Data Acquisition System Research Articles

Event driven high speed data acquisition with IEEE 1588 synchronization for long pulse operations of Indian Test Facility for ITER DNB

The Indian Test Facility (INTF) is a negative Hydrogen ion based 100 kV, 60A, 5 Hz modulated NBI system having duty cycle of 3 s ON time to 20 s OFF time. Prime objective of the facility is to characterize ITER Diagnostic Neutral Beam (DNB) with full specifications, prior to shipment and installation in ITER. In order to fully characterize ITER DNB, a matured Data Acquisition and Control system (DACS) is needed which will be responsible for supervisory control of the facility and for acquiring and monitoring signals at run time. Apart from conventional DACS, high speed data acquisition is needed for diagnostics and other signals with sampling rate requirements of 100 MS/s. For acquiring data from such systems it is imperative that the data be acquired only for certain duration on the occurrence of the event. Such acquisition systems are classified as event driven data acquisition system and are widely used in fusion engineering community.Development and implementation of high speed event driven data acquisition systems pose challenges in terms of data buffering, data streaming and synchronization. The precise timing of the event occurrence with respect to the main pulse should also be known for which a timing and synchronization system is needed. To fulfill this purpose, IEEE 1588 protocol offers a network based method of synchronizing multiple nodes based on Ethernet with sub microsecond accuracy. The present work describes the development of an event driven high speed data acquisition in synchronization with IEEE 1588 based timing network. The work proposes the time stamping of the event from synchronized network integrated with the event acquisition platform. The developed system has been tested for pulse durations longer than 3600 s. The performance of event data acquisition system has been thoroughly characterized and improved by applying various software optimizations in LabVIEW. The present work although intended to be used for INTF can be used for any such facility in fusion or other areas.The paper provides results of IEEE 1588 based timing network in various configurations and event data acquisition system developed on high speed FPGA controlled digitizer board with prototype results.

Versatile micro-electrode array to monitor human iPSC derived 3D neural tissues at air-liquid interface

Engineered 3D neural tissues made of neurons and glial cells derived from human induced pluripotent stem cells (hiPSC) are among the most promising tools in drug discovery and neurotoxicology. They represent a cheaper, faster, and more ethical alternative to in vivo animal testing that will likely close the gap between in vitro animal models and human clinical trials. Micro-Electrode Array (MEA) technology is known to provide an assessment of compound effects on neural 2D cell cultures and acute tissue preparations by real-time, non-invasive, and long-lasting electrophysiological monitoring of spontaneous and evoked neuronal activity. Nevertheless, the use of engineered 3D neural tissues in combination with MEA biochips still involves series of constraints, such as drastically limited diffusion of oxygen and nutrients within tissues mainly due to the lack of vascularization. Therefore, 3D neural tissues are extremely sensitive to experimental conditions and require an adequately designed interface that provides optimal tissue survival conditions. A well-suited technique to overcome this issue is the combination of the Air-Liquid Interface (ALI) tissue culture method with the MEA technology. We have developed a full 3D neural tissue culture process and a data acquisition system composed of high-end electronics and novel MEA biochips based on porous, flexible, thin-film membranes integrating recording electrodes, named as “Strip-MEA,” to allow the maintenance of an ALI around the 3D neural tissues. The main motivation of the porous MEA biochips development was the possibility to monitor and to study the electrical activity of 3D neural tissues under different recording configurations, (i) the Strip-MEA can be placed below a tissue, (ii) or by taking advantage of the ALI, be directly placed on top of the tissue, or finally, (iii) it can be embedded into a larger neural tissue generated by the fusion of two (or more) tissues placed on both sides of the Strip-MEA allowing the recording from its inner part. This paper presents the recording and analyses of spontaneous activity from the three positioning configurations of the Strip-MEAs. Obtained results are discussed with the perspective of developing in vitro models of brain diseases and/or impairment of neural network functioning.

Anomaly detection in wind turbine blades based on PCA and convolutional kernel transform models: employing multivariate SCADA time series analysis

With the widespread application of wind power technology, the detection of abnormalities in wind turbine blades has become a key research area. The use of data from monitoring and data acquisition (SCADA) systems for data-driven fault detection research presents new challenges. This study utilizes short-term SCADA data from wind turbine generators to classify the blade abnormal and normal operational states, thereby introducing a new method called PCABSMMR. This strategy integrates principal component analysis (PCA) and borderline-synthetic minority over-sampling technique (Borderline-SMOTE) for data processing and utilizes an improved multi-dimensional time series classification (MTSC) model. It combines one-dimensional convolution from deep learning with shallow learning’s rigid classifiers. PCA is used for dimensionality reduction, while Borderline-SMOTE expands the samples of minority class fault instances. Comparative analysis with various methods shows that the proposed method has an average F1-score of 0.98, outperforming many state-of-the-art MTSC models across various evaluation metrics.

Dual threshold input receiver FPGA-only signal digitization method for time-of-flight positron emission tomography

AbstractAs silicon photomultiplier (SiPM)-based time-of-flight (TOF) positron emission tomography (PET) becomes popular, the need for sophisticated PET data acquisition (DAQ) systems is increasing. One promising solution to this challenge is the adoption of a field-programmable gate array (FPGA)-only signal digitization method. In this paper, we propose a new approach to efficiently implement an FPGA-only digitizer. We configured the input/output (IO) port of the FPGA to function as a dual-threshold voltage comparator through the use of simple passive circuitry and heterogeneous IO standards. This configuration overcomes the limitations of existing methods by allowing different threshold voltages for adjacent IO pins, effectively reducing routing complexity and lowering manufacturing costs. An FPGA-only digitizer was implemented by integrating the dual-threshold voltage comparator and FPGA-based time-to-digital converter. By combining the dual-threshold time-over-threshold (TOT) method and curve fitting, precise energy information could be obtained. The performance of the FPGA-only digitizer was assessed using a detector setup comprising a 3 × 3 × 20 mm3 LYSO scintillation crystal and a single pixel SiPM. Using the configured evaluation setup, an energy resolution of 12.5% and a time resolution of 146 ± 9 ps were achieved for a 20 mm scintillation crystal. The dual-threshold TOT implemented using the proposed method showed consistent linearity across an energy range of 100 keV to 600 keV. The proposed method is well-suited for the development of cost-effective DAQ systems in highly integrated TOF PET systems.

Assessment of demand consumptions and potential viability of installation of biogas digester in melani village Eastern Cape, South Africa

AbstractAfrica relies heavily on traditional fossil fuel sources, especially coal. To solve the energy problem in rural areas, the country initiated the production and distribution of several renewable energy technologies. Biogas has been proven viable and has begun as a promising technology among several promising technologies. It has been one of the most successful models for producing clean, environmentally friendly, cost-effective energy sources and has multiple benefits. A financial analysis will be conducted, including an estimation of the total investment, the present value of the annual investment, the present value of the investment, and a simple payback period. To determine the demand, onset CTA-A hobo current transducers were installed in three families to measure everyday use in summer and winter. The Data acquisition system has shown that each home consumes an average of 140 kWh of electricity per month. Finally, the biogas digester's analytical life cycle cost analysis shows that the simple payback period would be approximately two years.

Indoor measurement and analysis on soil-traction device interaction using a soil bin

Investigating the mechanical interaction between vehicles and soil requires measuring various mechanical parameters, which have been enhanced through the advancement of measurement tools. This study delves into the measurement tools and data recording devices utilized in soil-traction device studies conducted at the Off-Road Vehicle Research Center of Urmia University. The tools and methods used for measuring and recording parameters such as forces, velocities, displacements, stresses, and contact areas during traction engagements of laboratory test traction devices (wheels and tracks) are presented. These measurements may have been simultaneously obtained using multiple transducers. The results demonstrate the data acquisition system's successful measurement and recording of these parameters. This research emphasizes the integration of different sensors, developing and implementing a unified data acquisition system for various transducers, and creating innovative setups for measuring and recording parameters such as soil density and wheel-soil contact area, which are of significant importance.

Detection of ion cyclotron emission by using an ion cyclotron range of frequency antennas-based diagnostic system in experimental advanced superconducting tokamak

In the experimental advanced superconducting tokamak (EAST), a novel ion cyclotron range of frequency (ICRF) antenna-based diagnostic system is designed to measure ion cyclotron emission (ICE) driven by high-energy ions. The diagnostic system includes ICRF antenna straps, a three-tune impedance matching system, a coaxial switching system, a direct current block, and a data acquisition and storage system. Using the coaxial switching system, the ICRF antenna can be switched from the heating mode to the coupling mode between two discharges. In the 2023 EAST experiment campaign, core ICE was observed using the ICRF antenna-based diagnostic system during neutron beam injection heating, and the obtained results agreed well with the signal detected by the previous high-frequency B-dot probe-based diagnostic system.

The Prospect of Typhoon Landfall Observation Utilizing L-band InSAR

The cyclonic phenomenon, particularly typhoons within the 100° E to 180° E longitude region, bring significant devastation through intense rainfall and strong winds, causing secondary effects like landslides and floods upon landfall. This results in infrastructural damage and loss of life, ranking storm-related disasters, including typhoons, second only to earthquakes in casualties, emphasizing the need for a robust observation system. While higher income countries benefit from established radar and meteorological stations for continuous monitoring, this study highlights the critical necessity for an additional monitoring system in lower income countries. We investigate the applicability of Interferometric Synthetic Aperture Radar (InSAR) during typhoon landfall, particularly in densely vegetated areas where longer wavelengths like L-band (for instance, the Advanced Land Observing Satellite (ALOS/PALSAR) and ALOS-2/PALSAR-2) are suitable. By analyzing typhoon occurrences and confirming landfall using weather radar from 2007 to 2011 (ALOS/PALSAR observation period) and 2014 to 2023 (ALOS-2/PALSAR-2 observation period), our study successfully identifies the landfall of the Jebi typhoon on September 4, 2018. InSAR processing reveals significant phase gradients linked to dense water vapor during landfall, corroborated by comparisons with sea-level Zenith Wet Delay (ZWD) from Global Navigation Satellite System (GNSS) data and hourly precipitation rates from the Automated Meteorological Data Acquisition System (AMeDAS). The concurrence of InSAR results with ZWD values and rainfall data from meteorological stations validates the potential of L-band InSAR in observing typhoon landfalls.

Outer Barrel services chain characterisation for the ATLAS ITk Pixel detector

For the high-luminosity upgrade of the ATLAS Inner Tracking detector of the ATLAS experiment, a new pixel detector will be installed to allow for a bigger bandwidth and cope with the increased radiation among other challenges. This contribution will present the evaluation of the Outer Barrel Pixel layer services chains. A full data transmission study covering data merging will be presented from the pixel module all the way to the FELIX data acquisition system, using most of the components foreseen for the detector. Challenges and results of the services chain of the Outer Barrel will be highlighted.

Periodic sampling and count rate correction of the low energy X-ray telescope on board the Insight- Hard X-ray modulation telescope

The Low Energy X-ray Telescope (LE) is an important instrument of the Insight-Hard X-ray Modulation Telescope (Insight-HXMT), which performs scanning and point observation in the soft X-ray energy band (0.7–13 keV). Since its launch in 2017, it has conducted a large number of scientific observations and achieved significant astronomical discoveries. LE is composed of three detector boxes and an electronic control box. The data acquisition system of LE is designed to use periodic sampling, which solves the problem of unstable noise peaks. Data loss may occur when observing X-ray bursts, and periodic sampling provides a method of correcting light curves. In addition, in the South Atlantic Anomaly (SAA) or where the count rate of the particle monitor on the Insight-HXMT is very high, LE automatically switches into SAA operating mode, and only a small number of events are recorded. After data correction, the light curves can be estimated to expand the astronomical achievements of LE.

Research and application of small-diameter hydraulic fracturing in situ stress measurement system

Abstract. Observation and estimation of the stress state in the deep crust is a crucial challenge in in situ stress measurement work. The hydraulic fracturing method is an important borehole-based technique for absolute in situ stress measurement. The small-diameter hydraulic fracturing in situ stress measurement system described in this article consists mainly of underground measurement components (serial small-diameter packers and dual-circuit connecting installation rods) and surface control components (hydraulic fluid control system, data acquisition system, and high-pressure oil pump with controllable flow). It enables series measurement of small-sized boreholes for in situ stress and provides a maximum measurement range of 30–45 MPa. The subsequent calculation of in situ stress data adopts a uniform design method to discuss the influence of various external factors on rock fracturing values. The small-diameter hydraulic fracturing in situ stress measurement system has the advantages of simple and lightweight structure, short testing time, high success rate, and low requirements for rock integrity and pressurization equipment. It has formed a series of small-diameter in situ stress measurement equipment which has been innovatively promoted to the field of underground tunnel safety assessment in coal mines and metal mining areas. It has an important practical value and economic significance in accurately determining the in situ stress state of deep development areas.

Automatic measurement of water infiltration into the soil

ABSTRACT In hydrological modeling and for the development of projects related to soil and water conservation and civil engineering, determination of water infiltration variables into the soil plays a key role. However, measuring infiltration with manual infiltrometers is work-intensive and requires several people, which casts doubts on the consistency of the process description. Our objective was to develop automated and compact systems for data acquisition by double-concentric-ring and Cornell infiltrometers. The systems are based on air differential pressure sensors and microcontrollers using open-source software and a simple construction. We developed ten sets of automatic infiltrometers for each method that were properly calibrated. The equipment was validated in the field, and the alignment of the automatically measured with the hand-measured infiltration data was considered satisfactory. The proposed systems make data records of infiltration and associated variables possible, with less operator dependence than manual measurement strategies. In addition, the enhanced resolution resulting from infiltrometer automation makes the infiltration curve more representative, especially in the initial infiltration stage.

ОСНОВНІ РЕЖИМИ РОБОТИ І ГРАФІЧНИЙ ІНТЕРФЕЙС КОРИСТУВАЧА КОМПЛЕКСУ ДЛЯ ЕКСПЕРИМЕНТАЛЬНИХ ДОСЛІДЖЕНЬ МАГНІТНИХ ПОЛІВ І ДІАГНОСТУВАННЯ ЕЛЕКТРОЕНЕРГЕТИЧНОГО ОБЛАДНАННЯ

Hardware and software monitoring complex is designed to study the relationship between changes in the patterns of the magnetic field intensity distribution with power equipment failures. In experimental studies with predetermined techni-cal faults artificially introduced into the object the complex will provide useful and reliable results by registering changes in the magnetic field induction in the spatial, temporal and frequency domains. The choice and flexible adjust-ment of data collection tools by the researcher will ensure the use of the most appropriate method for measuring, con-verting and displaying information about the investigated faults. The article presents the main operating modes and graphical user interfaces of a personal computer and a mobile data acquisition system that jointly convert, store, ana-lyze and display measurement information received from various magnetic sensors. The generalized functional specifi-cation of the complex software, the design of the graphical user interface (GUI) as parts of the real-time operating sys-tem (RTOS) of the mobile data acquisition system (DAQ) and PC software will also be used in the development of prob-lem-oriented computer diagnostic systems for electric power equipment. Ref. 12, fig. 3.

Design and Manufacturing of EV Go-Kart

Abstract: Go-karts are small-size and small-weight vehicles that were developed for racing. These are made with materials that are strong and durable. It consists of many parts which include a chassis, engine, steering and braking system, and electronic controls. The chassis is the main part that is responsible for the stability of the vehicle. Chassis is made with the material having greater endurance and rigidity. It was developed in the 1950s in the USA and now getting popular. These are now used in amusement parks as a recreational activity. Many researchers have done work on go-karts and improve their design. This project was intended to design and fabricate a reliable and durable go-kart. Its primary objective to build a go-kart using local resources and applying different techniques to limit the cost of vehicles. These objectives were achieved by going through a detailed literature review and studying different techniques which can be implemented. A reliable design was chosen which can be implemented and can be completed in our period. Critically evaluate the design of the vehicle and then different parts were designed. This paper presents an approach to a go-kart chassis design, vehicle dynamics calculation, Li-ion battery capacity analysis, and electric motor choice for optimized vehicle performance. The chassis analysis shown in this paper was performed using a CAD/FEA software package, SolidWorks Student Edition. Three highlights can be found in this paper: An original design was implemented; the basic analysis was composed of chassis optimization using beam elements and modelling such an optimized chassis “locally” with solid elements for sub-modelling purposes. The most stressed tube joint was sub-modelled to calculate the risk of tube wall stability. Vehicle dynamics were calculated for the case of braking on a curved path and the case of a collision with the front tire due to road imperfection. The authors intend to install a data acquisition system in the future to analyse the stress of local chassis tubes.

3D DEWS digital parametric modeling and manufacturing for obtaining the post-cracking parameters of SFRC

A pullout analytical model is introduced to simulate the Double Edge Wedge Splitting (DEWS) test to obtain the tensile post-peak response of steel fiber reinforced concretes. One of the main barriers to the widespread utilization of FRC as a structural system is the anisotropy of the material. This augments the uncertainty of the material behavior (fibers random distribution and orientation in the bulk concrete), increases the dispersion of the test results, and requires the performance of characterization tests to check the residual tensile stresses at specific crack opening intervals. The characterization tests proposed in the literature (e.g., Barcelona, Montevideo, Wedge Splitting Test, EN 14651) are time-consuming and relatively complex, demanding careful preparation and hydraulic presses with data acquisition systems. This paper aims to contribute to the discussion of alternatives for FRC characterization procedures by the introduction of a pullout analytical model to predict FRC constitutive law based on DEWS tests. The pullout analytical model is calibrated with pullout tests considering straight and hooked-end steel fibers with different strengths, embedment lengths, inclinations, and diameters. A 3D digital model reproducing the experimental DEWS samples is developed, considering the fibers’ randomness distribution, orientation, and wall effect. The analyses are compared with four different experimental tests. The results define a linear post-peak tensile constitutive law, considering the mean residual stress values at different COD values. The model was able to reproduce the specimens’ production procedures and the fibers’ distribution and orientation correctly. The results demonstrated a good agreement with the experimental data.

Wind turbine fault detection and identification using a two-tier machine learning framework

A proactive approach is essential to optimize wind turbine maintenance and minimize downtime. By utilizing advanced data analysis techniques on the existing Supervisory Control and Data Acquisition (SCADA) system data, valuable insights can be gained into wind turbine performance without incurring high costs. This allows for early fault detection and predictive maintenance, ensuring that unscheduled or reactive maintenance is minimized and revenue loss is mitigated. In this study, data from a wind turbine SCADA system in the southeast of Ireland were collected, preprocessed, and analyzed using statistical and visualization techniques to uncover hidden patterns related to five fault types within the system. The paper introduces a conditional function designed to test two given scenarios. The first scenario employs a two-tier approach involving fault detection followed by fault identification. Initially, faulty samples are detected in the first tier and then passed to the second tier, which is trained to diagnose the specific fault type for each sample. In contrast, the second scenario involves a simpler solution referred to as naive, which treats fault types and normal cases together in the same dataset and trains a model to distinguish between normal samples and those related to specific fault types. Machine learning models, particularly robust classifiers, were tested in both scenarios. Thirteen classifiers were included, ranging from tree-based to traditional classifiers, neural networks, and ensemble learners. Additionally, an averaging feature importance technique was employed to select the most impactful features on the model decisions as a starting point. A comparison of the results reveals that the proposed two-tier approach is more accurate and less time-consuming, achieving 95% accuracy in separating faulty from normal samples and approximately 91% in diagnosing each fault type. Furthermore, ensemble learners, particularly bagging and stacking, demonstrated superior fault detection and identification performance. The performance of the classifiers was validated using t-SNE and explainable AI techniques, confirming that the impactful features align with the findings and that the proposed two-tier solution outperforms the naive solution. These results strongly indicate that the proposed solution is accurate, independent, and less complex compared to existing solutions.

Wide-Aperture Backscattering Detector (BSD-A) for The High-Resolution Fourier Diffractometer

The high-resolution Fourier diffractometer (HRFD) has been in routine operation since 1994 at the long-pulse neutron source, the IBR-2 reactor, in Dubna. Its fast Fourier chopper provides probably the best compromise between very high resolution in reciprocal space (Δd/d ≈ 0.001) and the intensity. For further improving intensity of TOF-diffraction pattern, a wide-aperture ring backscattering detector (BSD) has been developed on the basis of ZnS(Ag)/6LiF scintillator. BSD is designed in the form of 6 concentric rings, each of which is subdivided into 12 identical parts. The main parameters of the detector are the following: range of scattering angles is 2θ = (133 - 175) degrees, covered solid angle is Ωd ≈ 2.0 sr, average percentage absorption efficiency gets closer to 85%, geometrical contribution to resolution function does not exceed Δd/d  = 0.0005. In the report the concept of the detector is described and its data acquisition system is presented. The start of operation of the detector at the HRFD is scheduled for 2024.

Exploring high-rise preventive ventilation: Experimental investigation of inter-zone air pressurization with tracer gas analysis

Over the past four years, five major variants of the SARS-CoV-2 virus have circulated globally, causing seven million deaths. Meanwhile, specific preventative ventilation measures were recommended to minimize exposure to the aerosol infection risk, such as opening doors, and disabling ventilation systems. Given more attention to high-rise buildings, where quite a few outbreaks have been reported, there is a notable lack of reported studies assessing preventive ventilation measures. Therefore, this study focused on practicing several ventilation measures in a 16-story high-rise building located in Montreal, Canada. A variety of inter-zonal tracer measurements, including room-to-floor and inter-floor tests, were carried out considering controlled airflow/pressure across zones. An automated data acquisition system was developed for real-time monitoring of tracer/CO2 spatial concentrations. Findings show that enabled ventilation with opened doors reduces CO2 concentrations by up to 82 % in nearby source locations and positively pressurized zones; however, negatively pressurized zones experience a 40 % increase in tracer exposure. With ventilation active, a corridor source leads to a higher risk of tracer exposure (up to 86 %) than the in-room source. Disabled ventilation with closed doors is a recommended ventilation measure, for corridors with infection sources, to minimize tracer transport across zones. Zones with infection sources follow the latter ventilation measure; however, ventilation with open doors offers a conditional ventilation measure if careful airflow is designed particularly at return and exhaust points within the ventilation system. This study has implications for practicing preventative ventilation measures for post-COVID-19 building practices and design considerations.

Novel Real-Time Data Acquisition System Of Hydrodynamic Signals Obtained In Laboratory

Understanding marine dynamics, particularly in coastal areas with high wave activity, cannot be achieved without physical modeling. However, when it comes to downscaled physical wave modeling, accurately recording wave data becomes a challenge, especially near coastlines where disturbances are common. Traditional water surface measurement tools, such as invasive wave probes, have proven to be both inaccurate and impractical. To overcome these limitations, this study presents a new data acquisition system (DAQ) utilizing resistive sensors and wireless transmission protocols to enhance the accuracy of wave measurements in laboratory-scale experiments. The data acquisition technology effectively measures water surface electric potential by utilizing specialized resistive probes. Additionally, the DAQ is equipped with an automatic calibration system using a vertical potentiometer, providing a cutting-edge solution to calibrate the invasive wave probes usually employed in several types of hydraulic physical modeling. The recorded data is efficiently handled by Arduino® board controllers, allowing for convenient wireless transmission for laboratory usage. This exceptional system surpasses traditional methods, offering a combination of versatility, cost-efficiency, and enhanced accuracy in capturing wave characteristics. In addition to describing the development of controllers and data processing algorithms, this study highlights their seamless integration into a unified solution for superior wave data collection.

Trigger transceiver and timing control system for ADITYA-U tokamak

The trigger transceiver and timing control system described in this study is developed to generate multiple triggers with varying delays to synchronize various subsystems with plasma discharges in the ADITYA Upgrade (ADITYA-U) tokamak (Ghosh et al., 2016) [1]. The Toroidal Field Power Supply (TFPS) is a fundamental component for each plasma discharge in the ADITYA-U, which generates a master trigger pulse for the particular discharge. The rise time of Toroidal Field Power Supply is 2 s and the loop voltage which is required to initiate the plasma discharge begins at 2.4 s after the master trigger. So the loop voltage is time-stamped at t = 0 and the master trigger from TFPS is time-stamped at t = −2.4 s and considered as a pre-trigger. Apart from this master trigger at t = −2.4 s, two more pre-trigger pulses, one at ∼ −40 ms and another at ∼ −4 ms, prior to the initiation of loop voltage trigger are generated by the power supply. These pre-trigger pulses generated by TFPS constitute the backbone of the entire discharge timing sequence, and they operate/control/initiate numerous ADITYA-U subsystems such as the gas puffing system, data acquisition system, radio frequency pre-ionization and heating system, plasma position control, and so on. So a suitable trigger generator system was needed to be developed in which three pre-trigger pulses (time stamped @ −2.4 s, −40 ms, and −4 ms prior to the loop voltage trigger) arriving from the TFPS may be selected and altered based on the experimental needs. To cater these requirements in ADITYA-U, a trigger transceiver and timing control system has been developed. The system has been successfully operated over ∼6000 discharges of ADITYA-U and functioned satisfactorily in all discharges in daily experiments with no failures. This study will discuss the detailed design elements and implementation of the Trigger Transceiver and Timing Control System for ADITYA-U plasma operations.