scholarly journals Artificial intelligence based operational strategy development and implementation for vibration reduction of a supercritical steam turbine shaft bearing

Author(s):  
Waqar Muhammad Ashraf ◽  
Yasir Rafique ◽  
Ghulam Moeen Uddin ◽  
Fahid Riaz ◽  
Muhammad Asim ◽  
...  
2022 ◽  
Vol 12 (1) ◽  
pp. 65
Author(s):  
Yasir Rafique ◽  
Abid Hussain

The energy efficiency of a power plant is largely determined by the vibrations of bearings that hold the shaft rotating at high speed which need to be critically controlled. This study presents the relative vibration modeling of a shaft bearing that is installed in a 660 MW supercritical steam turbine system. The operational data in raw form after being cleaned using machine learning based visualization and extensive data processing helped in training and validation of SVM and ANN models which are then compared by external validation tests. The model with best results is then used for the simulations of constructed operating scenarios. The ANN has been further tested for the complete operational load range (353 MW to 662 MW) which predicted the reduction in relative vibrations. Moreover, the validated ANN model has been used to develop many strategies of vibration reduction which helped in achieving more than 4% reduction in relative vibrations. Subsequently, an operational strategy that predicts a significant reduction in the bearing vibration levels is selected. For confirmation of the accuracy of prediction by ANN process model, the selected strategy has been used with the actual power plant. This assures the significant reduction of bearing vibration less than the alarm limit.


Author(s):  
Theunis Gert Pelser ◽  
Garth Gaffley

What the internet with its connectivity did to facilitate the third industrial revolution, cloud computing and artificial intelligence have done for the fourth industrial revolution. Technology is changing the world at an alarming rate, which includes products and services that require scale to manage the growing demands of an ever-changing and increasing population. Digital transformation is enabled through cloud technology where human comprehension cannot cope with the size and speed of data required to manage a business in the digital economy. Artificial intelligence and machine learning assist in activities to overcome human limitation, using algorithms to develop predictive and simulation models and scale to provide data for decision making. The technologies employed to run and execute these require skill and resource. The challenge for the modern-day CEO is that the use of technology and its demand in the digital economy of the Fourth Industrial Revolution is not fully understood by them due to their digital skill level and managing the generational skill sets in their structure.


Author(s):  
M Rund ◽  
R Procházka ◽  
J Džugan ◽  
P Konopík ◽  
M Nesládek ◽  
...  

2020 ◽  
Vol 36 (8) ◽  
pp. 17-19

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings Artificial Intelligence (AI) is enabling companies to perform many functional tasks more efficiently. Some organizations are starting to further utilize its capabilities by combining the rationality of AI with human creativity in order to optimize development of marketing strategies. Originality/value The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.


2020 ◽  
Vol 10 (5) ◽  
pp. 1712 ◽  
Author(s):  
Hsiu-Ying Hwang ◽  
Tian-Syung Lan ◽  
Jia-Shiun Chen

In order to achieve better performance of fuel consumption in hybrid vehicles, the internal combustion engine is controlled to operate under a better efficient zone and often turned off and on during driving. However, while starting or shifting the driving mode, the instantaneous large torque from the engine or electric motor may occur, which can easily lead to a high vibration of the elastomer on the driveline. This results in decreased comfort. A two-mode power-split hybrid system model with elastomers was established with MATLAB/Simulink. Vibration reduction control strategies, Pause Cancelation strategy (PC), and PID control were developed in this research. When the system detected a large instantaneous torque output on the internal combustion engine or driveline, the electric motor provided corresponding torque to adjust the torque transmitted to the shaft mitigating the vibration. To the research results, in the two-mode power-split hybrid system, PC was able to mitigate the vibration of the engine damper by about 60%. However, the mitigation effect of PID and PC-PID was better than PC, and the vibration was able to converge faster when the instantaneous large torque input was made. In the frequency response, the effect of the PID blocking vibration source came from the elastomer was about 75%, while PC-PID additionally reduced 8% by combining the characteristics of the two control methods.


2010 ◽  
Vol 3 (3) ◽  
pp. 11-18
Author(s):  
Anne Wilms ◽  
Stephen J. Andriole

This paper focuses on the development of a business technology strategy for a large global specialty chemicals company. The requirement was to develop a strategy that aligned with the company’s business strategy, which is not an uncommon requirement for business technology strategies in the 21st century. The expectation was that information technology (IT) would cross the operation-to-strategic chasm and start to generate some significant ROI. The paper explores the elements of the “strategic strategy” (versus an “operational strategy”) as well as ongoing challenges to make both operational and strategic technology work. The authors illustrate a number of strategy development principles that students should internalize as they assess other cases and develop their own business technology strategies.


2017 ◽  
Vol 7 ◽  
pp. 190-197 ◽  
Author(s):  
M. Nesládek ◽  
J. Jurenka ◽  
M. Lutovinov ◽  
M. Růžička ◽  
P. Měšťánek ◽  
...  

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