Study on herbicide residues in soybean processing based on UPLC-MS/MS detection
(3)
(4)
Publication Date
Thu Dec 30 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
(58)
(12)
Publication Date
Tue Oct 01 2024
Journal Name
Analytical And Bioanalytical Electrochemistry
(4)
Publication Date
Wed May 01 2024
Journal Name
Journal Of Drug Delivery Science And Technology
(21)
(12)
Publication Date
Sun Dec 01 2024
Journal Name
Russian Journal Of General Chemistry
(2)
(2)
Publication Date
Mon Nov 18 2024
Journal Name
Molecular Crystals And Liquid Crystals
(2)
(2)
Publication Date
Sun Dec 01 2024
Journal Name
Russian Journal Of General Chemistry
(2)
(2)
Publication Date
Sun Dec 01 2024
Journal Name
Russian Journal Of General Chemistry
(2)
(2)
Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of a Programmable System for Failure Modes and Effect Analysis of Steam-Power Plant Based on the Fault Tree Analysis
Keywords: Fault Tree
Reliability
Maintainability
Industrial Systems
Failure Mode and Effect Analysis
Diagnostic Expert System
Steam Power Plant
In this paper, the system of the power plant has been investigated as a special type of industrial systems, which has a significant role in improving societies since the electrical energy has entered all kinds of industries, and it is considered as the artery of modern life.
The aim of this research is to construct a programming system, which could be used to identify the most important failure modes that are occur in a steam type of power plants. Also the effects and reasons of each failure mode could be analyzed through the usage of this programming system reaching to the basic events (main reasons) that causing each failure mode. The construction of this system for FMEA is dependi
... Show MorePublication Date
Sun Jun 30 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
(4)
(2)
Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of Nonlinear PID Neural Controller for the Speed Control of a Permanent Magnet DC Motor Model based on Optimization Algorithm
Nonlinear PID Controller
DC Motor
Particle Swarm Optimization
Neural Networks
MATLAB
LabVIEW
In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe
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