Acquisition Design Research Articles

Vacuum booster control system design and fault self-check strategies

In this paper, the software and hardware design of the vehicle vacuum pump control system was carried out based on single-chip microcomputer technology. Combined with the vacuum pump structure and control principle, the hardware design of the power supply, barometric pressure sensor, vacuum pressure sensor, current detection, and motor drive is carried out with the HS08 series single-chip microcomputer as the core. The software strategy design for barometric pressure signal acquisition, vacuum pressure signal acquisition, and vacuum pump driving has been completed, and the dual pressure vacuum pump control system for electric vehicles has been developed. The system can diagnose the common faults of the vacuum power system. Finally, the functional test of the control system is carried out. The results show that the system can work normally and that the design meets the expected requirements.

Narrow beam breast CT: proof-of-concept.

In breast CT, scattered photons form a large portion of the acquired signal, adversely impacting image quality throughout the frequency response of the imaging system. Prior studies provided evidence for a new image acquisition design, dubbed Narrow Beam Breast CT (NB-bCT), in preventing scatter acquisition. Here, we report the design, implementation, and initial characterization of the first NB-bCT prototype. The imaging system's apparatus is composed of two primary assemblies: a dynamic Fluence Modulator (collimator) and a photon-counting line detector. The design of the assemblies enables them to operate in lockstep during image acquisition, converting sourced x-rays into a moving narrow beam. During a projection, this narrow beam sweeps the entire fan angle coverage of the imaging system. The assemblies are each comprised of a metal housing, a sensory system, and a robotic system. A controller unit handles their relative movements. To study the impact of fluence modulation on the signal received in the detector, three physical breast phantoms, representative of small, average, and large size breasts, were developed and imaged, and acquired projections analyzed. The scatter acquisition in each projection as a function of breast phantom size was investigated. The imaging system's spatial resolution at the center and periphery of the field of view was measured. Minimal acquisition of scattered rays occurs during image acquisition with NB-bCT; results in minimal scatter to primary ratios in small, average, and large breast phantoms imaged were 0.05, 0.07, and 0.9, respectively. System spatial resolution of 5.2 lp/mm at 10% max MTF and 2.9 lp/mm at 50% max MTF at the center of the field of view was achieved, with minimal loss with the shift toward the corner (5.0 lp/mm at 10% max MTF and 2.5 lp/mm at 50% max MTF). The disclosed development, implementation, and characterization of a physical NB-bCT prototype system demonstrates a new method of CT-based image acquisition that yields high spatial resolution while minimizing scatter-components in acquired projections. This methodology holds promise for high-resolution CT-imaging applications in which reduction of scatter contamination is desirable.

Novel tunable current feedback instrumentation amplifier based on BBFC OP-AMP for biomedical applications with low power and high CMRR

The paper presents a novel low power, low noise and high CMRR current feedback instrumentation amplifier (CFIA) design for biomedical signal acquisition i.e. EEG/ECG applications is presented. The proposed instrumentation amplifier performance is evaluated using 0.18μm, CMOS technology with 1.8 V supply and results are obtained in Cadence EDA tool. The proposed CFIA is implemented using a dual output bandwidth boosted folded cascode operational amplifier (BBFC OP-AMP) active block. In this paper the proposed CFIA performance parameters has been considered for optimization to get better results by using the idea of signal to noise ratio (SNR) with Taguchi design of experiments (Taguchi DoE) and analysis of variance (ANOVA) to estimate the most important independent variable which control the performance of the design. The bias voltage, channel length and width of input MOS transistors have been selected to optimize the proposed circuit performance. The proposed CFIA structure have 50.33 to 69.67 dB tunable differential gain, common mode rejection ratio (CMRR) of 143.19 dB, tunable bandwidth of 148.24 kHz to 1.31 MHz, dynamic range (DR) of 74.31 dB and 297.73 dB of figure of merit (FoM). The CFIA shows an equivalent input referred noise (IRN) of 0.586 μV at 0.1 Hz to 148.24 kHz frequency range, with total power dissipation of 102.73 μW and occupies 8194μm2 of core area. The simulation results of the proposed CFIA are close to the predicted solution obtained from ANOVA. The PVT analysis and post layout simulation has been performed to check the robustness of the proposed design. The proposed design has been compared with the other existing literature which shows the competence of the design.

Carrier recovery for satellite-to-ground coherent laser communication systems using double feedback loop and Viterbi–Viterbi feedforward cascade structure

High dynamic and wide range frequency offset in satellite-to-ground coherent optical communication system caused by Doppler frequency shift, transceiver laser frequency offset and laser frequency stabilization technology based on perturbation is one of the important differences compared with terrestrial fiber-optic coherent transmission. The design of a reliable frequency offset acquisition and fine carrier tracking algorithm is critical to ground optical stations. Two-stage feedback loop and Viterbi–Viterbi (V–V) feedforward cascaded carrier recovery algorithm is presented in this work. Pre-decision-based angle differential estimator (PADE) is adopted as the residual frequency offset (RFO) estimator in the first stage to estimate the high dynamic and wide range of frequency offset. Then V–V based RFO estimator in the second stage is employed to accurately compensate the residual frequency. V–V algorithm is used to compensate phase offset, which share the same logic resource with V–V based RFO estimator. A real-time 10-Gbps data rate PM-QPSK experiment based on FPGA is performed to evaluate the algorithm performance. The proposed cascaded algorithm exhibits excellent performance in terms of dynamic tracking speed and normalized mean-square-error (MSE) of the FOE.

Differential absorption lidar data acquisition and control system for remote detection of trace chemicals including methane and thiodiglycol.

We report the design and development of a data acquisition and control system for high-speed acquisition of weak, backscattered differential signals and synchronized sequential operation of all subsystems of a tunable, mid-infrared Differential Absorption Lidar (DIAL) system. The presence of a low-level concentration of chemical species results in weak differential return signals. The differential signal also varies dynamically with respect to background atmospheric conditions. The challenge is to measure this low level of differential signal with high resolution and also control the sequence of operation of subsystems such as lasers and scanners for real time testing and evaluation in open field conditions. The concentration spread of the chemical species varies rapidly with distance. In order to capture this spatial variation, the lidar signal should be sampled and digitized at a high sampling rate. A customized Peripheral Component Interconnect based data acquisition of a 12-bit resolution, 30 Mega samples per second sampling rate, and an industrial personal computer-based control system has been realized. Detection algorithms and the firing sequence of the laser have been developed indigenously and implemented in the LabVIEW platform. The developed graphical user interface has various modes of operation as per user requirement and is capable of executing automatic operations for the developed DIAL system in order to detect and identify the chemicals. The performance has been evaluated by detecting the chemical species thiodiglycol at 800m using 3190 and 3300nm (online and offline wavelengths) with a differential cross-section of 2.5 × 10-23m2. Similarly, methane has been detected and quantified with concentration of 2.2 ppm up to 300m using 3316 and 3326nm (online and offline wavelengths, respectively).

Review of electrooculography-based human-computer interaction: recent technologies, challenges and future trends

Electrooculography-based Human-Computer Interaction (EOG-HCI) is an emerging field. Research in this domain aims to capture eye movement patterns by measuring the corneal-retinal potential difference. This enables translating eye movements into commands, facilitating human-computer interaction through eye movements. This paper reviews articles published from 2002 to 2022 in the EOG-HCI domain, aiming to provide a comprehensive analysis of the current developments and challenges in this field. It includes a detailed and systematic analysis of EOG signal electrode arrangement, hardware design for EOG signal acquisition, commonly used features, and algorithms. Representative studies in each section are presented to help readers quickly grasp the common technologies in this field. Furthermore, the paper emphasizes the analysis of interaction design within the EOG-HCI domain, categorizing different interaction task types and modalities to provide insights into prevalent interaction research. The focus of current research in the field is revealed by examining commonly used evaluation metrics. Lastly, a user-centered EOG-HCI research model is proposed to visually present the current research status in the EOG-HCI field from the perspective of users. Additionally, we highlight the challenges and opportunities in this field.

Optimal Matching Full Waveform Inversion

The conventional least squares full waveform inversion compares the seismograms point by point. It loses the inter-receiver coherency along the spatial axis, and loses the inter-event coherency along the temporal axis. Optimal transport is a global comparison algorithm. However, extending it to high dimensions is challenging due to high computation cost and often irregular acquisition design. This study proposes an optimal matching function. Each receiver is represented by an extended vector attribute containing the seismic signals and its spatial coordinates. A cost matrix is calculated for each pair of receivers. An optimal path is located in the cost matrix, which indicates whether two receivers match. This algorithm avoids point by point comparison, also it decreases the computation by collapsing one dimension. Two modes of the optimal matching function are developed: balanced mode and unbalanced mode. The optimal matching function is extensively examined in several models. In the Marmousi-II model experiment, the performances of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> norm function, the optimal transport function, and the optimal matching function are evaluated and compared. The best velocity is obtained by the optimal matching function. The second inversion experiment is conducted with the Middle East model. Both of the balanced and the unbalanced mode recovers the velocity model starting from a linear initial model. The optimal matching function is not limited to acoustic full waveform inversion. In the final inversion experiment with the elastic SEG/EAGE overthrust model, the optimal matching function interprets both of the body and surface waves, and recovers the velocity parameters.

From FWI to ultra-high-resolution imaging

In recent years, the development of time-lag full-waveform inversion (FWI) has enabled the use of the full wavefield (primary reflections, diving waves, and their multiples and ghosts) in the inversion process. With this advancement, it is possible to obtain a very detailed velocity model, ultimately reaching the point of deriving from the velocity a migration-like reflectivity image called the FWI image. When the FWI maximum frequency is increased, high-resolution velocity models are obtained, revealing superior reservoir information compared to conventional imaging results. Two case studies will be discussed in this paper. The first is in the Greater Castberg area where the 150 Hz FWI image greatly surpassed the Q Kirchhoff prestack depth migration image from the water-bottom level down to the reservoir (located at a depth of about 1.5 km). The second case study is over the Nordkapp Basin. The use of the full wavefield for the shallow ultra-high-resolution (UHR) FWI image (run at 200 Hz) revealed reverse faulting and pockmark details that were invisible with Kirchhoff prestack depth migration and reverse time migration. By using additional information present in multiples, ghosts, and diving waves, a spatial resolution down to 3 m was achieved. This made it possible to image very thin features without the need for a dedicated high-resolution acquisition design. The current UHR FWI image workflow provides velocity and reflectivity information in the near surface that is important in identifying optimal locations for various purposes such as well placement and wind-turbine installation.

Optimal Seismic Sensor Placement Based on Reinforcement Learning Approach: An Example of OBN Acquisition Design

Seismic acquisition costs are directly associated with the number of sensors used in the survey. Limiting the number of sensors in a seismic survey can be beneficial, especially when sensors are expensive to purchase, deploy, and maintain. This work explores an optimal design method for ocean bottom node (OBN) detector deployment. The proposed method is based on a reinforcement learning approach. We assume access to an initial dataset over the area of study. These data are used to extract an over-complete pre-learned basis library via the proper orthogonal decomposition method, which leads to a fast least-squares seismic data reconstruction algorithm. Then, the sensor selection procedure entails using Q-learning to find the sensor configuration that maximizes the reconstruction quality.

Spectral Gap-Based Seismic Survey Design

Seismic imaging in challenging sedimentary basins and reservoirs requires acquiring, processing, and imaging very large volumes of data (tens of terabytes). To reduce the cost of acquisition and the time from acquiring the data to producing a subsurface image, novel acquisition systems based on compressive sensing (CS), low-rank matrix recovery (LRMR), and randomized sampling have been developed and implemented. These approaches allow practitioners to achieve dense wavefield reconstruction from a substantially reduced number of field samples. However, designing acquisition surveys suited for this new sampling paradigm remains a critical and challenging role in oil, gas, and geothermal exploration. Typical random designs studied in the LRMR and CS literature are difficult to achieve by standard industry hardware. For practical purposes, a compromise between stochastic and realizable samples is needed. In this article, we propose a deterministic and computationally cheap tool to alleviate randomized acquisition design, prior to survey deployment and large-scale optimization. We consider universal and deterministic matrix completion results in the context of seismology, where a bipartite graph representation of the source–receiver layout allows for the respective spectral gap (SG) to act as a quality metric for wavefield reconstruction. We provide realistic scenarios to demonstrate the utility of the SG as a flexible tool that can be incorporated into existing survey design workflows for successful seismic data acquisition via low-rank and sparse signal recovery.

Design and Validation of a Modular Control Platform for a Voltage Source Inverter

Integrating renewable energies, such as wind or photovoltaic, requires an electronic power converter, the three-phase Voltage Source Inverter (VSI) the most common for such function. This paper presents a modular design of signal acquisition and control hardware (current and voltage) for the commercial SEMIKRON SKS35F VSI converter and a Texas Instruments TMS320F28335 DSP. Consequently, the proposed modular and open-source design allows its application in control systems of a VSI converter for isolated or grid-connected systems, applied to power generation based on renewable sources. The proposed scheme allows for a personalised design since it uses an open architecture to implement its own control algorithms that allow it to adapt to the application’s particular needs, unlike closed-architecture commercial equipment. Detailed electronic printed circuit board designs for implementation are shown on paper. Finally, the experimental tests’ results that validate the proposed design’s correct functioning are presented.

Venc Design and Velocity Estimation for Phase Contrast MRI.

In phase-contrast magnetic resonance imaging (PC-MRI), spin velocity contributes to the phase measured at each voxel. Therefore, estimating velocity from potentially wrapped phase measurements is the task of solving a system of noisy congruence equations. We propose Phase Recovery from Multiple Wrapped Measurements (PRoM) as a fast, approximate maximum likelihood estimator of velocity from multi-coil data with possible amplitude attenuation due to dephasing. The estimator can recover the fullest possible extent of unambiguous velocities, which can greatly exceed twice the highest venc. The estimator uses all pairwise phase differences and the inherent correlations among them to minimize the estimation error. Correlations are directly estimated from multi-coil data without requiring knowledge of coil sensitivity maps, dephasing factors, or the actual per-voxel signal-to-noise ratio. Derivation of the estimator yields explicit probabilities of unwrapping errors and the probability distribution for the velocity estimate; this, in turn, allows for optimized design of the phase-encoded acquisition. These probabilities are also incorporated into spatial post-processing to further mitigate wrapping errors. Simulation, phantom, and in vivo results for three-point PC-MRI acquisitions validate the benefits of reduced estimation error, increased recovered velocity range, optimized acquisition, and fast computation. A phantom study at 1.5T demonstrates 48.5% decrease in root mean squared error using PRoM with post-processing versus a conventional "dual-venc" technique. Simulation and 3T in vivo results likewise demonstrate the proposed benefits.

ENVIRONMENTALAND GEOPHYSICAL IMPLICATIONS OF DRILLING TECHNIQUESEMPLOYED IN ONSHORE SEISMIC DATA ACQUISITION

Seismic survey which primarily involves using artificially generated seismic energy to examine the subsurface is a common exploration practice in Nigeria. The manner which seismic exploration is carried out affects not only the expected outcome but also the environment, the flora and fauna. In this study, implications of employing the following drilling techniques, the single deep hole technique and the pattern drilling technique were x-rayed as it affects the expected sampling of the subsurface and the human environment in line with the united nations sustainable development goals on sustainable environment and energy.To achieve this assessment, a 3D seismic acquisition design was employed within the study area, having a survey block consisting of 30 receiver lines oriented northeast to southwest, and 47 source lines running northwest to southeast. Safe shooting distances for acquisition were stipulated as a guide to preserve the environment and as well achieve the desired result. Linear acquisition was not consistently carried out due to some obstacles seen within the lines; hence, different types of point movement or offset were employed depending on the type of obstacle encountered. The following offset types - point shift, smooth curve and laminar flow were employed when obstacles were encountered on line. In this research, different drilling techniques, Single Deep Hole (SDH) and Pattern Drilling techniques were considered to ascertain the one with most desirable output, having the least negative impact on personnel, equipments, environment etc. SDH was adjudged to give a better result and with least or no environmental implications as compared to pattern drilling technique. Challenges of drilling operations which include drilling on wrong positions, drilling substandard depths, inaccurate measurement of hole spacing and stuck drilling stems were encountered minimally, and measures were taken to effect correction

Design and Development of Real-Time Data Acquisition of Photovoltaic Panel Parameters via IoT

Abstract In recent years,there has been an urgent need in world for electricity. It has being increased constantly with the expansion of energy consumption via traditional energy sources which are depleting. The world has needed to turn to alternative energy, which is represented by renewable energy. The most important and most efficient of these is solar energy, and to get the maximum value of this energy with the highest efficiency, there should be direct monitoring of the performance of these solar panels. So, in this study, the Internet of Things (IoT) was used as a remote monitoring system to obtain the main factors like load current, terminal voltage, consumption power, temperature, humidity, and light intensity. The values were real and accurate, depending on the use of Adriano and sensors to measure the above-mentioned determinants and then using Wi-Fi technology to send the data that was processed in the circuit. Then the thing speak platform was used to display, analyze, and store the results in real-time

Design and Implementation of a Data Acquisition and Processing Method for Precisely Calculating the Location Errors of Five-Axis CNC Machine Tools

Computer-Aided Design and Applications is an international journal on the applications of CAD and CAM. It publishes papers in the general domain of CAD plus in emerging fields like bio-CAD, nano-CAD, soft-CAD, garment-CAD, PLM, PDM, CAD data mining, CAD and the internet, CAD education, genetic algorithms and CAD engines. The journal is aimed at all developers and users of CAD technology to ptovide CAD solutions for various stages of design and manufacturing. The journal publishes all about Computer-Aided Design and Computer-Aided technologies.

Design of Image Acquisition System Based on Visual Intelligent Sensor and Video Signal Processing

With the rapid development and iteration of CMOS image sensor and other related technologies, in addition to the more advanced technology, the corresponding sensor also integrates the image signal processing system, so it is a leap for the image acquisition system. Based on this, this paper will take the visual intelligent sensor produced and developed by a semiconductor company as the hardware to complete the hardware design of the image acquisition and transmission system. In addition to the core processor of the system, this paper will also use audio and video processing chips and image data processing chips for collaborative analysis, so as to ensure the processing capacity and processing quality of the image acquisition system at the hardware design level. Compared with the traditional system, at the corresponding system software level, in order to further improve the quality of video signal processing, this paper creatively proposes a switch weighted median filter denoising algorithm, which has a significant impact on the processing of random impulse noise in video and the overall image filtering. At the same time, the algorithm also protects the edge details of the video image, thus improving the authenticity of the image and video. Based on this, this paper has built a verification platform based on supporting hardware and corresponding algorithms. Through hardware debugging and system operation analysis, when the operating frequency of the visual intelligent sensor is 100 MHz, the set acquisition depth is 10 bits, and the corresponding system collects data at a rate of 251 fps per second. In terms of the corresponding performance, the iteration number of the algorithm proposed in this paper is about 40% more than that of the traditional algorithm in unit time. In terms of the corresponding algorithm performance, the algorithm proposed in this paper is about 30% higher than the traditional algorithm. In terms of the efficiency of the corresponding image and video acquisition system, the algorithm proposed in this paper is about 44% higher than the traditional algorithm. Based on this, the system proposed in this paper has obvious advantages over the traditional algorithm.

Ensemble‐Based Experimental Design for Targeting Data Acquisition to Inform Climate Models

AbstractData required to calibrate uncertain general circulation model (GCM) parameterizations are often only available in limited regions or time periods, for example, observational data from field campaigns, or data generated in local high‐resolution simulations. This raises the question of where and when to acquire additional data to be maximally informative about parameterizations in a GCM. Here we construct a new ensemble‐based parallel algorithm to automatically target data acquisition to regions and times that maximize the uncertainty reduction, or information gain, about GCM parameters. The algorithm uses a Bayesian framework that exploits a quantified distribution of GCM parameters as a measure of uncertainty. This distribution is informed by time‐averaged climate statistics restricted to local regions and times. The algorithm is embedded in the recently developed calibrate‐emulate‐sample framework, which performs efficient model calibration and uncertainty quantification with only model evaluations, compared with evaluations typically needed for traditional approaches to Bayesian calibration. We demonstrate the algorithm with an idealized GCM, with which we generate surrogates of local data. In this perfect‐model setting, we calibrate parameters and quantify uncertainties in a quasi‐equilibrium convection scheme in the GCM. We consider targeted data that are (a) localized in space for statistically stationary simulations, and (b) localized in space and time for seasonally varying simulations. In these proof‐of‐concept applications, the calculated information gain reflects the reduction in parametric uncertainty obtained from Bayesian inference when harnessing a targeted sample of data. The largest information gain typically, but not always, results from regions near the intertropical convergence zone.

Design of Real-Time Monitoring System for Performance Parameter and Alarm of Main Engine RV. Baruna Jaya III

With the increasing age of RV. Baruna Jaya III (30 years), the ships often face various problems. The continuous operation of the engine causes a decrease in its performance which eventually results in the failure of the main engine. For instance, damage to the main engine can stop operating of the ship at sea which eventually have various impacts on ship and life safety as well as operational cost. In this context, efforts to manage ships especially for the operation of main engine and its prevention from errors through real time monitoring and control system have become a major issue. This study aims to design a monitoring and alarm system for the main engine performance on the RV. Baruna Jaya III as the preliminary step for the development of the overall monitoring system. As a result, a design for data acquisition of the main engine performance parameters in real time and the design of a ship’s main engine failure alarm system have been developed using PLC-based design technology and a SCADA-based monitoring system. This system can be thus further built for the performance of the ship’s main engine, as part of management ship operations and maintenance policies.

Examination of a Modified Incremental Rehearsal Approach to Explore Causal Mechanisms.

Incremental rehearsal (IR) has consistently been shown to improve students’ math fact retention and fluency (Maki et al., Journal of Behavioral Education 30:534–558, 2021). However, less is known about how intervention modifications may support longer-term skill maintenance. The purpose of this study was to compare traditional IR with a modified IR (shuffle IR; ShIR) in which known multiplication facts were shuffled between sequences using a cumulative acquisition design with six fourth- and fifth-grade students. All participants retained and maintained more facts in IR and ShIR compared to a control condition. However, IR or ShIR did not consistently result in greater retention than the other, with three students demonstrating greater retention in the IR condition and three students demonstrating greater retention in the ShIR condition. Most participants demonstrated greater fact maintenance in the ShIR condition than in the IR condition. All participants made fewer intervention session errors in the condition in which they retained more multiplication facts.

Full wave seismic exploration technology

Reflected wave seismology has the following defects: the acquisition design is based on the assumption of layered media, the signal processing suppresses weak signals such as diffracted wave and scattered wave, and the seismic wave band after the image processing is narrow. They limit the full utilization of broadband raw data. The concept of full wave seismic exploration is redefined based on the idea of balanced utilization of reflected wave, diffracted wave and scattered wave information, its characteristics and adaptive conditions are clarified. A set of key technologies suitable for full wave seismic exploration are put forward. During seismic acquisition period, it is necessary to adopt multi geometry, i.e. embed small bin, small offset and small channel interval data in conventional geometry. By discretizing of common midpoint (CMP) gathers, small offset with high coverage, the weak signals such as diffracted wave and scattered wave in the raw seismic data can be enhanced. During seismic processing, the signal and noise in the original seismic data need to be redefined at first. The effective signals of seismic data are enhanced through merging of multi-geometry data. By means of differential application of data with different bin sizes and different arrangement modes, different regimes of seismic waves can be effectively decomposed and imaged separately. During seismic interpretation stage, making the most of the full wave seismic data, and adopting well-seismic calibration on multi-scale and multi-dimension, the seismic attributes in multi-regimes and multi-domains are interpreted to reveal interior information of complex lithology bodies and improve the lateral resolution of non-layered reservoirs.