Charge-coupled Device Imaging Research Articles

A Novel Linear CCD Variable Velocity Two-Dimensional Imaging Approach Based on Adaptive Image Segmentation

Linear charge coupled device (CCD) camera has been widely used in industrial manufacturing and science research because of its capability of high-resolution digital imaging. To reduced imaging distortion caused by scanning velocity variation, a novel linear CCD variable velocity 2-D imaging approach based on adaptive image segmentation is proposed in this article. An adaptive image segmentation algorithm is presented to calculate the size of image segmentation according to variable scanning velocity. A velocity curve fitting based on discrete interpolation is designed to obtain the scanning velocity in each image segment. Then, by using scanning velocity in each segment, compensation coefficient at each segment is calculated and a cubic spline interpolation based pixel interpolation transformation algorithm is designed to obtain the whole corrected image. Finally, the proposed approach is implemented in a printed circuit board (PCB) linear CCD imaging experiments and the results demonstrated its efficiency.

Cryogenic characteristics of GaAs-based near-infrared light emitting diodes

High performance infrared light emitting diodes (LEDs) have drawn wide attention because of their significant applications in biomedicine, agriculture, aquaculture, night vision security systems and scientific researches. Due to the rapid development of infrared up-conversion devices, especially in the terahertz region, the studies on the GaAs-based infrared LEDs operating at low temperature (<20 K) are quite needed. In this paper, two representative GaAs-based LEDs (GaAs/AlGaAs double heterostructure LED (DH-LED) and GaAs (InGaAs)/AlGaAs quantum well infrared LED (QW-LED)) are fabricated and characterized with electroluminescence (EL) spectroscopy and electroluminescence efficiency (ELE) at different temperatures. The ELE of the QW-LED is about 70% higher at low temperatures (<150 K) but lower at high temperatures (>150 K) than that of the DH-LED. A developed rate equation method is used to analyze the ELE superiority of the QW-LED. Finally, the surface EL uniformity of the two LEDs is studied by using the charge coupled devices imaging. This study provides a guidance to choose and design LED structures for different operation temperatures.

Effects of particle type on the particle distribution in a two-pass circulating fluidized bed evaporator with baffle

To enhance heat transfer, as well as prevent and remove fouling, a two-pass circulating fluidized bed evaporator with baffle has been designed and built. The uniformity of particle distribution significantly influences the performance of evaporator. This paper mainly researches the influences of particle types on the particle distribution with a Charge Couple Device image measurement and acquisition system. Consequently, for four kinds of particles, particle distributions in the up-flow bed are relatively uniform; those in the down-flow bed become more uniform with the increase of circulation flow rate and decline of particle amount and baffle height. Particle maldistribution becomes obvious with the increase of particle density. Furthermore, particles with greater density are more susceptible to the operating parameters, and the increase of circulation flow rate can weaken the influences of particle amount and baffle height. Finally, phase diagrams are established to show the optimal range of the operating parameters.

Automatic Astronomical Survey Method Based on Video Measurement Robot

AbstractUtilizing charge-coupled device (CCD) imaging technology in astronomical surveying and positioning facilitates high-precision measurements without manual observation. This eliminates the in...

A note of optical error diagnosis of parabolic trough concentrator based on flux image

In practical applications, there are many optical errors in the parabolic trough concentrators (PTC), such as mirror slope errors and tracking errors. Image detection is a no contact technique that has a potential to diagnose the optical errors at large plants in use. In this study, a CCD (Charge Coupled Device) camera was used to directly observe the absorber, and the images of the flux peaks were successful obtained. The CCD image showed two bright peaks on the outer wall of the tubular absorber. By comparing the CCD image with the simulation results, the concave deformation of the parabolic mirror was diagnosed, and the slope error of the parabolic mirror was figured out. The images also revealed that sun tracking errors can cause a synchronous shift in the flux. The flux image method does not influence the normal operation of PTC and is an on-line method, which facilitates the field application.

Research progress on color determination methods of reagent strips in routine urinalysis

Clinically, routine urinalysis includes more than 10 items, such as urine protein, urinary pH, urinary bilirubin and so on. The above items are usually analyzed by dry chemical methods. The principle is that after the urine infiltrates the reagent strips, the color changes can be observed in each strip. The color depth is related to the component concentration, and the darker the color, the greater the measured component concentration, and vice versa. In this paper, four color discrimination methods in urinary dry chemical analysis were introduced, i.e. the method based on integrating sphere photoelectric conversion, the method based on charge-coupled device (CCD) image sensor, the method based on color sensor, and the method based on the combination of color sensor and fiber bundle. Besides, the four methods were compared and analyzed. Finally, the recent research progress in urinalysis was reviewed. Key words: Urine; Dry chemical method; Color; Urine reagent strip

Development of low-cost multi-wavelength imager system for studies of aurora and airglow

This paper introduces a new system that can monitor aurora and atmospheric airglow using a low-cost Watec monochromatic imager (WMI) equipped with a sensitive camera, a filter with high transmittance, and the non-telecentric optics. The WMI system with 486-nm, 558-nm, and 630-nm band-pass filters has observable luminosity of about ~200–4000 Rayleigh for 1.07-sec exposure time and about ~40–1200 Rayleigh for 4.27-sec exposure time, for example. It is demonstrated that the WMI system is capable of detecting 428-nm auroral intensities properly, through comparison with those measured with a collocated electron-multiplying charge-coupled device (EMCCD) imager system with narrower band-pass filter. The WMI system has two distinct advantages over the existing system: One makes it possible to reduce overall costs, and the other is that it enables the continuous observation even under twilight and moonlight conditions. Since 2013 a set of multi-wavelength WMIs has been operating in northern Scandinavia, Svalbard, and Antarctica to study meso- and large-scale aurora and airglow phenomena. Future development of the low-cost WMI system is expected to provide a great opportunity for constructing a global network for multi-wavelength aurora and airglow monitoring.

Time-resolved imaging of streamer formation inside gaseous bubbles in liquids

Bulk liquid conditions can impact how plasma discharges behave in bubbles and affect the future implementation of plasma technologies for water treatment. A 2D plasma-in-liquid apparatus was used to investigate the effects of liquid conductivity on the propagation of nanosecond pulsed streamers in bubbles. ANSYS Maxwell was used to model the resulting static electric field. Electric field enhancement was found at the contact point between the bubble surface and the plexiglass, and can direct propagation of observed discharges. Nanosecond exposure time intensified charge-coupled device imaging was used to photograph the temporal development of the streamers in the bubble. At high liquid conductivity, surface hugging streamers stalled out axial streamers. However, at lower conductivity, increase in charge relaxation time and presence of charge carriers became important. Deposited charges on the interface led to development of opposing electric field and terminated streamer development. Presence of organic contaminants can increase conductivity of surface water. To maximize energy efficiency of future plasma-based water treatment reactor, it is important to take liquid conductivity into consideration. Shorter pulse width and rise time can potentially minimize development of surface hugging streamers, which is a major source of charge dissipation and thermal effects.

Plasma-Enhanced Catalytic Synthesis of Ammonia over a Ni/Al2O3 Catalyst at Near-Room Temperature: Insights into the Importance of the Catalyst Surface on the Reaction Mechanism.

A better fundamental understanding of the plasma-catalyst interaction and the reaction mechanism is vital for optimizing the design of catalysts for ammonia synthesis by plasma-catalysis. In this work, we report on a hybrid plasma-enhanced catalytic process for the synthesis of ammonia directly from N2 and H2 over transition metal catalysts (M/Al2O3, M = Fe, Ni, Cu) at near room temperature (∼35 °C) and atmospheric pressure. Reactions were conducted in a specially designed coaxial dielectric barrier discharge (DBD) plasma reactor using water as a ground electrode, which could cool and maintain the reaction at near-room temperature. The transparency of the water electrode enabled operando optical diagnostics (intensified charge-coupled device (ICCD) imaging and optical emission spectroscopy) of the full plasma discharge area to be conducted without altering the operation of the reactor, as is often needed when using coaxial reactors with opaque ground electrodes. Compared to plasma synthesis of NH3 without a catalyst, plasma-catalysis significantly enhanced the NH3 synthesis rate and energy efficiency. The effect of different transition metal catalysts on the physical properties of the discharge is negligible, which suggests that the catalytic effects provided by the chemistry of the catalyst surface are dominant over the physical effects of the catalysts in the plasma-catalytic synthesis of ammonia. The highest NH3 synthesis rate of 471 μmol g–1 h–1 was achieved using Ni/Al2O3 as a catalyst with plasma, which is 100% higher than that obtained using plasma only. The presence of a transition metal (e.g., Ni) on the surface of Al2O3 provided a more uniform plasma discharge than Al2O3 or plasma only, and enhanced the mean electron energy. The mechanism of plasma-catalytic ammonia synthesis has been investigated through operando plasma diagnostics combined with comprehensive characterization of the catalysts using N2 physisorption measurements, X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), NH3-temperature-programmed desorption (TPD), and N2-TPD. Four forms of adsorbed NHx (x = 0, 1, 2, and 3) species were detected on the surfaces of the spent catalysts using XPS. It was found that metal sites and weak acid sites could enhance the production of NH3 via formation of NH2 intermediates on the surface.

Ignition of A Plasma Discharge Inside An Electrodeless Chamber: Methods and Characteristics

In this paper the generation and diagnostics of a reduced pressure (300 mTorr to 3 Torr) plasma generated inside an electrodeless containment vessel/chamber are presented. The plasma is ignited by a guided ionization wave emitted by a low temperature pulsed plasma jet. The diagnostics techniques include Intensified Charge Coupled Device (ICCD) imaging, emission spectroscopy, and Langmuir probe. The reduced-pressure discharge parameters measured are the magnitude of the electric field, the plasma electron number density and temperature, and discharge expansion speed.

Labeling Confidence Values for Wafer-Handling Robot Arm Performance Using a Feature-Based General Regression Neural Network and Genetic Algorithm

The prognosis and management of machine health statuses are emerging research topics. In this study, the performance degradation of a wafer-handling robot arm (WHRA) was predicted using the proposed machine-learning approach. This method considers the eccentric vertical and planar position deviations from a wafer mark using a charge-coupled device (CCD) camera. Synthesized position signals were defined using the square root of x- and y-axes deviations in the horizontal view and the square of the wafer mark diameter in the vertical view. A feature extraction method was used to determine the position status on the basis of these displacements and the area of a wafer mark in a CCD image. The root mean square error and mean, maximum, and minimum of the synthesized position signals were extracted through feature extraction and used for data mining by a general regression neural network (GRNN) and logistic regression (LR) models. The lifetime assessment by confidence value of the WHRA’s remaining useful life (RUL) by the genetic algorithm/GRNN exhibited nearly the same trend as that predicted through a run-to-failure LR model. The experimental results indicated that the proposed methodology can be used for proactive assessments of the RUL of WHRAs.

Low Cost Laser Speckle Imaging System for Blood Flow Assessment

This paper aims to demonstrate the feasibility of using a low cost laser speckle imaging built for the detection of changes of tissue blood flow with different experimental conditions. Images of anterior portion of the wrist of four healthy adult volunteers illuminated by a laser source of wavelength 650 nm were collected via a monochromatic charge-coupled device (CCD) imager. The mean and standard deviation (SD) of blood flow perfusion was predicted as 3.92 ± 1.47 and 2.90 ± 1.39, respectively, for measurements at rest condition and during blood flow occlusion. This work showed the ability of the developed system to detect changes in blood flow perfusion with differences in the experimental conditions. However, further works are required to further confirm the suitability of the system before it is used for different clinical applications such as monitoring of blood flow during diabetic foot ulcers healing following standard medical treatment.

Experimental Investigation on the Influence of Target Physical Properties on an Impinging Plasma Jet

The present work aims to investigate the interaction between a plasma jet and targets with different physical properties. Electrical, morphological and fluid-dynamic characterizations were performed on a plasma jet impinging on metal, dielectric and liquid substrates by means of Intensified Charge-Coupled Device (ICCD) and high-speed Schlieren imaging techniques. The results highlight how the light emission of the discharge, its time behavior and morphology, and the plasma-induced turbulence in the flow are affected by the nature of the target. Surprisingly, the liquid target induces the formation of turbulent fronts in the gas flow similar to the metal target, although the dissipated power in the former case is lower than in the latter. On the other hand, the propagation velocity of the turbulent front is independent of the target nature and it is affected only by the working gas flow rate.

Unsteady interaction of nanosecond surface sliding discharge with plane shock wave

In this study, we present experimental results on fast intensified charge-coupled device imaging and current measurements of a nanosecond surface sliding discharge interacting with a plane shock wave in a shock tube. A shock wave with Mach number 1.9–3.5 passed through the discharge area while the electric pulse was switched on. The discharge is initiated by a voltage pulse of 25 kV; the discharge current is ∼1 kA. The discharge current in high-speed airflows including plane shock waves has been measured and the dynamics of the discharge radiation was studied with the nanosecond time resolution. It is shown that the inhomogeneity of the airflow-density field leads to a change in the discharge current and the structure of the discharge radiation strongly depending on the shock wave position in the discharge gap. The dynamics of the energy input is determined by the interaction of the shock wave with the discharge region, as measurements of the discharge current reveal.

Automatic Identification of Tool Wear Based on Convolutional Neural Network in Face Milling Process.

Monitoring of tool wear in machining process has found its importance to predict tool life, reduce equipment downtime, and tool costs. Traditional visual methods require expert experience and human resources to obtain accurate tool wear information. With the development of charge-coupled device (CCD) image sensor and the deep learning algorithms, it has become possible to use the convolutional neural network (CNN) model to automatically identify the wear types of high-temperature alloy tools in the face milling process. In this paper, the CNN model is developed based on our image dataset. The convolutional automatic encoder (CAE) is used to pre-train the network model, and the model parameters are fine-tuned by back propagation (BP) algorithm combined with stochastic gradient descent (SGD) algorithm. The established ToolWearnet network model has the function of identifying the tool wear types. The experimental results show that the average recognition precision rate of the model can reach 96.20%. At the same time, the automatic detection algorithm of tool wear value is improved by combining the identified tool wear types. In order to verify the feasibility of the method, an experimental system is built on the machine tool. By matching the frame rate of the industrial camera and the machine tool spindle speed, the wear image information of all the inserts can be obtained in the machining gap. The automatic detection method of tool wear value is compared with the result of manual detection by high precision digital optical microscope, the mean absolute percentage error is 4.76%, which effectively verifies the effectiveness and practicality of the method.

Mapping Rice Paddies in Complex Landscapes with Convolutional Neural Networks and Phenological Metrics

ABSTRACTRice mapping with remote sensing imagery provides an alternative means for estimating crop-yield and performing land management due to the large geographical coverage and low cost of remotely sensed data. Rice mapping in Southern China, however, is very difficult as rice paddies are patchy and fragmented, reflecting the undulating and varied topography. In addition, abandoned lands widely exist in Southern China due to rapid urbanization. Abandoned lands are easily confused with paddy fields, thereby degrading the classification accuracy of rice paddies in such complex landscape regions. To address this problem, the present study proposes an innovative method for rice mapping through combining a convolutional neural network (CNN) model and a decision tree (DT) method with phenological metrics. First, a pre-trained LeNet-5 Model using the UC Merced Dataset was developed to classify the cropland class from other land cover types, i.e. built-up, rivers, forests. Then, paddy rice field was separated from abandoned land in the cropland class using a DT model with phenological metrics derived from the time-series data of the normalized difference vegetation index (NDVI). The accuracy of the proposed classification methods was compared with three other classification techniques, namely, back propagation neural network (BPNN), original CNN, pre-trained CNN applied to HJ-1 A/B charge-coupled device (CCD) images of Zhuzhou City, Hunan Province, China. Results suggest that the proposed method achieved an overall accuracy of 93.56%, much higher than those of other methods. This indicates that the proposed method can efficiently accommodate the challenges of rice mapping in regions with complex landscapes.

Novel pendrin inhibitor attenuates airway hyperresponsiveness and mucin expression in experimental murine asthma

Novel pendrin inhibitor attenuates airway hyperresponsiveness and mucin expression in experimental murine asthma

Aerostatic moving stage positioning compensation using a numerical algorithm combined with an image acquisition method

In this study, positioning error measurements and compensation techniques were developed for a two-dimensional (2D) coplanar aerostatic system. Standard optical template targets were acquired using charge-coupled device (CCD) image acquisition; after which, positioning errors were measured and compensated for. A 2D Lagrange equation was utilized to compensate for the precision of the precision aerostatic system. Experimental results showed that X- and Y-axis positioning accuracy improved from 5.06 to 1.53 μm and from 3.99 to 1.06 μm, respectively, signifying improvements of over 70%.

Thermal and Optical Study on the Frequency Dependence of an Atmospheric Microwave Argon Plasma Jet

This paper presents the frequency- and power-dependent thermal and spectral properties of a microwave argon plasma jet in the gigahertz range. These properties are determined at 1.3 GHz, 2.4 GHz, and 3.5 GHz for input powers from 2 W to 15 W and gas-flows from 1 to 4 Lm−1, including the influence of an argon/nitrogen mixture. These investigations are performed to determine the specific influence of the excitation frequency on the spectral properties of the plasma. The gas temperature is determined via the hydroxyl radical (OH) rotational band around 310 nm by fitting the simulated spectrum to the measurements. It is shown that high temperatures above 1350 K are generated inside the plasma for an input power of 10 W. At the same time, selective discharge 2-D mapping is realized as a result of charge-coupled device (CCD) imaging through optical bandpass filters, corresponding to the OH, N2, Ar, and H spectral emission lines. It is found that all the investigated species change their size proportional to the size of the plasma. Influence of nitrogen is investigated by generating an argon/nitrogen gas mixture. The nitrogen admixtures up to 2% are examined. These investigations are based on measurements of the N2-band around 370 nm. A strong dependence of the discharge appearance on the nitrogen content is found.

Remote examination of the seasonal succession of phytoplankton assemblages from time-varying trends

The seasonal succession of phytoplankton assemblages is important to ascertain the dynamics of an aquatic ecosystem structure, whereas its occurrence in response to hydrodynamic alterations is not clearly understood. In view of the characteristics of annual water level variation formed by the Three Gorges Dam Project (TGDP), our understanding about how these changes affect phytoplankton structure and dynamics is still very limited due to the shortage of long-term observation data. In this study, we used Huan Jing 1 charge-coupled device images over the past decade to examine the phytoplankton succession dates between cyanobacterial and green algal blooms in the backwater area of the Three Gorges Reservoir (TGR). The results indicated continuous wavelet transform-based peak analysis is an efficiency tool that can illustrate the temporal pattern of phytoplankton succession using satellite-derived chlorophyll ɑ and Cyano-Chlorophyta index thresholds. Water level, air temperature, pH and total nitrogen/total phosphorus ratio were four important factors affecting the decline and rise phase of cyanobacterial blooms in the TGR from 2008 to 2018. Given that the upstream dam operation is likely to alter ecological and environmental conditions in the backwater area, this mechanism, so-called “water-level linkage”, could alleviate the persistent period of cyanobacterial and green algal blooms. Remote sensing together with time series analysis provided a useful method to examine the seasonal succession of phytoplankton assemblages in the TGR, and these findings provided strategic insight for the water-quality management in the post-TGDP period.