Gas path fault diagnosis framework for a three-shaft gas turbine

2003 ◽  
Vol 217 (2) ◽  
pp. 149-157 ◽  
Author(s):  
S. O T. Ogaji ◽  
R Singh
Keyword(s):  
Neural Networks ◽  
Gas Turbine ◽  
Large Scale ◽  
Sensor Faults ◽  
Large Scale Integration ◽  
Multiple Sensor ◽  
Multiple Component ◽  
Gas Path Fault ◽  
Diagnostic Framework ◽  
Scale Integration

A diagnostic framework has been developed for the detection of faults in the gas path of a three-shaft aeroderivative gas turbine thermodynamically similar to the Rolls Royce RB211-24GT. The framework involves a large-scale integration of artificial neural networks (ANNs) designed and trained to detect, isolate and assess faults in the gas path components of the engine. The approach has the capacity to assess both multiple-component and multiple-sensor faults. The results obtained demonstrate the promise of ANNs applied to engine diagnostic activities.

scholarly journals Global Detection of Live Virtual Machine Migration Based on Cellular Neural Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Kang Xie ◽  
Yixian Yang ◽  
Ling Zhang ◽  
Maohua Jing ◽  
Yang Xin ◽  
...  
Keyword(s):  
Neural Networks ◽  
Virtual Machine ◽  
Large Scale ◽  
Detection Algorithm ◽  
Cellular Neural Networks ◽  
Virtual Machine Migration ◽  
Vm Migration ◽  
Large Scale Integration ◽  
Scale Integration ◽  
Virtual Resources

In order to meet the demands of operation monitoring of large scale, autoscaling, and heterogeneous virtual resources in the existing cloud computing, a new method of live virtual machine (VM) migration detection algorithm based on the cellular neural networks (CNNs), is presented. Through analyzing the detection process, the parameter relationship of CNN is mapped as an optimization problem, in which improved particle swarm optimization algorithm based on bubble sort is used to solve the problem. Experimental results demonstrate that the proposed method can display the VM migration processing intuitively. Compared with the best fit heuristic algorithm, this approach reduces the processing time, and emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI) implementation allowing the VM migration detection to be performed better.

Plant hormones, plant growth regulators

2014 ◽  
Vol 155 (26) ◽  
pp. 1011-1018 ◽  
Author(s):  
György Végvári ◽  
Edina Vidéki
Keyword(s):  
Nervous System ◽  
Growth And Development ◽  
Large Scale ◽  
Essential Role ◽  
Higher Plants ◽  
Structure And Function ◽  
Wide Sense ◽  
Large Scale Integration ◽  
Scale Integration ◽  
And Function

Plants seem to be rather defenceless, they are unable to do motion, have no nervous system or immune system unlike animals. Besides this, plants do have hormones, though these substances are produced not in glands. In view of their complexity they lagged behind animals, however, plant organisms show large scale integration in their structure and function. In higher plants, such as in animals, the intercellular communication is fulfilled through chemical messengers. These specific compounds in plants are called phytohormones, or in a wide sense, bioregulators. Even a small quantity of these endogenous organic compounds are able to regulate the operation, growth and development of higher plants, and keep the connection between cells, tissues and synergy beween organs. Since they do not have nervous and immume systems, phytohormones play essential role in plants’ life. Orv. Hetil., 2014, 155(26), 1011–1018.

Behavior Models of Voltage Differencing Inverting Buffered Amplifier and Applications in Circuit Analysis

2019 ◽  
Vol 12 (4) ◽  
pp. 298-303
Author(s):  
YongAn LI
Keyword(s):  
Large Scale ◽  
Vlsi Design ◽  
Circuit Analysis ◽  
Second Order ◽  
Very Large Scale Integration ◽  
Behavioral Models ◽  
Order Filter ◽  
Large Scale Integration ◽  
Scale Integration ◽  
Behavior Models

Background: The symbolic nodal analysis acts as a pivotal part of the very large scale integration (VLSI) design. Methods: In this work, based on the terminal relations for the pathological elements and the voltage differencing inverting buffered amplifier (VDIBA), twelve alternative pathological models for the VDIBA are presented. Moreover, the proposed models are applied to the VDIBA-based second-order filter and oscillator so as to simplify the circuit analysis. Results: The result shows that the behavioral models for the VDIBA are systematic, effective and powerful in the symbolic nodal circuit analysis.</P>

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