Distributed Data Acquisition System Research Articles

Three-Dimensional Resistivity and Chargeability Tomography with Expanding Gradient and Pole–Dipole Arrays in a Polymetallic Mine, China

Three-dimensional resistivity/chargeability tomography based on distributed data acquisition technology is likely to provide abundant information for mineral exploration. To realize true 3D tomography, establishing transmitter sources with different injection directions and collecting vector signals at receiver points is necessary. We implemented 3D resistivity/ chargeability tomography to search for new ore bodies in the deep and peripheral areas of Huaniushan, China. A distributed data acquisition system was used to form a vector receiver array in the survey area. First, by using the expanding gradient array composed of 11 pairs of transmitter electrodes, we quickly obtained the 3D distributions of the resistivity and chargeability of the whole area. Based on the electrical structure and geological setting, a NE-striking potential area for mineral exploration was determined. Next, a pole–dipole array was employed to depict the locations and shapes of the potential ore bodies in detail. The results showed that the inversion data for the two arrays corresponded well with the known geological setting and that the ore veins controlled by boreholes were located in the low-resistivity and high-chargeability zone. These results provided data for future mineral evaluation. Further research showed that true 3D tomography has obvious advantages over quasi-3D tomography. The expanding gradient array, characterized by a good signal strength and field efficiency, was suitable for the target determination in the early exploration stage. The pole–dipole array with high spatial resolution can be used for detailed investigations. Choosing a reasonable data acquisition scheme is helpful to improve the spatial resolution and economic efficiency.

Robot-Assisted Rehabilitation Architecture Supported by a Distributed Data Acquisition System.

Rehabilitation robotics aims to facilitate the rehabilitation procedure for patients and physical therapists. This field has a relatively long history dating back to the 1990s; however, their implementation and the standardisation of their application in the medical field does not follow the same pace, mainly due to their complexity of reproduction and the need for their approval by the authorities. This paper aims to describe architecture that can be applied to industrial robots and promote their application in healthcare ecosystems. The control of the robotic arm is performed using the software called SmartHealth, offering a 2 Degree of Autonomy (DOA). Data are gathered through electromyography (EMG) and force sensors at a frequency of 45 Hz. It also proves the capabilities of such small robots in performing such medical procedures. Four exercises focused on shoulder rehabilitation (passive, restricted active-assisted, free active-assisted and Activities of Daily Living (ADL)) were carried out and confirmed the viability of the proposed architecture and the potential of small robots (i.e., the UR3) in rehabilitation procedure accomplishment. This robot can perform the majority of the default exercises in addition to ADLs but, nevertheless, their limits were also uncovered, mainly due to their limited Range of Motion (ROM) and cost.

Improved Timing for better performance of distributed data acquisition systems - a further refinement

Continuing the works debuted in the previous work “Improved Timing for better performance of distributed data acquisition systems” the present paper refines and revisits the concept of a local oscillator with GPS corrections as a source of long-term stable reference clock signals with direct application in distributed data acquisition systems. The system as described herein can generate precise and repeatable clock source signals for trigger and sync of various data acquisition equipment when used in mixed and distributed architectures. These timing signals are a vital part of data acquisition as oftentimes raw data is processed as time series and correlations are made based on timestamps. This paper details improvements in implementation of a cost-effective high precision time base (reference clock) using a GPS receiver as a primary time source and a local high precision real time clock as a secondary oscillator. The improvements to the previous version come both from hardware refinements and from updated software with reduced latencies and reconfigured structure that allows for compensation of internal delays and internal process offsets.

Experience and Performance of Persistent Memory for the DUNE Data Acquisition System

Emerging high-performance storage technologies are opening up the possibility of designing new distributed data acquisition (DAQ) system architectures, in which the live acquisition of data and their processing are decoupled through a storage element. An example of these technologies is 3D XPoint, which promises to fill the gap between memory and traditional storage and offers unprecedented high throughput for nonvolatile data. In this article, we characterize the performance of persistent memory devices that use the 3D XPoint technology, in the context of the DAQ system for one large Particle Physics experiment, DUNE. This experiment must be capable of storing, upon a specific signal, incoming data for up to 100 s, with a throughput of 1.5 TB/s, for an aggregate size of 150 TB. The modular nature of the apparatus allows splitting the problem into 150 identical units operating in parallel, each at 10 GB/s. The target is to be able to dedicate a single CPU to each of those units for DAQ and storage.

Improved Timing for better performance of distributed data acquisition systems

Distributed data acquisition systems are the norm in the great majority of industry branches where the process to be controlled covers a physically large and often fragmented area. Many local smaller data acquisition modules are interfaced and pass raw or pre-processed data along with the timing signals. These timing signals are a vital part of data acquisition as oftentimes raw data is processed as time series and correlations are made based on timestamps. This paper presents a study for implementation of a cost-effective high precision time base (reference clock) using a GPS receiver as a primary time source and a local high precision real time clock as a secondary oscillator.

Design and implementation of a distributed data acquisition function architecture based on DOA/Handle technology

With the development of new generation Internet technology, Digital Object Architecture (DOA)/Handle system plays an important role in industrial system. The development and technical characteristics of DOA/Handle technology is studied in this paper. Then function architecture of distributed data acquisition system based on DOA/Handle technology is proposed. Through the detailed design of the functions and characteristics of the architecture, the core functions such as distributed data acquisition, distributed data management, data security sharing, and data security governance are realized in the industrial Internet environment. At the end of the paper, the typical scenarios of this architecture are summarized, and a prospect of the application prospect of DOA/Handle technology is introduced.

Performance comparison between signal digitizers and low-cost digital oscilloscopes: spectroscopic, pulse shape discrimination and timing capabilities for nuclear detectors

Signal digitizers revolutionized the approach to the electronics readout of radiation detectors in Nuclear Physics. These highly specialized pieces of equipment are designed to acquire the signals that are characteristic of the detectors in nuclear physics experiments. The functions of the several modules that were once needed for signal acquisition, can now be substituted by a single digitizer. As suggested by the name, with such readout modules, signals are first digitized (i.e. the signal waveform is sampled and converted to a digital representation) and then either stored or analyzed on-the-fly. The performances can be comparable or better than the traditional analog counterparts, in terms of energy, time resolution, and acquisition rate. In this work, we investigate the use of general-purpose digital oscilloscopes as signal digitizers for nuclear detectors. In order to have a proper comparison, we employ a distributed data acquisition system (DAQ), that standardizes the interface between the hardware and the on-line data analysis. The signals, from a set of typical radiation detectors, are digitized and analyzed with the very same algorithms in order to avoid biases due to different software analysis. We compare two traditional signal digitizers (CAEN DT5725 and CAEN DT5751) to two low-cost digital oscilloscopes (Digilent Analog Discovery 2, and Red Pitaya STEMLab 125-14), in terms of their capabilities for spectroscopy (energy resolution), time resolution, pulse shape discrimination, and maximum acquisition rate.

Reliability Assessment of a Large Diesel Generator Fleet

PowerSecure (PS), a subsidiary of Southern Company, operates over 1600 microgrids including a large fleet of standby diesel generators. Machines range from 125 to 2800 kW. There are two missions: standby power after utility failure and load management when utility is available. This report updates generator reliability data published over 20 years ago. These results are first derived from uniform records from a distributed data acquisition system. The unique aspects of this effort include automated data collection, analysis, and storage producing a standardized record for all machines and events. This greatly reduces the effort required to prepare reports and analysis. The automated collection largely eliminates human errors in data entry, and prevents post hoc adjustment of mission success or failure. We are not aware of previous published generator data using automated data acquisition. This study counts all failures and excludes none, whereas previous studies exclude more than half. This analysis expresses reliability as experienced by the customers. The number of machines, years in service, and years of operation greatly exceed the sum of previous published studies, enabling calculation of useful confidence limits. The fleet is heterogenous with machines from over a dozen manufacturers and many power ratings. Machine reliability was consistent across brands, and there is no significant difference in reliability for different size machines. This common assumption was not supported by the prior studies. High-quality data enables reliability growth management practices. The fleet reliability for outage demands of all durations increased from 95% in 2011 to 98% in 2014-18. Analysis of failures arrival time shows that the failure rate is strongly dependent on mission duration. The failure rates after 14 h are approximately 1% of the value for the first 30 min of operation. This has important implications for designing systems to meet specified reliability targets, and in interpreting and comparing results from fleets with different mission durations.

On-site Evaluation of Rehabilitation Patients Monitoring System Using Distributed Wireless Gateways.

This paper presents a hands-free monitoring system for rehabilitation patients that uses wireless gateways to fully cover the floor of an inpatient ward. For stroke rehabilitation, 24-hour monitoring is recommended. Low-power wireless such as Bluetooth Low Energy (BLE) is suitable for this purpose because of its long battery life. However, most systems require smartphones or tablet computers to acquire patient data due to BLE's short communication range. Instead of using smartphones, we installed around fifty BLE gateways to implement a hands-free data acquisition system. The system was evaluated both quantitatively and qualitatively. The data acquisition rate of the system was found to be over 90% through 24-hour patient monitoring, which is almost the same as that for systems using smartphones. Questionnaires about usability administered to both medical staff and patients suggested that they felt the smartphone-less system was more comfortable than the smartphone system. These results suggest the possibility of using such a distributed data acquisition system in real medical wards and its benefits.

A Fully Programmable White-Rabbit Node for the SKA Telescope PPS Distribution System

Distributed data acquisition (DAQ) systems are in charge of converting different analog environment signals into digital values to perform control and monitor tasks. They require a computer network technology to share data between their different elements. One of their main issues is to match data with the specific events under study. A possible solution is to include an event synchronization technology such as Network Time Protocol (NTP), Precise Time Protocol (PTP), or White Rabbit (WR). This contribution proposes a high-performance distributed timing system based on the WR technology. We focus on the square kilometer array (SKA) project as an example of the distributed DAQ system. The SKA project has a strict timing requirements for its operation with a performance below 2 ns. This accuracy is not achievable by current standard synchronization technologies such as NTP or PTP. Under this context, the authors propose the WR zynq embedded node (WR-ZEN) platform as a candidate for the SKA’s pulse per second (PPS) distribution system. It is a new design that integrates the WR technology, thus enabling the subnanosecond accuracy. Finally, the WR-ZEN has been evaluated in different scenarios to demonstrate its timing performance in dynamic environment conditions fulfilling the SKA telescope requirements for PPS distribution.

A Review of Distributed Algorithms for Principal Component Analysis

Principal component analysis (PCA) is a fundamental primitive of many data analysis, array processing, and machine learning methods. In applications where extremely large arrays of data are involved, particularly in distributed data acquisition systems, distributed PCA algorithms can harness local communications and network connectivity to overcome the need of communicating and accessing the entire array locally. A key feature of distributed PCA algorithm is that they defy the conventional notion that the first step toward computing the principal vectors is to form a sample covariance. This paper is a survey of the methodologies to perform distributed PCA on different data sets, their performance, and of their applications in the context of distributed data acquisition systems.

Study of web-based management for EAST MDSplus data system

A large distributed data acquisition system based on PXI/PXIe technology has been implemented on EAST tokamak. Now the whole data system has more than 60 data acquisition units and more than 3000 raw channels, and the maximum data throughput is about 5GBytes/s. Most of the acquired data are continuously stored into MDSplus Wan et al. database, moreover the calculated and analyzed data are also saved into MDSplus. In case of long-term discharge mode, the raw data of one shot is more than 1TBytes, and the total data of one campaign is more than 100TBytes.MDSplus is helpful to store tokamak experiment discharge data, and the scientific data are saved into database by shot and tree, and it is easy to know the signal information of one shot or tree. However, it is difficult to get the general metadata information of all the shots and trees. Even if we can read the information by some scripts, but it is not so convenient and the data retrieval speed is slow. So we have planned to design a data statistics and retrieval system for EAST MDSplus data system, which can provide all the metadata information of all the trees such as signal name, sampling rate, data size, data available or not, and so on, basing on these metadata the system can give detailed statistics and reports automatically by some pre-defined model, which can help users to grasp the status and schema of all the data. The system has been developed based on apache/mysql/php framework and the PCIe SSD storage is adopted to promote the database access speed. The design details will be given in the paper.

A distributed data acquisition system for nuclear detectors

Nowadays, many examples of data acquisition (DAQ) software for experimental nuclear physics are monolithic processes that run on a computer attached to the DAQ hardware. In this article we present a distributed DAQ system developed for the C-BORD project. With our system, we propose a novel approach, in which each task related to the different DAQ parts (acquisition, pre-process, analysis, etc.) runs in a separate process. In particular, the system is composed of a set of servers that exchange information through dedicated communication sockets. Therefore, with this architecture, an important advantage is the possibility to run the processes on different computers to distribute the computational load. The initial tests of the system have been giving excellent results, both in terms of performance (i.e., maximum acquisition rates) and stability. The project entitled “Effective container inspection at BORDer control points” (C-BORD) is funded by the European H2020 programme. Its aim is to develop a comprehensive set of technologies for the generalized non-intrusive inspection (NII) of containers and large-volume freight at the European Union border.

Near Theoretical Gigabit Link Efficiency for Distributed Data Acquisition Systems.

Link efficiency, data integrity, and continuity for high-throughput and real-time systems is crucial. Most of these applications require specialized hardware and operating systems as well as extensive tuning in order to achieve high efficiency. Here, we present an implementation of gigabit Ethernet data streaming which can achieve 99.26% link efficiency while maintaining no packet losses. The design and implementation are built on OpenPET, an opensource data acquisition platform for nuclear medical imaging, where (a) a crate hosting multiple OpenPET detector boards uses a User Datagram Protocol over Internet Protocol (UDP/IP) Ethernet soft-core, that is capable of understanding PAUSE frames, to stream data out to a computer workstation; (b) the receiving computer uses Netmap to allow the processing software (i.e., user space), which is written in Python, to directly receive and manage the network card's ring buffers, bypassing the operating system kernel's networking stack; and

A Distributed Data Acquisition System for the Sensor Network of the TAWARA_RTM Project

This paper describes a distributed Data Acquisition System (DAQ) developed for the TAWARA_RTM project (TAp WAter RAdioactivity Real Time Monitor). The aim is detecting the presence of radioactive contaminants in drinking water; in order to prevent deliberate or accidental threats. Employing a set of detectors, it is possible to detect alpha, beta and gamma radiations, from emitters dissolved in water. The Sensor Network (SN) consists of several heterogeneous nodes controlled by a centralized server. The SN cyber-security is guaranteed in order to protect it from external intrusions and malicious acts. The nodes were installed in different locations, along the water treatment processes, in the waterworks plant supplying the aqueduct of Warsaw, Poland. Embedded computers control the simpler nodes, and are directly connected to the SN. Local-PCs (LPCs) control the more complex nodes that consist signal digitizers acquiring data from several detectors. The DAQ in the LPC is split in several processes communicating with sockets in a local sub-network. Each process is dedicated to a very simple task (e.g. data acquisition, data analysis, hydraulics management) in order to have a flexible and fault-tolerant system. The main SN and the local DAQ networks are separated by data routers to ensure the cyber-security.

Distributed Data Acquisition System for Condition Monitoring of Low-speed Machines Using Wireless Sensor Networks

Low-speed machines play an important role in industrial production, and the condition monitoring of these machines is of great importance. Monitoring with wireless sensor network (WSN) has many advantages. To monitor the condition of low-speed machines, we need to acquire low-frequency, weak and hardly-varying physical signals. As such, we designed a WSN system for high-precision signal acquisition. Actual measurement results showed that the acquisition precision of nodes could reach 0.01 mV. When the sensor nodes continuously acquired and sent data, the energy conversion efficiency was higher than 90% and the nodes’ power consumption came to about 110mW. The WSN system was designed based on the low-power consumption 802.15.4 MAC/Zigbee, and the WSN was built through MESH topology. Data transmission was stable and the PER was lower than 1%. The measurement results under laboratory and industrial field conditions showed that the WSN system designed met the requirements for on-site data acquisition and monitoring of low-speed machines.

Principles for the development of distributed data-acquisition systems based on ontologies

This paper investigates the issues of the automated construction of distributed data-acquisition systems using a formalized description of a domain. Techniques for the creation of ontological descriptions are reviewed. A new method for domain ontology construction is proposed. Object, relational, and hierarchical software models are developed based on it. A technology for the separation of the functionality of a dataacquisition system from their objective description is presented.

New DAQ System for the CANDLES Experiment

A new data acquisition (DAQ) system for the CANDLES experiment was developed using the SpaceWire protocol and the DAQ-Middleware framework. The CANDLES experiment uses a trigger board and Flash Analog-to-Digital Converters (FADCs). The SpaceWire helps us construct the DAQ system with a flexible and multi-path access to FADCs and the trigger board. FADCs have a ring buffer with three buffers to detect sequential decays from backgrounds. We developed the DAQ system with parallel read-out to reduce the dead time at high trigger rates using three read-out personal computers (PCs) that are connected to the three buffers in FADCs one by one. Each PC connects all FADCs and the trigger board and gathers a complete data set of one event without any event builder. The maximum DAQ speed of parallel read-out by three PCs was 2.4 times higher than that of single read-out. In order to collect event data sets from PCs, we built the network distributed DAQ system through Ethernet, which is naturally introduced with the DAQ-Middleware. To realize remote monitoring and histogram modification while the DAQ running, we also developed a dynamic online monitor system independent with the DAQ-Middleware.

Data-flow Performance Optimisation on Unreliable Networks: the ATLAS Data-Acquisition Case

The ATLAS detector at CERN records proton-proton collisions delivered by the Large Hadron Collider (LHC). The ATLAS Trigger and Data-Acquisition (TDAQ) system identifies, selects, and stores interesting collision data. These are received from the detector readout electronics at an average rate of 100 kHz. The typical event data size is 1 to 2 MB. Overall, the ATLAS TDAQ system can be seen as a distributed software system executed on a farm of roughly 2000 commodity PCs. The worker nodes are interconnected by an Ethernet network that at the restart of the LHC in 2015 is expected to experience a sustained throughput of several 10 GB/s.A particular type of challenge posed by this system, and by DAQ systems in general, is the inherently burstynature of the data traffic from the readout buffers to the worker nodes. This can cause instantaneous network congestion and therefore performance degradation. The effect is particularly pronounced for unreliable network interconnections, such as Ethernet.In this paper we report on the design of the data-flow software for the 2015-2018 data-taking period of the ATLAS experiment. This software will be responsible for transporting the data across the distributed Data-Acquisition system. We will focus on the strategies employed to manage the network congestion and therefore minimisethe data-collection latency and maximisethe system performance. We will discuss the results of systematic measurements performed on different types of networking hardware. These results highlight the causes of network congestion and the effects on the overall system performance.

Intelligent operations of the data acquisition system of the ATLAS experiment at LHC

The ATLAS experiment at the Large Hadron Collider at CERN relies on a complex and highly distributed Trigger and Data Acquisition (TDAQ) system to gather and select particle collision data obtained at unprecedented energy and rates. The Run Control (RC) system is the component steering the data acquisition by starting and stopping processes and by carrying all data-taking elements through well-defined states in a coherent way. Taking into account all the lessons learnt during LHC's Run 1, the RC has been completely re-designed and re-implemented during the LHC Long Shutdown 1 (LS1) phase. As a result of the new design, the RC is assisted by the Central Hint and Information Processor (CHIP) service that can be truly considered its “brain”. CHIP is an intelligent system able to supervise the ATLAS data taking, take operational decisions and handle abnormal conditions. In this paper, the design, implementation and performances of the RC/CHIP system will be described. A particular emphasis will be put on the way the RC and CHIP cooperate and on the huge benefits brought by the Complex Event Processing engine. Additionally, some error recovery scenarios will be analysed for which the intervention of human experts is now rendered unnecessary.