 100%, respectively. The overall average reconstruction error is 0.014 mm. The average morphological trait measurement accuracy is submillimeter, and the average relative percentage error is within 3%. The proposed method provides a feasible method of batch data acquisition and processing, which will facilitate the automation in high-throughput legume seed phenotyping.

TLS point cloud as a data source for multi-lod of 3D models

The development of science and technology had a strong impact on all branches of engineering, including geodesy and the possibility of acquiring and processing measurement data. The best example of this is the Terrestrial Laser Scanning, whih can perform measurements in the form of a multi-million-point cloud. The cloud, representing places and objects, becomes a spatial database. The current problem in engineering is no longer data acquisition and processing, but information excess and redundancy. The solution to this problem is optimisation, which is the process of reducing the amount of data. It should implement its assumptions in such a way as to remove or reduce unnecessary information without losing the information presented by an ob- ject. This issue is particularly important in the process of using point clouds in 3D modelling at various levels of detail. The appropriate levels of the LOD0–LOD4 model require a different type of data: on the one hand ensuring the obtainment of the appropriate accuracy class in the study, and on the other hand, the data source should not contain too detailed information that is unnecessary for the study, which makes the work harder and slows it down due to the need to operate on a huge amount of redundant information Therefore, the purpose of this paper is to determine the scope of work on the optimisation of the point cloud in order to adjust its number and quality to the needs of individual LODs. The results of the work allowed to determine the scope of data unification for the respective precision groups of 3D models generating.

Unequally Interval Data Processing Across Fault Deformation Measurement

According to different regions, conditions and requirements, the cross-fault measurement specifications is allowed to measure at different resurvey periods, and resulted in unequal interval observation data. The unequal interval observation data is a common phenomenon data, the difference on both sides of the fault is observed by geological investigation, historical record, artificial observation, simulated record, digital sampling, encrypted observation before and after the event, change of observation equipment, change of observation environment, human factors, etc, and the unequal interval observation data is obtained. The characteristics of the unequal interval observation data is not only shown in time, but also in space. The unequal interval observation data is usually preprocessed into equal interval data by some kind of algorithm chosen before the subsequent complex calculation. In the data processing of cross-fault measurement, the unequal interval observation data is usually preprocessed into equal interval data, and then calculated, which leads to a series of new problems, such as time calculation, synchronization, master-slave relationship, comparability and so on. In view of unequal interval observation data in cross-fault measurement, some new problems are tried to solve in unequal interval data matching calculation by using conventional methods combined with some algorithm requirements, data characteristics and practical experience, and their adaptability in various algorithms is investigated in this paper. These works contribute to the improvement and development of cross-fault survey data processing methods, and enhance the role of cross-fault survey data in earthquake protection and disaster reduction.

Data processing of shipborne absolute gravity measurement based on extended Kalman filter algorithm

The precision dynamic measurement of absolute gravity based on the cold atom interferometer can provide a new method for marine gravimetry, so that it has attracted more attention. Based on the homemade shipborne cold atom interferometric absolute gravity measurement system, we carry out a series of measurement experiments in a certain area of the South China Sea. Under dynamic conditions, the suppression of measurement noise is essential for the improvement of the measurement performance. According to the physical model of the measurement system, in this paper a data processing method is proposed based on the extended Kalman filter algorithm for the absolute gravity dynamic measurement. The observed atomic interference fringe data are filtered in the time domain to estimate the absolute gravity value. Based on this processing method, the sensitivity of absolute gravity measurement under the condition of ship speed less than 2.1 km/h is improved from 300.2 mGal/Hz<sup>1/2</sup> to 136.8 mGal/Hz<sup>1/2</sup> (<i>T</i> = 4 ms). Comparing the processed data with the data calculated from the earth gravity model (XGM2019), it is found that both of the data are in good agreement. These results confirm the effectiveness of the data processing method proposed in this paper, and provide a new processing method of suppressing the measurement noise of shipborne cold atom interferometric absolute gravity measurement system.

An Improved Iterative Algorithm Utilized in Data Processing for Incoherent Scatter Radar

Measurements by incoherent scatter radars (ISRs) play very important roles in modern ionospheric and geospace studies. The ionospheric parameters are normally extracted from echo signals of ISR using nonlinear iteration algorithms. The processing speed and accuracy significantly rely on the iteration algorithm. The Levenberg-Marquardt (LM) method is a widely used algorithm for nonlinear iteration in modern ISR data processing. In the present letter, a new iteration algorithm, which is the so-called dog leg (DL) method, was introduced. Comparing with the LM method, the step size for the iteration with the DL method is not fixed. The iteration step size for the DL method keeps being adjusted in accordance with the trust region during the iteration process. The performance of the DL method was compared with that of the LM method using the simulation tests of ionospheric parameter extraction from ISR power spectra. The results showed that the DL method has better accuracy and iteration speed than that of the LM method. In addition, the error of the DL method is more stable than that of the LM method. Moreover, the DL method is more convergent than the LM method, which helps avoid the lack of ionospheric parameter due to the divergence of iteration with the LM method. Therefore, the DL method could be a more appropriate iteration algorithm for data processing of ISR measurements.

Содружество ленинградских ученых и производственников в обеспечении работ по изучению космоса и созданию аппаратуры для этих целей (вторая половина 50-х – 70-е годы XX века)

The article considers a set of works on the development of systems used for the study of outer space and the development of cosmonautics in the early years of the space age. The development of the unified time system, the system of the onboard standard of time and frequency "Liana", as well as equipment for studying long-wave X-ray radiation of the Sun, which was installed on the second artificial Earth satellite (AES), is being investigated. Attempts have been made to analyze the creation of equipment for recording the physiological parameters of living beings in space flight, the development of secondary electronic and photo-multipliers used in the creation of the first AES equipment, the development and manufacture of a complex of peripheral digital machines that allowed real-time processing and transmission of trajectory measurement data to the coordination and computing center. The issues of developing and manufacturing an automatic detonation system for unmanned vehicles are being studied. The data on the observation of the flight of the first satellites, on the improvements that made it possible to photograph with great accuracy, on the creation of a theory that allows calculating the orbit of the satellite, as well as to assess the influence of various factors on it: changes in atmospheric density, light pressure, the influence of harmonics of the gravitational field of the Earth. It tells about the first Soviet-American space experiment with a passive communication satellite "Echo-2". All this clearly illustrates the notable contribution of scientists and engineers from Leningrad (now Saint Petersburg) to space research at the dawn of the space age. The article pays special attention to the history of events that unfolded both inside the country and abroad regarding the creation and launch of the first artificial Earth satellite. And first of all, the reaction to this epoch-making event in the international scientific community, as well as the reaction to this event from some politicians in Western Europe. The analysis of some of the first joint experiments of Soviet and American scientists in the field of space exploration at the beginning of the space age of mankind is also of interest to readers.

Calibration and Operation of a Bistatic Real-Aperture Polarimetric-Interferometric Ku-Band Radar

This article presents the bistatic operation mode and the performance analysis of KAPRI, a terrestrial frequency-modulated continuous-wave (FMCW) Ku-band polarimetric radar interferometer capable of acquiring bistatic full-polarimetric datasets with high spatial and temporal resolution. In the bistatic configuration, the system is composed of two independently operating KAPRI devices, one serving as a primary transmitter and receiver and the other as a secondary receiver. The secondary bistatic dataset is affected by possible offsets between the two devices’ reference clocks, as well as distortions arising from the bistatic geometry. To correct for this, we present a two-chirp bistatic FMCW signal model, which accounts for the distortions, and a reference chirp transmission procedure, which allows correcting the clock offsets in the deramped signal time domain. The second challenge of operation of a bistatic polarimetric system is polarimetric calibration since it is not possible to employ purely monostatic targets such as corner reflectors. For this purpose, we developed a novel active calibration device Variable-Signature Polarimetric Active Radar Calibrator (VSPARC), designed for monostatic and bistatic calibration of all polarimetric channels. VSPARC and its associated novel polarimetric calibration method were then used to achieve full calibration of both KAPRI devices with polarimetric phase calibration accuracy of 20° and 30-dB polarization purity in field conditions. This article thus presents a complete measurement configuration and data processing pipeline necessary for synchronization, coregistration, and polarimetric calibration of bistatic and monostatic datasets acquired by a real-aperture FMCW radar.