scholarly journals DIGITAL TWIN OF GAS RECIPROCATING COMPRESSOR UNIT: CONCEPT, ARCHITECTURE & PILOT IMPLEMENTATION

2021 ◽  
pp. 68-72
Author(s):  
А. Prokhorenko ◽  
S. Kravchenko ◽  
E. Solodkii
Keyword(s):  
Data Collection ◽  
Internet Of Things ◽  
Combustion Engine ◽  
Piston Compressor ◽  
Physical Object ◽  
Technical Condition ◽  
Service Planning ◽  
Real Object ◽  
Term Operation ◽  
Digital Twin

Combination of information and operational technologies has led to a new way of production, to a new technological revolution, known as Industry 4.0. The Digital Twin plays a central role in this technology. The Digital Twin is a predictive maintenance tool, and allows you to simulate various options for device failures taking into account their operation modes, environmental influences and various degrees of wear. The concept of creating a digital twin of a real physical object of research is proposed - an AJAX DPS-180 internal combustion engine with a gas piston compressor, which is designed to pump gas from gas wells. A feature of its work is autonomous long-term operation in the field with the remoteness of the service personnel, direct environmental impact and ensuring the reliability and stability of work. Therefore, monitoring the parameters of the engine with the subsequent prediction of its failures is especially important. The work on creating a digital twin for AJAX DPS-180 is being carried out in cooperation and with the support of Armco-Engineering, the operator of this equipment. Six stages of the process of creating a digital twin of a given object are shown: collection and preliminary processing of data on the technical state of a real object; early detection of malfunctions, predicting the time of failure; service planning; optimization of financial and time resources for service. Equipping a real object with various sensors made it possible to continuously collect data on its technical condition, and technologies of the industrial Internet of things, such as Big Data and the predictive statistical model, predict failure times with high accuracy. The developed and implemented schemes for equipping an object with data collection equipment and a diagram of the flow of this data in the Internet of Things are presented. The basis of the data collection system is a microcontroller, a set of a crankshaft speed sensor and thermocouples, a multiplexer and 16-bit analog-to-digital converters that convert thermo-EMF of thermocouples. At the moment, channels for measuring the speed, coolant and exhaust gas temperatures have been implemented. It is proposed to use the ThingSpeak server as a remote resource as a cloud aggregator and carrier of this data. The MATLAB mathematical package integrated into the resource is used as a data analyzer.

scholarly journals Digital Twin Conceptual Model within the Context of Internet of Things

2020 ◽  
Vol 12 (10) ◽  
pp. 163 ◽  
Author(s):  
A. R. Al-Ali ◽  
Ragini Gupta ◽  
Tasneem Zaman Batool ◽  
Taha Landolsi ◽  
Fadi Aloul ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Conceptual Model ◽  
Environmental Parameters ◽  
3D Models ◽  
Physical Object ◽  
Virtual Space ◽  
Computing Device ◽  
Digital Twin ◽  
Smart Healthcare ◽  
Space Data

As the Internet of Things (IoT) is gaining ground and becoming increasingly popular in smart city applications such as smart energy, smart buildings, smart factories, smart transportation, smart farming, and smart healthcare, the digital twin concept is evolving as complementary to its counter physical part. While an object is on the move, its operational and surrounding environmental parameters are collected by an edge computing device for local decision. A virtual replica of such object (digital twin) is based in the cloud computing platform and hosts the real-time physical object data, 2D and 3D models, historical data, and bill of materials (BOM) for further processing, analytics, and visualization. This paper proposes an end-to-end digital twin conceptual model that represents its complementary physical object from the ground to the cloud. The paper presents the proposed digital twin model’s multi-layers, namely, physical, communication, virtual space, data analytic and visualization, and application as well as the overlapping security layer. The hardware and software technologies that are used in building such a model will be explained in detail. A use case will be presented to show how the layers collect, exchange, and process the physical object data from the ground to the cloud.

Design of an External Combustion Engine and its Application in a Free Piston Compressor

2007 ◽  
Vol 3 ◽  
Author(s):  
Jonathan Hogan Webb
Keyword(s):  
Combustion Engine ◽  
Piston Compressor ◽  
Dead Volume ◽  
Transfer Energy ◽  
Free Piston ◽  
Combustion Gases ◽  
Intermediate Chamber ◽  
Fuel Mixtures ◽  
External Combustion ◽  
External Combustion Engine

The design of a free piston compressor and an analysis on integrating an external combustion engine into the compressor design are presented in this article. A free piston compressor is a device which converts chemical energy to work on a volume of air through the kinetic energy of an inertia driven piston, which is not rigidly attached to a ground. An external combustion engine serves as in intermediate chamber which transfers combustion gases to a device to perform some work. The following discusses the design and experiments on an external combustion engine, with a focus on eliminating an injection holding force on a free piston compressor’s elastomeric membranes. The efficiency of the external combustion engine to transfer energy without significant losses due to heat, dead volume, air/fuel mixtures, and actuated valve speed are also presented.

scholarly journals How to increase the value of self-reported health service data by using data linkage: a case study

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
W Peng ◽  
J Maguire ◽  
A Hayen ◽  
J Adams ◽  
D Sibbritt
Keyword(s):  
Data Collection ◽  
Health Service ◽  
Health Services ◽  
Stroke Prevention ◽  
Data Linkage ◽  
Recurrent Stroke ◽  
Service Planning ◽  
Stroke Survivors ◽  
Reported Data

Abstract Background This is a case study for recurrent stroke prevention. Lifestyle factors account for about 80% of the risk of recurrent stroke. Most health services studies examining stroke prevention rely on stroke survivors' self-reported lifestyle behaviour data. How can researchers increase the value of collected self-reported data to provide additional information for more comprehensive assessments? Methods 45 and Up Study is the largest ongoing study in the Southern Hemisphere focusing on the health of people aged 45 years and older living in NSW, Australia. This case study linked self-reported longitudinal lifestyle data in the 45 and Up Study, with corresponding mortality data (i.e. NSW Registry of Births, Deaths and Marriages & NSW Cause of Death Unit Record File) and hospital data (i.e. NSW Admitted Patient Data Collection) via the Centre for Health Record Linkage (CHeReL). The main outcome measures are health services, clinical outcomes, and mortality rates for stroke care. The analyses will include descriptive analysis, multivariate regression analysis, and survival analysis. Results A total of 8410 stroke survivors who participated in the 45 and Up Study were included in this data linkage study. From January 2006 to December 2015, 99249 hospital claims (mean: 13 times admission to hospital per person) and 2656 death registration records have been linked to these participants. The mean age of the stroke survivors was 72 (SD = 11) years, with 56% being males. These results are preliminary and more analyses will be conducted by using quality of life status, clinical diagnosis, comorbidities, and procedures. Conclusions Data linkage enables researchers to generate comprehensive findings on health services studies and gain a more holistic understanding of the determinants and outcomes of stroke prevention with lower data collection costs and less burden on participants. Key messages Data linkage brings about a new opportunity for self-reported data on health services utilisation. It is a cost-effective way to enhance existing self-reported data via the data linkage approach to increase its usefulness for informing health service planning.

scholarly journals Bringing Older Adults to the Table: Opportunities for Consumer Engagement in Planning and Policy Making

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 102-102
Author(s):  
Alice Prendergast ◽  
Kristi Fuller
Keyword(s):  
Data Collection ◽  
Community Engagement ◽  
Community Involvement ◽  
Social Connectedness ◽  
Planning Process ◽  
The United States ◽  
Lessons Learned ◽  
Service Planning ◽  
Community Members ◽  
Design Data

Abstract Efforts to include community voice in health policy and service planning are gaining recognition and support in the United States. Findings suggest community involvement can contribute to a better understanding of systems and factors that impact health, and, subsequently, more effective and sustainable policy and program design. Additionally, engagement can increase community buy-in, and community members can gain a greater awareness of services; increased confidence navigating systems; feelings of social connectedness; and capacity to advocate around issues through participation. Despite these findings, the extent to which community members are engaged in planning and decision-making varies considerably. Researchers from Georgia State University conducted a review of state plans on aging using the Person-Centered Outcomes Research Initiative (PCORI) Engagement Principles and the Health Research & Educational Trust’s Community and Patient Engagement Spectrum as frameworks to assess evidence of community engagement. The frameworks recognize engagement throughout the planning process, including design, data collection and interpretation, and dissemination. The review revealed that few planning processes described significant engagement, but rather met the minimal requirements established by federal policy. Federal guidance on community-informed planning practices is sparse, as are resources to support states in adopting these processes. To address this gap, the research team drew on the frameworks and other promising practices to design two community engagement projects, both in partnership with Georgia’s Division of Aging Services. Methods for participant engagement, data collection, interpretation and application of results, and lessons learned through both projects will be discussed, as well as potential implications.

Data collection of safety accidents in sports training of athletes with Internet of Things technology

2021 ◽  
pp. 1-7
Author(s):  
Zhiping Wang ◽  
Xinxin Zheng ◽  
Zhichen Yang
Keyword(s):  
Information Technology ◽  
Data Collection ◽  
Internet Of Things ◽  
The Internet ◽  
Sports Training ◽  
Accident Data ◽  
And Performance ◽  
Control Technologies ◽  
Internet Of Things Technology ◽  
The Internet Of Things

The Internet of Things (IoT) technology is an information technology developed in recent years with the development of electronic sensors, intelligence, network transmission and control technologies. This is the third revolution in the development of information technology. This article aims to study the algorithm of the Internet of Things technology, through the investigation of the hazards of athletes’ sports training, scientifically and rationally use the Internet of Things technology to collect data on safety accidents in athletes’ sports training, thereby reducing the risk of athletes’ sports training and making athletes better. In this article, the methods of literature research, analysis and condensing, questionnaire survey, theory and experiment combination, etc., investigate the safety accident data collection of the Internet of Things technology in athletes’ sports training, and provide certain theories and methods for future in-depth research practice basis. The experimental results in this article show that 82% of athletes who are surveyed under the Internet of Things technology will have partial injuries during training, reducing the risk of safety accidents in athletes’ sports training, and better enabling Chinese athletes to achieve a consistent level of competition and performance through a virtuous cycle of development.

Traffic Flow Data Collection and Signal Control System Based on Internet of Things and Cloud Computing

2013 ◽  
Vol 846-847 ◽  
pp. 1608-1611 ◽  
Author(s):  
Hui Jie Ding
Keyword(s):  
Cloud Computing ◽  
Control System ◽  
Data Collection ◽  
Internet Of Things ◽  
Traffic Flow ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Flow Data ◽  
Traffic Jam ◽  
Sensing Data

As more and more cars are in service, the traffic jam becomes a serious problem in our society. At the same time, more and more sensors make the cars more and more intelligent, and this promotes the development of Internet of things. Real time monitoring the cars will produce massive sensing data, the Cloud computing gives us a good manner to solve this problem. In this paper, we propose a traffic flow data collection and traffic signal control system based on Internet of things and the Cloud computing. The proposed system contains two main parts, sensing data collection and traffic status control subsystem.

scholarly journals Towards Self-Awareness Privacy Protection for Internet of Things Data Collection

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Kok-Seng Wong ◽  
Myung Ho Kim
Keyword(s):  
Data Collection ◽  
Internet Of Things ◽  
Personal Data ◽  
Self Awareness ◽  
Privacy Concern ◽  
Goods And Services ◽  
Data Collector ◽  
Inaccurate Data ◽  
Secure Protocol ◽  
The Internet Of Things

The Internet of Things (IoT) is now an emerging global Internet-based information architecture used to facilitate the exchange of goods and services. IoT-related applications are aiming to bring technology to people anytime and anywhere, with any device. However, the use of IoT raises a privacy concern because data will be collected automatically from the network devices and objects which are embedded with IoT technologies. In the current applications, data collector is a dominant player who enforces the secure protocol that cannot be verified by the data owners. In view of this, some of the respondents might refuse to contribute their personal data or submit inaccurate data. In this paper, we study a self-awareness data collection protocol to raise the confidence of the respondents when submitting their personal data to the data collector. Our self-awareness protocol requires each respondent to help others in preserving his privacy. The communication (respondents and data collector) and collaboration (among respondents) in our solution will be performed automatically.

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