Automatic Separation Research Articles

An Adaptive Pulse Separation Strategy for PD Detection in Frequency-Tuned Resonant Tests

Frequency-tuned resonant (ACRF) test is one of the most widely used technologies for power equipment diagnosis. However, the intense interference generated by the variable-frequency power source hinders its further application in partial discharge (PD) detection. For this reason, an adaptive PD separation method based on improved clustering by fast search and find of density peaks (CFSFDP) is proposed in this article to separate PD signals and disturbances under the ACRF test. First, the characteristics of the PD signals and the interference signals generated from the ACRF test system are analyzed and compared. Then, an improved CFSFDP algorithm is proposed to realize the automatic cluster center selection and signal separation, and the working principle of the PD separation strategy based on the improved CFSFDP algorithm is introduced. Finally, the effectiveness of the proposed method is validated by performing the ACRF test on a defective cable. The experimental results show that this method can realize the separation and detection of PD signals in ACRF tests. The proposed method provides a feasible solution for performing PD detection using the ACRF test system without the restriction of the test system structure.

Research on Electronic Switch in Ground Automatic Passing Phase System

This article mainly designs a new type of ground automatic phase separation device. The electronic switch with thyristor as the component is used to replace the traditional vacuum switch to switch the two-phase voltage when the locomotive passes through the phase separation zone. The conversion time of the two-phase voltage is controlled from 10ms to 40ms by the new ground automatic phase passing device, which is a great improvement compared with the traditional mechanical switch of 300ms. It is verified through simulation experiments that the locomotive conversion time is reasonably shortened, and the overvoltage and impact are reduced when the electronic switch is closed and opened. The rationality and feasibility of the electronic switch are verified.

Solvent-free synthesis of phytosterol linoleic acid esters at low temperature.

Phytosterol unsaturated fatty acid esters show much higher oil solubility than free phytosterol. Thus, development of a green and low-cost method for the preparation of phytosterol fatty acid esters is highly desirable in the food industry. Herein, we have developed a simple chemical method toward efficient preparation of phytosterol linoleic acid esters at very mild temperature (60 °C) using 4-dodecylbenzenesulfonic acid (DBSA) as the catalyst. In this work, low-temperature esterification of phytosterols (soybean sterol) with linoleic acid could produce the corresponding phytosterol esters above 95% conversion under solvent-free conditions. In addition, this simple method could be applied to produce phytosterol esters through esterification of phytosterol with an unsaturated fatty acid mixture resulting from the hydrolysis of various vegetable oils. Importantly, no extra organic solvents and no extra water-removal operations or equipment were required in this chemical esterification method. The mechanism investigation suggested that the DBSA-catalyzed low-temperature esterification would form micro-emulsions of water-in-oil (W/O), which could achieve automatic separation of water from the hydrophobic system to avoid reverse reaction hydrolysis and rapidly promote the equilibrium reaction towards phytosterol esters.

KAT4IA: K-Means Assisted Training for Image Analysis of Field-Grown Plant Phenotypes.

High-throughput phenotyping enables the efficient collection of plant trait data at scale. One example involves using imaging systems over key phases of a crop growing season. Although the resulting images provide rich data for statistical analyses of plant phenotypes, image processing for trait extraction is required as a prerequisite. Current methods for trait extraction are mainly based on supervised learning with human labeled data or semisupervised learning with a mixture of human labeled data and unsupervised data. Unfortunately, preparing a sufficiently large training data is both time and labor-intensive. We describe a self-supervised pipeline (KAT4IA) that uses K-means clustering on greenhouse images to construct training data for extracting and analyzing plant traits from an image-based field phenotyping system. The KAT4IA pipeline includes these main steps: self-supervised training set construction, plant segmentation from images of field-grown plants, automatic separation of target plants, calculation of plant traits, and functional curve fitting of the extracted traits. To deal with the challenge of separating target plants from noisy backgrounds in field images, we describe a novel approach using row-cuts and column-cuts on images segmented by transform domain neural network learning, which utilizes plant pixels identified from greenhouse images to train a segmentation model for field images. This approach is efficient and does not require human intervention. Our results show that KAT4IA is able to accurately extract plant pixels and estimate plant heights.

Два способи фрактального аналізу як морфометричного методу в анатомії: спосіб підрахунку квадратів vs спосіб дилатації пікселів

Проведено порівняльний аналіз двох способів фрактального аналізу як методу морфометрії – підрахунку квадратів і дилатації пікселів. Для розробки методик фрактального аналізу використано білу речовину мозочка людини. Порівняно дві авторські модифікації методів фрактального аналізу. За результатами підрахунку фрактального індексу двома різними методами на одному зображенні встановлено, що значення фрактального індексу, обчислені методами підрахунку квадратів і дилатації пікселів, майже не розрізняються. Обидва методи дають порівнянні результати і можуть бути використані для фрактального аналізу в морфометрії з однаково високою точністю. Вибір методу залежить від особливостей зображення й досліджуваної структури. У випадках, якщо зображення легко автоматично розділити на фон і основну структуру, методом вибору є метод дилатації пікселів. Для більш складних структур і зображень може бути застосований рутинний метод підрахунку квадратів.

Cyclic on-chip bacteria separation and preconcentration

Nanoparticles and biological molecules high throughput robust separation is of significant interest in many healthcare and nanoscience industrial applications. In this work, we report an on-chip automatic efficient separation and preconcentration method of dissimilar sized particles within a microfluidic platform using integrated membrane valves controlled microfiltration. Micro-sized E. coli bacteria are sorted from nanoparticles and preconcentrated on a microfluidic chip with six integrated pneumatic valves (sub-100 nL dead volume) using hydrophilic PVDF filter with 0.45 μm pore diameter. The proposed on-chip automatic sorting sequence includes a sample filtration, dead volume washout and retentate backflush in reverse flow. We showed that pulse backflush mode and volume control can dramatically increase microparticles sorting and preconcentration efficiency. We demonstrate that at the optimal pulse backflush regime a separation efficiency of E. coli cells up to 81.33% at a separation throughput of 120.45 μL/min can be achieved. A trimmed mode when the backflush volume is twice smaller than the initial sample results in a preconcentration efficiency of E. coli cells up to 121.96% at a throughput of 80.93 μL/min. Finally, we propose a cyclic on-chip preconcentration method which demonstrates E. coli cells preconcentration efficiency of 536% at a throughput of 1.98 μL/min and 294% preconcentration efficiency at a 10.9 μL/min throughput.

Partial Discharges Identification and Localisation within Transformer Windings

This study proposes a technique that is based on the hypothesis that distinct PD sources have unique PD waveform characteristics at the point of measurement. Two different forms of PD pulses are injected into a model transformer winding at different points and by using wideband radio frequency current transformers (RFCTs), measurement data are obtained by positioning the RFCTs at the neutral-to-earth point of the winding and the bushing tap-point-to-earth. Mathematical morphology energy analysis using ordering points to identify clustering structure and signal cross correlation methods are utilized to extract information from the raw measurement data. Assessment of the relative performance of the analytical methods are examined and characterized in this study. The proposed approach allows automatic separation of PD data by source and localization of source site within the winding.

A novel online preparative high-performance liquid chromatography system with the multiple trap columns-valve switch technique for the rapid and efficient isolation of main flavonoids from Epimedium koreanum Nakai.

In this work, a new online preparative high-performance liquid chromatography was developed for the fast and efficient separation of complex chemical mixtures from natural products. This system integrates two chromatographic systems into an online automatic separation system using the technique of multiple trap columns with valve switching. The sample was first separated into 18 subfractions in the online preparative high-performance liquid chromatography, and the sample eluents were then diluted and captured online on 18 trap columns by the multiple trap columns technique, respectively. Each subfraction retained on the trap column was transferred online to the separation column for the second separation. Finally, the target compounds were purified by appropriate separation conditions and multiple heart-cutting strategies. Importantly, the system was successfully used to separate 18 high-purity flavonoids from the crude extract of Epimedium koreanum Nakai online in one step. The entire separation time was approximately 20 h, and the structures were characterized by the high-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry and nuclear magnetic resonance. This online preparative high-performance liquid chromatography system represents an efficient and rapid separation system that has the potential for a wide array of applications in the separation of complex chemical components from natural products.

Unveiling water dynamics in fuel cells from time-resolved tomographic microscopy data

X-ray dynamic tomographic microscopy offers new opportunities in the volumetric investigation of dynamic processes. Due to data complexity and their sheer amount, extraction of comprehensive quantitative information remains challenging due to the intensive manual interaction required. Particularly for dynamic investigations, these intensive manual requirements significantly extend the total data post-processing time, limiting possible dynamic analysis realistically to a few samples and time steps, hindering full exploitation of the new capabilities offered at dedicated time-resolved X-ray tomographic stations. In this paper, a fully automatized iterative tomographic reconstruction pipeline (rSIRT-PWC-DIFF) designed to reconstruct and segment dynamic processes within a static matrix is presented. The proposed algorithm includes automatic dynamic feature separation through difference sinograms, a virtual sinogram step for interior tomography datasets, time-regularization extended to small sub-regions for increased robustness and an automatic stopping criterion. We demonstrate the advantages of our approach on dynamic fuel cell data, for which the current data post-processing pipeline heavily relies on manual labor. The proposed approach reduces the post-processing time by at least a factor of 4 on limited computational resources. Full independence from manual interaction additionally allows straightforward up-scaling to efficiently process larger data, extensively boosting the possibilities in future dynamic X-ray tomographic investigations.

Separating collected seedlings using subdivided air streams

Large-scale seedling production aims to improve their production capacity and competitiveness by improving productivity, reducing labour costs, and eliminating labour-intensive production processes. With the pursuit of continuously improving productivity, the development of automatic seedling production has become a key technology. However, achieving the automatic separation of rootless collected seedlings into individual plants remains an important challenge because tender rootless seedlings need to be separated into individuals for feeding into seedling production equipment. In this study, a separator composed of subdivided air streams was developed to separate tender collected seedlings into individuals. The air streams for separation were generated by a jetting nozzle array of subdivided air streams at the base of the separator. By opening and closing different subdivided air stream nozzles, in turn, seedlings became suspended with some seedlings at the edge of the floating mass becoming separated. The separator was tested using aubergine and cucumber seedlings intended for grafting and for anthurium seedlings intended for cuttage transplanting. The results demonstrated that the separator could separate tender collected seedlings into individuals without causing damage. Moreover, the maximum separation rates for the collected seedlings were 11,070, 13,590, and 17,100 plants per hour for the aubergine, cucumber, and anthurium seedlings, respectively.

RTM-based dynamic absorption integrals for the retrieval of biochemical vegetation traits

Information about pigment and water contents provides comprehensive insights for evaluating photosynthetic potential and activity of agricultural crops. In this study, we present the concept of using spectral integral ratios (SIR) to retrieve three biochemical traits, namely chlorophyll a and b (Cab), carotenoids (Ccx), and water (Cw) content, simultaneously from hyperspectral measurements in the wavelength range 460−1100 nm. The SIR concept is based on automatic separation of respective absorption features through local peak and intercept analysis between log-transformed reflectance and convex hulls. The algorithm was tested on two synthetically established databases using a physiologically constrained look-up-table (LUT) generated by (i) the leaf optical properties model PROSPECT and (ii) the canopy radiative transfer model (RTM) PROSAIL. LUT constraints were realized based on natural Ccx-Cab relations and green peak locations identified in the leaf optical database ANGERS. Linear regression between obtained SIRs and model parameters resulted in coefficients of determination (R²) of 0.66 (i and ii) for Ccx, R2 = 0.85 (i) and 0.53 (ii) for Cab, and R2 = 0.97 (i) and 0.67 (ii) for Cw, respectively. Using the model established from the PROSPECT LUT, leaf level validation was carried out based on ANGERS data with reasonable results both in terms of goodness of fit and root mean square error (RMSE) (Ccx: R2 = 0.86, RMSE = 2.1 μg cm−2; Cab: R2 = 0.67, RMSE = 12.5 μg cm-2; Cw: R2 = 0.89, RMSE = 0.007 cm). The algorithm was applied to airborne spectrometric HyMap data acquired on 12th July 2003 in Barrax, Spain and to AVIRIS-NG data recorded on 2nd July 2018 southwest of Munich, Germany. Mapping of the SIR results as multiband images (3-segment SIR) allows for intuitive visualization of dominant absorptions with respect to the three considered biochemical variables. Barrax in situ validation using linear regression models derived from PROSAIL LUT showed satisfactory results regarding Cab (R2 = 0.84; RMSE = 9.06 μg cm-2) and canopy water content (CWC, R2 = 0.70; RMSE = 0.05 cm). Retrieved Ccx values were reasonable according to Cab-Ccx-dependence plausibility analysis. Hence, the presented SIR algorithm allows for computationally efficient and RTM supported robust retrievals of the two most important vegetation pigments as well as of water content and is ready to be applied on satellite imaging spectroscopy data available in the near future. The algorithm is publicly available as an interface supported tool within the 'Agricultural Applications' of the EnMAP-Box 3 hyperspectral remote sensing software suite.

Expanded Polytetrafluoroethylene/Graphite Composites for Easy Water/Oil Separation.

Oil spills in the ocean greatly threaten local environments, marine creatures, and coastal economies. An automatic water/oil separation material system was proposed in this study, and a tubular geometry was chosen to demonstrate the water/oil separation efficiency and effectiveness. The water/oil separation tubes were made of expanded polytetrafluoroethylene (ePTFE) and graphite composites. The permeation pressures of water and oil through the tube walls were tuned by adjusting the ePTFE microstructure, which, in turn, depended on the degree of expansion and the graphite content. Fourier-transform infrared spectroscopy was performed to confirm the compositions of the ePTFE/graphite composites, and a scanning electron microscope was used to examine the microstructure and morphology of the expanded PTFE/graphite composite tubes. When a proper pressure was applied, which was higher than the oil's permeation pressure (3.0 kPa) but lower than the water's permeation pressure (57 kPa), the oil leaked out of the tube walls while the water went through the ePTFE/graphite tubes. As such, the water/oil mixture could be separated and collected in different containers or an outer tube. Due to this automatic separation, the whole process could be done continuously and conveniently, thus exhibiting great potential in the practical applications of oil spill and water separation/remediation.

Template-Free Electrochemical Formation of Silicon Nanotubes from Silica.

Silicon, with its elaborate microstructure, plays important roles in energy materials. In operando engineering of microstructure during extraction is an ideal protocol to develop advanced Si‐based materials. A template‐free electrochemical preparation of silicon nanotubes (Si‐NT) is herein achieved by co‐electrolysis of SiO2 and AgCl in molten NaCl–CaCl2 at 850 °C. The in situ electrodeposited Ag facilitates the generation of a liquid Ag–Si intermediate, triggering a liquid–solid mechanism to direct the growth of Si‐NT. An automatic separation of Ag from Si then occurs in the following cooling process, resulting in Ag deposits on the Ni current collector and recycling of Ag. Such a facile and smart preparation of Si‐NT from affordable silica guarantees an enhanced current efficiency of 74%, a decreased energy consumption of 12.1 kW h kgSi −1, and enhanced lithium‐storage capability of the electrolytic Si‐NT. An in situ coating of Ag over the Si‐NT can also be fulfilled by simply introducing soluble AgCl in the melts. The present study provides a template‐free preparation and an in situ surface modification of Si‐NT.

VisEgg: a robust phenotyping tool to assess rainbow trout egg features and viability.

Assessing female fish reproductive success requires a thorough evaluation of egg characteristics, including egg number, size, and variability as well as egg developmental potential through the monitoring of embryo survival after fertilization. While embryonic success relies, at least in part, on paternal contribution, some parameters are strictly related to egg characteristics, one of the main ones being the viability of the egg when released into the water at spawning. It is however not necessarily possible, at least in salmonid fish that lay nontransparent eggs, to separate the different causes of egg/embryo failure. In this context, our aim was (i) to develop a simple and rapid system to capture images of rainbow trout eggs combined with computerized processing of these images to perform a fully automatic individual characterization of egg features including number and size (ii) to estimate unfertilized egg viability through the monitoring of the percentage of eggs that will not survive to water hydration. To evaluate the VisEgg system, unfertilized eggs (approximatively 400 eggs per batch) originating from 105 different females were hydrated in water. After 24 h, a picture of the eggs was obtained using a dedicated shooting system consisting of a light source and a digital single-lens reflex (SLR) camera. An image processing algorithm was developed to allow the automatic detection and separation of the eggs and to perform automatic measurements of egg number and individual egg size. The presence of white egg was used as an indirect measure of egg integrity, the "whitening" being the result of water entry into the egg through the vitelline membrane. These white eggs were therefore considered nonviable, as a result of their lack of physical integrity. Fertilization assays were performed in parallel using a subsample of the same egg batch. Embryonic development was monitored and hatching rate was calculated. A significant correlation between white egg percentage after hydration and hatching rate was observed (Spearman coefficient = -0.557, p < 0.001), in consistency with the fact that nonviable egg will not allow successful embryonic development. In contrast, the percentage of eggs that do not successfully hatch includes egg/embryo failures of different nature including reduced egg viability. Using the VisEgg, we were able to quantify the lack of viability of the eggs separately from the different other events that may occur during fertilization and incubation. the VisEgg is a convenient and reliable tool to obtain individual measures on trout eggs. It can be used to assess not only egg size and egg number but also unfertilized egg viability before fertilization.

One-dimensional convolutional neural networks for acoustic waste sorting

This paper presents a successful application of one-dimensional convolutional neural networks (1D CNNs) for waste sorting at source based on acoustic data. Most of the existing methods use images for waste classification, which causes a high computational complexity and requires a huge amount of training data. Acoustic data have also been employed due to its high correlation to the waste material type. The traditional approaches usually use fixed and handcrafted features extracted from acoustic data. Finding efficient features is usually time consuming and could be difficult in complex situations. In this paper, the 1D CNN method is proposed to automatically extract features from acoustic data and achieve high classification accuracy. Orthogonal experiment method is applied to optimize three key hyper-parameters of the 1D CNN structure. The experiment shows that the proposed method can achieve 92.40% classification accuracy within a short time. A traditional method using handcrafted features with a shallow classifier is taken as a benchmark and the attained classification accuracy is only 81.92%. In addition, a classification accuracy rate of 68.06% is achieved when using a shallow classifier with raw acoustic data as input. Therefore, the proposed method is promising to be practically applied in the trash bins for automatic waste source separation.

Time-Modulated Antenna Array With Dual-Circular Polarization

This letter presents a time-modulated antenna array (TMAA) with a dual-circular (left-hand and right-hand) polarization. The TMAA is composed of a single-pole four-throw radio frequency switch and four linearly polarized elements arranged accordingly to the sequential rotation technique. A periodic switching of the elements leads to generation of sideband components in the frequency domain. The right-hand circular polarization (RHCP) and the left-hand circular polarization (LHCP) are synthesized over the first negative sideband frequency and the first positive sideband frequency, respectively, in wide frequency band. The TMAA used in the receiving mode provides conversion of polarization diversity into frequency diversity, therefore enabling simultaneous reception and automatic separation of two electromagnetic waves, which have the same frequency, however, mutually orthogonal senses of polarization.

Evolutionary intelligence for breast lesion detection in ultrasound images: A wavelet modulus maxima and SVM based approach

Intelligent lesion detection system for medical ultrasound images are aimed at reducing physicians’ effort during cancer diagnosis process. Automatic separation and classification of tumours in ultrasound images is challenging owing to the low contra

Radon spectrogram-based approach for automatic IFs separation

The separation of overlapping components is a well-known and difficult problem in multicomponent signals analysis and it is shared by applications dealing with radar, biosonar, seismic, and audio signals. In order to estimate the instantaneous frequencies of a multicomponent signal, it is necessary to disentangle signal modes in a proper domain. Unfortunately, if signal modes supports overlap both in time and frequency, separation is only possible through a parametric approach whenever the signal class is a priori fixed. In this work, time-frequency analysis and Radon transform are jointly used for the unsupervised separation of modes of a generic frequency modulated signal in noisy environment. The proposed method takes advantage of the ability of the Radon transform of a proper time-frequency distribution in separating overlapping modes. It consists of a blind segmentation of signal components in Radon domain by means of a near-to-optimal threshold operation. The inversion of the Radon transform on each detected region allows us to isolate the instantaneous frequency curves of each single mode in the time-frequency domain. Experimental results performed on constant amplitudes chirp signals confirm the effectiveness of the proposed method, opening the way for its extension to more complex frequency modulated signals.

Design and Analysis of a New Profile Control Tool: Swirling Autonomous Inflow-Control Device

Summary Edge/bottomwater cresting or even breaking into the wellbore has been a major factor affecting crude-oil production and has not been overcome so far. Aiming at this problem, this paper designs a new autonomous inflow-control device (AICD) profile control tool—swirling AICD—on the basis of the research of profile control tools used in the past. The AICD is mainly based on the principle of automatic phase separation, the splitting of three-way pipes, and the principle of vortex depressurization. Combined with the special flow path, the production of edge/bottomwater can be effectively restrained. Computational fluid dynamics (CFD) numerical simulation and indoor flow experiments are used to prove the water-control function of the swirling AICD, to obtain the pressure and velocity distribution of fluid flow in the AICD, and to obtain the influencing factors and their influence rules. Based on these analyses, we established the swirling AICD mathematical model, which has laid a theoretical foundation for the application of swirling AICDs in wells.

Graphdiyne: A Brilliant Hole Accumulator for Stable and Efficient Planar Perovskite Solar Cells.

Traditional carbon materials have demonstrated immense potential in perovskite solar cells (PSCs) owing to their superior electrical properties and environmental stability. Graphdiyne (GDY), as an emerging carbon allotrope, features uniformly distributed pores, endless design flexibility, and unique electronic character compared with traditional carbon materials. Herein, graphdiyne is introduced into the upper part of the perovskite (CH3 NH3 PbI3 ) layer by utilizing a GDY-containing antisolvent during the one-step synthesis of perovskite. Intriguingly, GDY plays an essential role in hole accumulation and transportation because of its higher Fermi level than perovskite. As a result, the automatic separation of photogenerated carriers inside the perovskite film is achieved. Furthermore, the Schottky barrier formed on the interface between perovskite and GDY guarantees the unidirectional hole transport from perovskite to GDY, thereby benefiting further extraction to the hole transport layer. Consequently, GDY-modified perovskite-based planar PSCs exhibit a boosted Jsc of 24.21 mA cm-2 and up to 19.6% power conversion efficiency owing to the increased efficient light utilization and charge extraction. The device with GDY modification exhibits less than 10% shrinkage after a month in ambience. Overall, this work demonstrates an easy method for the utilization of GDY to boost the charge extraction and environmental stability in PSCs.