ESP "Smart Flow" Integrates Quality and Control Data for Diagnostics and Optimization in Real Time (Part of KwIDF Project)

2013 ◽  
Author(s):  
A Al-Jasmi ◽  
H. Nasr ◽  
H. K. Goel ◽  
G. Moricca ◽  
G. A. Carvajal ◽  
...  
Keyword(s):  
Real Time ◽  
Control Data ◽  
Time Part ◽  
And Control

ESP "Smart Flow" Integrates Quality and Control Data for Diagnostics and Optimization in Real Time

2013 ◽  
Author(s):  
Guillermo Velasquez ◽  
Jeff Kain ◽  
Miguel Villamizar ◽  
Zhou Yong ◽  
Joydeep Dhar ◽  
...  
Keyword(s):  
Real Time ◽  
Control Data ◽  
And Control

scholarly journals Design and Implementation of Real-time Power Grid WebGIS Visualization Framework Based on New Generation Dispatching and Control System

2021 ◽  
Vol 2087 (1) ◽  
pp. 012073
Author(s):  
Yuan He ◽  
Yuan Zhang ◽  
Yaowei Zhang ◽  
Caishen Fang ◽  
Kun Huang ◽  
...  
Keyword(s):  
Control System ◽  
Real Time ◽  
Power Grid ◽  
Secondary Development ◽  
Control Data ◽  
Cartographic Generalization ◽  
Data Platform ◽  
Platform System ◽  
New Generation ◽  
And Control

Abstract With the strengthening of the integrated characteristics of power grid and the construction of the New Generation Dispatching and Control System with “physical distribution, logical integration”, the demand for global monitoring and analysis of power grid has gradually increased. On the basis of understanding of design of the new generation real-time dispatching and control data platform system, with the principles of componentization and servitization, the real-time power grid WebGIS visualization framework is designed and implemented. And this paper further introduces the design of the front-end secondary development interface and examples, as well as the cartographic generalization of the power grid WebGIS visual map. This framework has successfully supported the construction and online operation of several real-time power grid WebGIS visualization applications.

Gas Lift Smart Flow Integrates Quality and Control Data for Diagnostic and Optimization in Real Time

2013 ◽  
Author(s):  
Jose Antonio Rodriguez ◽  
Miguel Villamizar ◽  
Gustavo A Carvajal ◽  
Carlos Lopez ◽  
Maiquel Querales ◽  
...  
Keyword(s):  
Real Time ◽  
Control Data ◽  
And Control ◽  
Gas Lift

Microstructural investigation of surface roughness in MBE-grown AlAs

1995 ◽  
Vol 53 ◽  
pp. 454-455
Author(s):  
R. Rajesh ◽  
R. Droopad ◽  
C. H. Kuo ◽  
R. W. Carpenter ◽  
G. N. Maracas
Keyword(s):  
Thin Film ◽  
Real Time ◽  
Growth Control ◽  
Native Oxide ◽  
Effusion Cell ◽  
Surface Oxide Layer ◽  
Microstructural Investigation ◽  
Mbe Growth ◽  
Film Substrate ◽  
And Control

Knowledge of material pseudodielectric functions at MBE growth temperatures is essential for achieving in-situ, real time growth control. This allows us to accurately monitor and control thicknesses of the layers during growth. Undesired effusion cell temperature fluctuations during growth can thus be compensated for in real-time by spectroscopic ellipsometry. The accuracy in determining pseudodielectric functions is increased if one does not require applying a structure model to correct for the presence of an unknown surface layer such as a native oxide. Performing these measurements in an MBE reactor on as-grown material gives us this advantage. Thus, a simple three phase model (vacuum/thin film/substrate) can be used to obtain thin film data without uncertainties arising from a surface oxide layer of unknown composition and temperature dependence.In this study, we obtain the pseudodielectric functions of MBE-grown AlAs from growth temperature (650°C) to room temperature (30°C). The profile of the wavelength-dependent function from the ellipsometry data indicated a rough surface after growth of 0.5 μm of AlAs at a substrate temperature of 600°C, which is typical for MBE-growth of GaAs.

Adaptive Signal Analysis and Interpretation for Real-time Intelligent Patient Monitoring

1994 ◽  
Vol 33 (01) ◽  
pp. 60-63 ◽  
Author(s):  
E. J. Manders ◽  
D. P. Lindstrom ◽  
B. M. Dawant
Keyword(s):  
Computer Architecture ◽  
Real Time ◽  
Data Abstraction ◽  
Monitoring Strategy ◽  
Intelligent Monitoring ◽  
Patient Status ◽  
On Line ◽  
Main Components ◽  
And Control ◽  
Adaptive Signal

Abstract:On-line intelligent monitoring, diagnosis, and control of dynamic systems such as patients in intensive care units necessitates the context-dependent acquisition, processing, analysis, and interpretation of large amounts of possibly noisy and incomplete data. The dynamic nature of the process also requires a continuous evaluation and adaptation of the monitoring strategy to respond to changes both in the monitored patient and in the monitoring equipment. Moreover, real-time constraints may imply data losses, the importance of which has to be minimized. This paper presents a computer architecture designed to accomplish these tasks. Its main components are a model and a data abstraction module. The model provides the system with a monitoring context related to the patient status. The data abstraction module relies on that information to adapt the monitoring strategy and provide the model with the necessary information. This paper focuses on the data abstraction module and its interaction with the model.

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