The Development of the Virtual Data Acquisition and Analysis System

The DAQ group of KENS has developing a data acquisition (DAQ) system for neutron scattering experiments in the MLF/J-PARC. The DAQ system has adopting the event-mode data taking instead of a conventional histogram-mode data taking to expand flexibility of measurements. The KENS-DAQ group, therefore, has developed the new DAQ system so called a NeuNET system for 3He PSD. The NeuNET system is realized scalable and distributed DAQ system by using electronics modules with a high speed network data transfer technique and software which based on component middleware.

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

Service-oriented architecture of adaptive, intelligent data acquisition and processing systems for long-pulse fusion experiments

Data collection and analysis is vital for evaluating the performance of any equipment or system. Though the methodology of collection, transmission, storage and retrieval varies in different scenarios, the basic components of the set-up remain the same. The Data Acquisition and Monitoring System evolved from the need for remote monitoring of facilities that did not have an independent reliable infrastructure to implement a full-fledged SCADA system. Back when IT infrastructure was prioritized for business communications within the limited bandwidth allocated, collection and transmission of process data through the available network infrastructure was a challenge. More so when there are concerns regarding the confidentiality of data being collected and transmitted. Individual facilities were provided with local instrumentation and controls for reliable operations. With the growing production rates, the focus generally goes for improving the processing facilities rather than reading, reporting or recording. Instead of an independent dedicated network for Supervisory Control and Data Acquisition system that mandate a huge infrastructural cost and dedicated skilled personnel, a pilot project was initiated with a minimum budget to test data transfer through existing communication network. Field transmitters were installed on Wellheads, Risers and Manifolds and Remote Terminal Units were provided to collect data from two platforms and to facilitate data transfer to the servers through existing microwave communication network with minimum field instrumentation. Considering bandwidth limitations and priority for business communications, servers in redundant configuration were placed strategically to ensure continuous data gathering. Pilot project was successful in providing reliable data and trends with minimum disruptions. Augmentation of DAMS network was envisioned to implement Digital Oil Field for monitoring multiple assets in real time. Implementation of Digital Oil Field continued with the addition of new field instrumentation and RTUs followed by server upgrades and integration of PLC based platform control systems to add four major producing platforms to the Data Acquisition and Monitoring System through existing microwave communication network. Upon successful commissioning, it was possible to gather data from various wellheads, process equipment and other independent meters for remote real time monitoring and analysis through user friendly HMI screens and customized dashboards to manage multiple assets effectively, improving performance evaluation, safety and reliability of operations.

With the rapid development of the WoT, acquisition requirements to the data grow with each passing day. However, the existing data acquisition systems usually use the upload mode. Uploading data not only takes a lot of time, but also requires staff to continuously monitor on duty. Aiming at the problem of enterprise management data acquisition, a WoT-based enterprise management data acquisition and analysis system is constructed. The system obtains multiple monitoring data through the data acquisition module and integrates these data through the processing module, which can solve the problems of traditional data acquisition systems. In order to effectively fuse data, based on canonical correlation analysis (CCA), the multiple order statistics correlation discrimination analysis algorithm is proposed as a fusion strategy. Experimental results show that the fusion strategy based on CCA can effectively integrate monitoring data and accurately identify different characters.

Development of a pipelined data acquisition system for experiments at J-PARC

For accurate and optimized aerodynamic study on aerospace vehicle models in a wind tunnel, a high performance automated data acquisition (DAQ) system is required. To serve the purpose, a DAQ system integrated with model attitude control mechanism (robotic arm) has been developed at National Wind Tunnel Facility (NWTF), IIT Kanpur (India). The system has been developed using virtual instrumentation (LabVIEW) technique and PXI architecture which enhance the productivity and lower the cost through easy-to-integrate LabVIEW software and PXI modular hardware. This paper presents the implementation aspects of the developed DAQ system along with the system application example for optimized wind tunnel study on an aircraft model.

A Data Acquisition (DAQ) system has become to be used in the field of large-scale scientific experiments with the advance of information technology. Especially, in DAQ System for a high energy physics experiment such as ATLAS experiment at CERN, parallel processing using a large number of network switches enhances the efficiency of acquiring and analyzing experimental data. Additionally, a DAQ system has many-to-one simultaneous communication that gathers data generated by a large number of detectors into one computer for analysis. Properties of such communication can cause network traffic congestions and packet losses, thereby decreasing throughput. One solution for such problem is Data Center Bridging (DCB) technology used to establish lossless Ethernet networks. In addition, since event fragments in a large-scale DAQ system are transmitted using many network switches, the buffer size of a network switch is critical. This study focuses on the queue of the network switch of a DAQ system using DCB and the effects on system performance. The fairness and throughput of each flow in many-to-one simultaneous communication system were measured. We confirmed maximum performance was achieved when an average queue length in the network switch was small.

The Boeing Company is designing, developing and manufacturing the Core Stage and Avionics for NASA's heavy lift rocket, the Space Launch System (SLS), which will support missions beyond low earth orbit for the first time since the Apollo days. On the SLS vehicle many sensors are selected and used to provide critical information for testing, ground operations, and vehicle flight environments. Appropriate data acquisition systems that can interface and process the selected sensors is important to the success of the program. In this program, multiple data acquisition systems are used to interface with sensors at various development stages of the SLS vehicle, and at different sensor criticality levels. These phased configurations of data acquisition classes and complexity range from gathering sensor data during system level testing at Stennis Space Center (SSC), to transmitting flight information after liftoff at the Kennedy Space Center. One challenge that engineers are faced with pertains to how the data acquisition system is defined prior to understanding the quantity and type of sensors required for the application. This paper focuses mainly on the SLS flight system and provides a general overview of the system architecture. The paper also addresses the strategy used to define the data acquisition system, along with the methodology for selecting data acquisition cards that fit with the application.

A data acquisition system is required to interpret the electrical signals produced by radiation detectors when a gamma ray, neutron or other radiation type interacts with it. The data acquisition system can take on many forms to match the wide variety of radiation detector types available and the different ways in which the signals from these detectors can be processed to give information on the detected radiation. First presented is a detailed overview of a variety of analog data acquisition topologies ranging from simple radiation event counters through to pulse shape discrimination. A comparison is then made with the digital counterparts of these data acquisition topologies, highlighting the relative merits and shortcomings of both analog and digital implementations. Next, the important factors relating to how data is processed, stored and transferred through different stages of a data acquisition chain is discussed and suggestions given on how to avoid bottle-necks and ensure balanced data flow throughout the system. Also discussed are the key challenges associated with the design and configuration of data acquisition systems for active interrogation (AI) environments such as dealing with the high event rates, capturing the time development of active radiation signatures, and techniques for working with pulsed interrogating sources.

The use of an automated Data Acquisition System (DAS) is very important in testing and measurement systems. The desire is extremely high in the DAS with high speed, multi-channel, and large capacity, so research in this area becomes very significant. The growing problem in DAS is to acquire the data with the required data rate and store data onto the on-chip memory. Microcontroller, microprocessor or Digital Signal Processors (DSP) devices can be programmed as a DAS, but these devices comprise problems, such as slower data acquisition rates, nonavailability of sufficient on-chip memory, etc. To overcome these above drawbacks, this paper provides an approach to design and develop DAS based on the Field Programmable Gate Array (FPGA). To acquire the data from Analog to Digital Converter (ADC) to FPGA, an Inter Integrated Circuit (I2C) serial communication protocol is used. I2C master communication protocol is designed and developed using VHDL with the Quartus II version 13.1, and the I2C master protocol is implemented in cyclone III FPGA. FPGA is acting as a master controller. DAS with the FPGA will provide the better acquisition results compared to the existing acquisition system.

Structural health monitoring for bridge is becoming a more widely accepted way to improve bridge management. To implementation the above objective, this paper presents a GPRS-based bridge remote data acquisition and monitoring system. It is a kind of unmanned automation, intelligent data acquisition system. The network structure of the system, data transmission, information collection and data-processing model methods provide a common, advanced and effective information acquisition model for other supervisory control and data acquisition systems. This system are highly portable with little changes can be applied to other systems. These will not only improve the automation degree of monitoring, and also a lot of human and financial resources are saved with a high practical value and economic value.

The development of data acquisition system for operation of the Kartini reactor was carried out by using a programable-logic controller (PLC) and based on the recommendation of an expert team of the International Atomic Energy Agency which justifies that the previous data acquisition system of the reactor operation has been considered obsolete. This research purpose is to follow up the recommendation by using a recent technology of PLC as the basis of the system. The parameter acquisition method was done by acquiring the analogue and digital voltage signals by the PLC and processing them into values accordingly. Analogue parameters: linear power, logarithmic power percent, period, and three control bars, Digital parameters: trigger trip signals. Parameter values are visually displayed using LabVIEW. The test method was comparing the obtained values to the current monitoring subsystem. Test results: linear power error is 0.09%; period error is 0.8%; and error of the three control rods is below 1%. All digital signal test results successfully show appropriate trip conditions when active. The conclusion of this study is successful in making a design of the Kartini Reactor process parameter acquisition system with small relative errors to the existing system.

Research on high-speed data acquisition system of negative ion source breakdown

The Simons Array upgrades the POLARBEAR experiment, which measures the cosmic microwave background from the Atacama Desert in Chile, with three newly developed receivers. Each receiver has 7,588 transition-edge sensor bolometers with a raw data rate of approximately 20 MB/s. This significantly increased data rate required us to develop a new data-acquisition (DAQ) and data-management system. As the network bandwidth from our observatory to our data-storage sites outside Chile is not high enough to send all the raw data, we compress the raw data on-site. The expected yearly compressed data rate is approximately 60 TB from each receiver. We have also developed a new housekeeping DAQ system. The new housekeeping DAQ system is a distributed system to handle the various newly added monitoring systems and to better understand our instruments and environments. Those data can also be fetched by another module for real-time monitoring of our instrument from all over the world with latencies on the order of minutes. We deployed the first receiver in late 2018 and started the commissioning of the DAQ system. The DAQ system has been working without significant problems and already accumulates a considerable amount of the new receiver data from the commissioning observations. In this presentation, we summarize and report the status of the new systems.