Architecture of Compressor Equipment Monitoring and Control Cyber-Physical System Based on Influxdata Platform

2019 ◽  
Author(s):  
Aleksey Kychkin ◽  
Aleksadr Deryabin ◽  
Olga Vikentyeva ◽  
Lidiia Shestakova
Keyword(s):  
Physical System ◽  
Cyber Physical System ◽  
Monitoring And Control ◽  
Equipment Monitoring ◽  
And Control ◽  
Compressor Equipment

Social factory as a production node of social manufacturing

2019 ◽  
Vol 233 (14) ◽  
pp. 5144-5160 ◽  
Author(s):  
Chao Liu ◽  
Pingyu Jiang
Keyword(s):  
Physical System ◽  
Cyber Physical System ◽  
Production Network ◽  
Monitoring And Control ◽  
The Social ◽  
Core Concepts ◽  
Social Factory ◽  
Smart Workpiece ◽  
System Nodes ◽  
And Control

Social factory is served as the production node of social manufacturing communities/network to make manufacturing factories shift to the internet-based ones. The social factory aims to deal with fast-changing production requirements, sharing and competing of product orders, flexible resource configuration, ubiquitous interconnections, and real-time production monitoring and control. To achieve these visions, an extended cyber-physical system-enabled social factory model is proposed by integrating current cyber-physical system with machining equipment, social sensors, and smart workpieces. Within the proposed social factory model, the system framework and runtime logic are presented, and some core concepts such as extended cyber-physical system node, social sensor, and smart workpiece are clarified. Based on that, the social factory model is implemented by developing diverse extended cyber-physical system nodes and then connecting them with humans to form a collaborative production network where humans can access and control the machines anywhere and anytime. To validate the proposed social factory framework, a flexible production line in our lab is regarded as an extended cyber-physical system-enabled social factory to demonstrate the decentralized production interaction and cooperation.

scholarly journals VIRTUAL FARMER: CONTROLLING PHYTOCHROME SIGNALING IN PLANTS THROUGH CYBER-PHYSICAL SYSTEM

2017 ◽  
Vol 10 (13) ◽  
pp. 319
Author(s):  
Ankush Rai ◽  
Jagadeesh Kannan R
Keyword(s):  
Physical System ◽  
Research Work ◽  
External Environment ◽  
Transcriptional Regulators ◽  
Nutrient Cycle ◽  
Cyber Physical System ◽  
Cycle Plays ◽  
Genetic Sequences ◽  
And Control ◽  
External Stimuli

Under external environment stimuli seedlings undergo variation of morphology and alterations in its genetic sequences. Phytochrome signaling i.e., feedback reaction of plants to photons and other nutrient cycle plays a crucial role in its maturation. In this research work we create a cyber physical system to control such morphogenesis of plants through the help of artificial intelligence framework which identifies and control the crucial feedback between plant’s genetic transcription with respect to the external stimuli such as nutrients, electricity, magnetism. This leads to autonomously grow a plant without its disadvantageous traits by destabilizing its negatively acting transcriptional regulators and enhance the plant’s advantageous features by controlling its positively acting transcriptional regulators. This has leaded us to control the plant metabolism, plant growth without soil, manipulate the immunity of plant against disease, develop a plant metabolic profile and maximizes its yield deprived off from its seasonal attribute. 

A Cyber-Physical Photovoltaic Array Monitoring and Control System

2017 ◽  
Vol 5 (3) ◽  
pp. 33-56 ◽  
Author(s):  
Gowtham Muniraju ◽  
Sunil Rao ◽  
Sameeksha Katoch ◽  
Andreas Spanias ◽  
Cihan Tepedelenlioglu ◽  
...  
Keyword(s):  
Solar Panel ◽  
Cyber Physical System ◽  
Monitoring And Control ◽  
Monitoring And Control System ◽  
Renewable Energy Systems ◽  
Photovoltaic Array ◽  
Distributed Approach ◽  
Secure Authentication ◽  
And Control ◽  
Utility Scale

A cyber physical system approach for a utility-scale photovoltaic (PV) array monitoring and control is presented in this article. This system consists of sensors that capture voltage, current, temperature, and irradiance parameters for each solar panel which are then used to detect, predict and control the performance of the array. More specifically the article describes a customized machine-learning method for remote fault detection and a computer vision framework for cloud movement prediction. In addition, a consensus-based distributed approach is proposed for resource optimization, and a secure authentication protocol that can detect intrusions and cyber threats is presented. The proposed system leverages video analysis of skyline imagery that is used along with other measured parameters to reconfigure the solar panel connection topology and optimize power output. Additional benefits of this cyber physical approach are associated with the control of inverter transients. Preliminary results demonstrate improved efficiency and robustness in renewable energy systems using advanced cyber enabled sensory analysis and fusion devices and algorithms.

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