Data Acquisition System Research Articles

Development of a charged particle-[formula omitted] coincidence system for nuclear structure and reaction studies at TIFR

A new detector system for measurements of charged particles and γ-rays in coincidence has been developed at TIFR Mumbai, by coupling an annular double-sided segmented Si detector with an array of Compton-suppressed clover HPGe detectors. Digital data acquisition system has been configured for the setup, which has been calibrated and tested using the 229Th radioactive source that emits α-particles along with γ-rays. The functionality and performance of the coincidence apparatus for Doppler correction of γ-transitions emitted during the in-flight de-excitation of the projectile and the target in the 30Si + 197Au Coulomb excitation experiment have been demonstrated.

FPGA-based measurements of the relative arrival time of a high-repetition rate, quasi-cw fourth generation light source.

In this paper, we demonstrate the successful implementation of reconfigurable field-programmable gate array technology into a pulse-resolved data acquisition system to achieve a femtosecond temporal resolution in ultrafast pump-probe experiments in real-time at large scale facilities. As proof of concept, electro-optic sampling of terahertz waveforms radiated by a superradiant emitter of a quasi-cw accelerator operating at a 50kHz repetition rate and probed by an external laser system is performed. Options for up-scaling the developed technique to a MHz range of repetition rates are discussed.

Test Stand for Microjet Engine Prototypes

To investigate the functionality and performance of a prototype microjet engine, we constructed a versatile test stand tailored to the specifications of a 400 N prototype. This test stand facilitated a comprehensive study by enabling real-time recording of 45 essential parameters for analysis, encompassing temperatures, pressures, speed, fuel flow, thrust, vibration, and various other monitored metrics. All parameters and control elements were seamlessly integrated via a data acquisition and control system, utilizing a compactDAQ (Data Acquisition) system from National Instruments and a custom Virtual Instrument programmed with graphical language. The test stand offers both manual and automated operation modes, with the flexibility for hybrid operation. For instance, following the idle regime, manual control using a potentiometer can seamlessly transition from automated control via a proportional control (P control) mechanism. Before the experimental campaign, rigorous verification and validation tests were conducted to ensure the reliability and accuracy of the setup. The experimental campaign comprised a series of manual tests focusing on the fuel system and automated tests covering starting, idle, working, and stopping regimes. This structured approach allowed for a comprehensive evaluation across different operational scenarios, providing insights into the engine’s behavior and performance under varying conditions.

Wind turbine foundation ring fatigue reliability analysis under wind-load using SCADA system

Under the action of wind load, the foundation ring of the fan will generate stress concentration and alternating stress, leading to fatigue failure. Based on the average wind speed obtained from the supervisory control and data acquisition (SCADA) system, the orthogonal expansion method of random pulsating wind field and the number theory point selection method are used to calculate and simulate the corresponding pulsating wind speed time series, and then calculate the wind speed time series and wind load time series. Based on the ABAQUS finite element software, a model of a 5 MW wind turbine is established. The modal analysis is used to obtain the modal vibration pattern and the intrinsic frequency to verify the reasonableness of the structural modeling. Subsequently, the wind load time series is applied to the wind turbine model to obtain the stress time series using instantaneous modal dynamic analysis (Modal dynamics). The stress time series at the location of maximum stress concentration in the foundation ring is extracted, and the stress time series with the same stress amplitude is obtained through conversion, which has Wiener characteristics. After obtaining the stress amplitude using the rainflow counting method, the fatigue reliability is calculated based on the structural fatigue reliability analysis method considering the threshold crossing duration of the random process. This research holds reference significance for the calculation of fatigue reliability under approximate working conditions.

Analysis of Factors Influencing Traffic Sign Recognition Based on Multi-Sensor Perception Data

When traffic signs are blocked or faded, the ability of automated vehicles (AVs) to perceive and recognize them is lost or reduced. Previous research has improved and optimized the recognition algorithm but has not systematically analyzed the environmental and design factors that can lead to the AV’s failure to perceive and recognize traffic signs. This study uses the multiple sensors in the equipped vehicles of the Tongji University Road and Traffic Holographic Data Acquisition System to perceive and recognize traffic signs in six crash hotspots in Shanghai, China. Failure to recognize traffic signs was analyzed considering the influence of four sets of factors: traffic sign design, vehicle characteristics, environmental factors, and road design. A feature importance analysis was conducted utilizing the machine learning algorithm model CatBoost. Shapley additive explanation values were used to analyze the positive and negative relationships as well as the contribution rates of each influencing factor. The results revealed that the major factors influencing sign perception and recognition were positioning of traffic sign, lighting, blockage, cleanliness, fading, and reflectivity. Cleanliness had the most significant impact on the perception and recognition of traffic signs compared with the other influencing factors, and it also showed significant influencing interaction with the other factors. Fading was the second most important factor. The results of this study can guide designers of traffic signs to promote safety in mixed traffic environments that include both AVs and human-driven vehicles.

System for the Acquisition and Monitoring of Energy Consumption in the Context of Industry 4.0

This paper examines methodologies for monitoring energy consumption and operational parameters of an industrial assembly line, with a particular emphasis on the utilization of virtual tools, augmented reality, and real-time data visualization. The research examines the integration of an interface and the implementation of a data acquisition system, employing augmented reality to facilitate interaction with the collected data. The proposed system employs the Node-RED interface to facilitate the establishment of connections between constituent elements. The data is stored in a database, which provides support for decision-making in the analysis of energy consumption and operational parameters of the industrial assembly line. The results demonstrate that the solution is effective in enhancing energy resource management, identifying inefficiencies, and optimizing the performance of industrial equipment. The findings indicate that the implementation of such a system can markedly enhance the industrial process.

ATLAS upgrade for the HL-LHC

While the on-going Run-3 data-taking campaign will provide twice the integrated proton–proton luminosity currently available at the LHC, most of the data expected for the full LHC physics program will only be delivered during the HL-LHC phase. For this, the LHC will undergo an ambitious upgrade program to be able to deliver an instantaneous luminosity of 7.5⋅1034cm−2s−1, allowing the collection of more than 3 ab−1 of data at s=13.6(14)TeV. This unprecedented data sample will allow the ATLAS experiment to perform several precision measurements to constrain the Standard Model (SM) in yet unexplored regions of phase space, in particular in the Higgs sector, only accessible at the LHC. To benefit from such a rich data sample, it is fundamental to upgrade the detector to cope with the challenging experimental conditions that include radiation doses 10 times higher than what ATLAS experienced since its construction and increase in the number of interactions per bunch crossing from the current 50-60 to 200. The upgrade of the ATLAS detector comprises a completely new all-silicon tracker with extended rapidity coverage that will replace the current inner tracker detector; a redesigned trigger and data acquisition system for the calorimeters and muon systems, allowing the implementation of a readout system that can operate complex trigger algorithms at 40 MHz. Finally, a new subsystem called High Granularity Timing Detector will aid the track-vertex association in the forward region by providing timing information to the reconstructed tracks. An important ingredient, relevant to almost all measurements, is the precise determination of the delivered luminosity with systematic uncertainties below the percent level. This challenging task will be achieved by collecting the information from several detector systems using different and complementary techniques. This document will describe the ongoing ATLAS detector upgrade status and the main results obtained with the prototypes, giving a synthetic view of the whole upgrade project.

A Mixed Approach for Clock Synchronization in Distributed Data Acquisition Systems.

Proper timing synchronization is important when data from sensors are acquired by different devices. This paper proposes a simple but effective solution for System on Chip (SoC) architectures that integrates a general-purpose Field Programmable Gate Array (FPGA) with a CPU. The proposed approach relies on a network synchronization protocol implemented in software, such as Network Time Protocol (NTP) or Precision Time Protocol (PTP), and uses the FPGA to generate a clock reference that is maintained in step with the synchronized system clock. The clock generated by the FPGA is obtained from the FPGA oscillator via appropriate fractional clock division. Clock drift is avoided via a software program that periodically compares the FPGA and the system counters, respectively, and adjusts the fractional clock divider in order to slightly adjust the FPGA clock frequency using a Proportional Integral controller. A specific implementation is presented on the RedPitaya platform, generating a 1 MHz clock in step with the NTP synchronized system clock. The presented system has been used in a distributed data acquisition system for fast transient recording in the neutral beam test facility for the ITER nuclear fusion experiment.

Image De-noising Based on WMF Technique for Electrical Trees Structure in High Voltage Cable Insulation

Electrical treeing is a common problem during the pre-breakdown phenomenon in solid insulations due to the damage caused by Partial Discharge (PD) that progresses through stressed insulation via chemical degradation, which resembles the shape of a tree root. This resulted in a decrease in performance through degrading the insulation, which became a serious problem while dealing with electrical equipment. Hence, a deep understanding of electrical tree structure is vital to improving the quality of solid insulations. Ergo, optical microscopy is primarily used to examine tree structures, shapes, and fractal dimensions to reconstruct electrical tree structures for morphological study. However, optical microscopy images are frequently degraded by noise from readout procedures or image data acquisition systems, noise caused by occlusion, illumination, non-uniform intensity, destroying potential tree pixels, and a critical loss of information about the electrical tree structures. Therefore, this research proposed the Wiener Median Fusion (WMF) filter for electrical tree study. The performance of the WMF de-noising technique improves the image quality for the precise portrayal of the electrical tree structure based on thresholding segmentation algorithm analysis in terms of accuracy, sensitivity, and false positive rate. Based on the analysis of the thresholding segmentation algorithm, Otsu's thresholding exhibits the highest result compared to Niblack. The Otsu's overall percentage in terms of accuracy is 80.2934%, the sensitivity is 99.1513%, and the false positive rate is 82.6265%.

Adaptation of a Differential Scanning Calorimeter for Simultaneous Electromagnetic Measurements.

Although much information can be gained about thermally induced microstructural changes in metals through the measurement of their thermophysical properties using a differential scanning calorimeter (DSC), due to competing influences on the signal, not all microstructural changes can be fully characterised this way. For example, accurate characterisation of recrystallisation, tempering, and changes in retained delta ferrite in alloyed steels becomes complex due to additional signal changes due to the Curie point, oxidation, and the rate (and therefore the magnitude) of transformation. However, these types of microstructural changes have been shown to invoke strong magnetic and electromagnetic (EM) responses; therefore, simultaneous EM measurements can provide additional complementary data which can help to emphasise or deconvolute these complex signals and develop a more complete understanding of certain metallurgical phenomena. This paper discusses how a DSC machine has been modified to incorporate an EM sensor consisting of two copper coils printed onto either side of a ceramic substrate, with one coil acting as a transmitter and the other as a receiver. The coil is interfaced with a custom-built data acquisition system, which provides current to the transmit coil, records signals from the receive coil, and is controlled by a graphical user interface which allows the user to select multiple excitation frequencies. The equipment has a useable frequency range of approximately 1-100 kHz and outputs phase and magnitude readings at a rate of approximately 50 samples per second. Simultaneous DSC-EM measurements were performed on a nickel sample up to a temperature of 600 °C, with the reversable ferromagnetic to paramagnetic transition in the nickel sample invoking a clear EM response. The results show that the combined DSC-EM apparatus has the potential to provide a powerful tool for the analysis of thermally induced microstructural changes in metals, feeding into research on steel production, development of magnetic and conductive materials, and many more areas.

Application of photothermal beam deflection spectrometry for non-destructive evaluation of advanced materials: a state-of-the-art review

Abstract The progress made in lasers and data acquisition systems has paved the way for innovative non-destructive evaluation methods based on the photothermal phenomenon. Beam deflection spectrometry (BDS) is a photothermal spectroscopic technique that offers ultra-sensitivity, high signal-to-noise ratios, and reduced sample preparation requirements. These advantages provide precise assessment of advanced material (AM) properties. This review presents a comprehensive in-depth analysis, thus helping researchers to understand the potential and future perspectives of BDS along with the theory, instrumentation, and application supported by the literature data. The objective of this review is also to present the possibilities of BDS in the characterization of AMs, including organic, inorganic, and hybrid organic–inorganic materials in the form of thin films, coatings, composites, and nanomaterials.

An efficient and automatic method based on monocular camera and GNSS for collecting and updating geographical coordinates of mileage pile in highway digital twin map

Abstract The high-precision positioning of mileage piles on a digital map ensures accurate data for high-speed event releases, toll audits, and road condition monitoring. This paper introduces an efficient and automatic system for positioning highway mileage piles. The self-developed data acquisition system collects mileage pile images and road trajectory. Considering the limited variety of mileage piles, a Simplified-YOLOv5m (S-YOLOv5m) is proposed. Then a high-precision character detection network of S-YOLOv5m is proposed to enhance feature extraction and improve the accuracy of character detection on mileage piles. Thirdly, the end-to-end monocular distance measurement combines the target detection with the distance estimation, enabling simultaneous object detection and distance measurement. Fourthly, by combining with the geographical coordinates of the acquisition point, the direct solution to geodetic problems is applied to calculate the spatial coordinates of the mileage piles. Finally, the missing mileage piles are compensated for using the road curve and equal distance interpolation. The complete mileage piles and geographical information list of the inspection trajectory are output. Through a series of verification tests, the average positioning error of the mileage pile system is 1.265 m. The contribution of the automatic positioning system of mileage piles is to construct the relationship between mileage piles and geographical coordinates, match mileage piles with digital maps to realize the full-featured, real-scene, and high-dynamic management of road attributes.

Retraction Note: Optical imaging technology based on embedded processors in real-time data acquisition system for motion training

Retraction Note: Optical imaging technology based on embedded processors in real-time data acquisition system for motion training

Fault detection framework in wind turbine pitch systems using machine learning: Development, validation, and results

This work develops a methodology for detecting faults in wind turbines through supervised machine-learning classification methods focusing in two modes of operation. The Normal mode will be related to the regular operation of the wind turbines and in the case of the abnormal mode, the system will be cataloged as Pitch system failure. This methodology uses real data through the supervisory control and data acquisition (SCADA) system and the recording of events and actions (LOG alarm system). Sixteen classifications artificial intelligence (AI) models were tested, such as Random Forest Classifier (RF), Gradient Boosting Classifier (GBC), Extra Trees Classifier (ET), Extreme Gradient Boosting (XGBOOST), Light Gradient Boosting Machine (LIGHTGBM), Categorical Boosting Classifier (CATBOOST), Adaptative Boosting Classifier (ADA), Decision Tree Classifier (DT), Linear Discriminant Analysis (LDA), K-Nearest Neighbors Classifier (KNN), Logistic Regression (LR), Naive Bayes (NB), Quadratic Discriminant Analysis (QDA), Dummy Classifier (DC), Super vector machine (SVM), Ridge Classifier (RC). The training process model was carried out by structuring the dataset in 75% for training and validation and 25% for the final test, considering cross-validation and optimization of the hyperparameters. The Random Forest Classifier (RF) and Extra Trees Classifier (ET) classifiers models presented the best performances, and the models with the lowest performances were K-Nearest Neighbors Classifier (KNN) and Linear Discriminant Analysis (LDA) ones. The average hit effectiveness for both Healthy and Faulty operating modes was approximately 80% across most of the models developed.

Revisiting Dissolved Organic Matter Analysis Using High-Resolution Trapped Ion Mobility and FT-ICR Mass Spectrometry.

The molecular level characterization of complex mixtures remains an analytical challenge. We have shown that the integration of complementary, high-resolution, gas-phase separations allows for chemical formula level isomeric content description. In the current work, we revisited the current challenges associated with the analysis of dissolved organic matter using high-resolution trapped ion mobility separation (TIMS) and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). In particular, we evaluated the separation capabilities provided by TIMS-MS compared to MS alone, the use of ICR complementary data acquisition (DAQ) systems and transient processing strategies, ICR cell geometries (e.g., Infinity cell vs harmonized cell), and magnetic field strengths (7 T vs 9.4 T vs 21 T) for the case of a Harney River DOM sample. Results showed that the external high-performance DAQ enables direct representation of mass spectra in absorption mode FT (aFT), doubling the MS resolution compared to the default magnitude mode FT (mFT). Changes between half- vs full-apodization result in greater MS signal/noise vs superior MS resolving power (RP); in the case of DOM analysis, a 45% increase in assigned formulas is observed when employing the DAQ half (Kaiser-type)-apodization window and aFT when compared to the default instrument mFT. Results showed the advantages of reprocessing 2D-TIMS-FT-ICR MS data with higher RP and magnetic field chemical formulas generated list acquired (e.g., 21 T led to a 24% increase in isomers reported) or the implementation of alternative strategies.

Why should a bioengineering lab have engineers and health professionals?

Through the description of the methodology of the development of a bite force measurement device it will be shown how interdisciplinary work of Engineers and Health Professionals bring enhance of life quality to general population. Bite force measurement is a reliable exam to check stomatognathic system (SS) conditions. In order to provide a reliable, low cost and do-it-yourself gnathodynamometer a Dentist joined Bioengineering Laboratory (LabBio) at UFMG. The development of a 3D printed resin structure was made using CAD/CAM and tested by means of FEM. A Carbon Nano Tube (CNT) extensometer developed at CTNANO at UFMG to capture the structure deformation were fixed in two geometries that showed good results in FEM simulation and will be tested in an EMIC universal mechanical testing machine (DL1000) equipped with a 1 kN load cell. The electrical response of the extensometers was monitored using a Keithley 2000 digital multimeter (Tektronix), connected to a computer and remotely controlled by a LabView application (View Point Systems), a data storage protocol in a SD card and in the clouds using IoT and an data acquisition system will be tested. In bench tests both geometries showed good results with deformation capturable from 40 N. Data was codified using an Arduino Nano and a program was developed for data acquisition and storage. The interdisciplinary work generates prototypes with promising results in bench tests. The fruit of the team work may generate a toll that improves life quality of population by allowing more people to be tested and lowering health costs.

Sensing Skin Technology for Fatigue Crack Monitoring of Steel Bridges: Laboratory Development, Field Validation, and Future Directions

A significant number of steel bridges are vulnerable to fatigue cracks, and the timely discovery of damage is critical in ensuring safety and continuous operations. Despite various crack monitoring methods available in the field of structural health monitoring (SHM) to empower real-time feedback, few commercially-available technologies are applicable to the task of discovering new cracks because of the highly localized nature of the sensors. The authors have developed a sensing skin constituted from soft elastomeric capacitors (SECs). An SEC is a large-area strain gauge that transduces strain into a measurable change in capacitance. It can be easily deployed over large surfaces, and thus can be used to discover new fatigue cracks. The technology has been developed and characterized in a laboratory environment over the last decade. It has been recently deployed in the field on a bridge located in Kansas, USA. The aim of this paper is to present and discuss technological updates that were necessary to enable field deployment, with the objective of supporting the field deployment of the cSEC and other SHM technologies. In particular, it reviews the following SEC technology modifications: 1) corrugation of the surface of the dielectric, creating a corrugated SEC or cSEC, to improve sensing performance; 2) development of a dedicated wireless data acquisition system; and 3) improvement of the data fusion algorithm to account for higher signal contamination in the field. After this review, challenges in conducting field deployment are examined. Lastly, a discussion is provided on a path to commercialization.

Resilience analysis of stress corrosion cracking in AISI 4340 steel under varying industrial electrochemical conditions

Stress Corrosion Cracking (SCC) presents a substantial challenge within industries where materials confront both mechanical stresses and corrosive environments. This work comprehensively examines SCC, incorporating the collection and analysis of a diverse dataset. The dataset encompasses pivotal parameters, including time to failure, corrosion rates, and electrochemical data. These parameters are meticulously garnered through Slow Strain Rate Testing on carefully prepared smooth, round tension specimens. The experiments are vigilantly overseen through a condition-based data acquisition and logging system, employing various Potentiostatic loads to mirror real-world electrochemical conditions. This research elucidates the intricate interplay between mechanical stresses, electrochemical processes, and corrosive conditions, rendering crucial insights for industries dependent on material integrity amidst formidable environmental challenges. Findings show that AISI 4340 Steel specimens exposed to a +400mV potential in NS4 solution exhibit an extended time to failure of approximately 7.4 days. Conversely, a −1200mV potential in NS4 accelerates the failure to around 5.24 days. In a 3.5wt% NaCl solution at 0mV, the time to failure is approximately 5.76 days. On the other hand, an applied potential of +400mV increases the failure time to approximately 6.16 days. And an applied potential of −1200mV accelerates the failure time to approximately 4.77 days. Specifically, the study reflects on structures submerged in water and those buried underground, represented by NS4 (Near Neutral Soil Simulating Solution) and 3.5w.t.% NaCl solutions, simulating real-world corrosive conditions. Through a deeper comprehension of SCC, industries can better anticipate and mitigate the risks associated with material failure in harsh environmental conditions, advancing the safeguarding of critical infrastructures.

Demonstration and optimization of coherent Doppler wind LiDAR with low sampling resolution

A low sampling resolution scheme for coherent Doppler wind LiDAR (CDWL) is proposed. The CDWL offers advantages in precision and detection resolution but suffers from the requirement of high-speed data acquisition (DAQ) with high sampling resolution, such as 12- or 14-bit, which leads to an increase of the computational complexity and the system cost. The use of a DAQ system with lower sampling resolution can provide a solution to mitigate this problem. The feasibility of the proposed scheme is validated by simulations and experiments. The detection performance can be greatly affected by the quantization interval selected during sampling. It is shown that the optimal quantization interval exists and only depends on the carrier-to-noise ratio (CNR), and the optimal quantization intervals of several sampling resolutions are given at different CNRs. With the given optimal quantization configuration, the low sampling resolution data can be used for reliable wind field measurements. For long-distance detection with a CNR lower than −13dB, the CNR deterioration of 1-bit, 2-bit, 3-bit, and 4-bit signals can be as low as 2, 0.5, 0.2, and 0.1 dB.

THE effect of P2X7 receptor activation on functional responses of human left internal mammary artery.

The Purinoreceptor 7 (P2X7R) has become a promising drug target in many cardiovascular diseases, including coronary artery disease, since prolonged activation of P2X7R could promote vascular dysfunction, atherosclerosis, and thrombosis. Thus, we aimed to study the effects of P2X7R activation on vascular relaxation responses of the human left internal mammary artery (LIMA). Sections of redundant human LIMA were cut into 3-mm wide rings,, suspended in 20-mL organ baths containing physiologic salt solution, and attached to an isometric force transducer connected to a computer-based data acquisition system. Long-term (60min) incubation with specific P2X7R agonist Bz-ATP caused significant reductions in relaxation responses of LIMA to ATP and acetylcholine, which were reversed by selective P2X7R antagonists Brilliant Blue G or AZ11645373, whereas there were no changes in relaxation responses to endothelium-independent vasodilators isoprenaline, cAMP analog 8-Br-cAMP, and nitric oxide donor sodium nitroprusside. The impairment in relaxant responses of LIMA to endothelium-dependent vasodilators following activation of P2X7R for the long-term may contribute to postoperative LIMA vasospasm and hypertension. Modulation of P2X7R activity with selective agents may represent a new potential therapeutic approach in patients undergoing coronary artery bypass grafting surgery.