This research is devoted to design and implement a Supervisory Control and Data Acquisition system (SCADA) for monitoring and controlling the corrosion of a carbon steel pipe buried in soil. A smart technique equipped with a microcontroller, a collection of sensors and a communication system was applied to monitor and control the operation of an ICCP process for a carbon steel pipe. The integration of the built hardware, LabVIEW graphical programming and PC interface produces an effective SCADA system for two types of control namely: a Proportional Integral Derivative (PID) that supports a closed loop, and a traditional open loop control. Through this work, under environmental temperature of 30°C, an evaluation and comparison were done for two types of controls tested at low soil moisture (48%) and high soil moisture (80 %) to study the value of current, anode voltage, pipe to soil potential (PSP) and consumed power. The results show an decrease of 59.1% in consumed power when the moisture changes from the low to high level. It was reached that the closed loop controller PID is the best solution in terms of efficiency, reliability, fast response and power consumption.
The aim of this research is to study the effect of welded joint design (Butt joint and lap joint) on thejoint strength during tension and fatigue loading with different current of welding (40,50,60,70,80) ^per, and different type of wire welding. The result of this research is showed that the effect of fatigue loading on the type of joint is more than the effect of tension loading on it. And the butt joint welding is better than the lap joint welding during the fatigue loaded.The experimental results of the effect of W'elding current showed that more increasing and more decreasing the value of the heat input, during the welding was found to produce mechanical brittleness on the buttjoint welding during the static and dynamic loading. Also i
... Show MoreLawful protection of the human gene conceded a moral concern regarding the future of existence human. After the discovery of the human genetic map, scientific experiments and research related to the human gene increased, negative applications of genetic engineering in particular that violate essential human rights, the right to human dignity to be specific. These practices represent actual challenges to the existence and diversity of current and future generations. Therefore, the presence of legal rules at the domestic and global levels is an absolute necessity to prohibit these threats and determine civil and criminal accountability for those who infringe any laws related to this issue.
There are many methods of forecasting, and these methods take data only, analyze it, make a prediction by analyzing, neglect the prior information side and do not considering the fluctuations that occur overtime. The best way to forecast oil prices that takes the fluctuations that occur overtime and is updated by entering prior information is the Bayesian structural time series (BSTS) method. Oil prices fluctuations have an important role in economic so predictions of future oil prices that are crucial for many countries whose economies depend mainly on oil, such as Iraq. Oil prices directly affect the health of the economy. Thus, it is necessary to forecast future oil price with models adapted for emerging events. In this article, we st
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The regressor-based adaptive control is useful for controlling robotic systems with uncertain parameters but with known structure of robot dynamics. Unmodeled dynamics could lead to instability problems unless modification of control law is used. In addition, exact calculation of regressor for robots with more than 6 degrees of freedom is hard to be calculated, and the task could be more complex for robots. Whereas the adaptive approximation control is a powerful tool for controlling robotic systems with unmodeled dynamics. The local (partitioned) approximation-based adaptive control includes representation of the uncertain matrices and vectors in the robot model as finite combinations of basis functions. Update laws for the weighting matri
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Abstract
One of the major components in an automobile engine is the throttle valve part. It is used to keep up with emissions and fuel efficiency low. Design a control system to the throttle valve is newly common requirement trend in automotive technology. The non-smoothness nonlinearity in throttle valve model are due to the friction model and the nonlinear spring, the uncertainty in system parameters and non-satisfying the matching condition are the main obstacles when designing a throttle plate controller.
In this work, the theory of the Integral Sliding Mode Control (ISMC) is utilized to design a robust controller for the Electronic Throttle Valve (ETV) system. From the first in
... Show MoreThe earth's surface comprises different kinds of land cover, water resources, and soil, which create environmental factors for varied animals, plants, and humans. Knowing the significant effects of land cover is crucial for long-term development, climate change modeling, and preserving ecosystems. In this research, the Google Earth Engine platform and freely available Landsat imagery were used to investigate the impact of the expansion and degradation in urbanized areas, watersheds, and vegetative cover on the land surface temperature in Baghdad from 2004 to 2021. Land cover indices such as the Normalized Difference Vegetation Index, Normalized Difference Water Index, and Normalized Difference Built-up Index (NDVI, NDWI, an
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<span lang="EN-US">This paper presents the comparison between optimized unscented Kalman filter (UKF) and optimized extended Kalman filter (EKF) for sensorless direct field orientation control induction motor (DFOCIM) drive. The high performance of UKF and EKF depends on the accurate selection of state and noise covariance matrices. For this goal, multi objective function genetic algorithm is used to find the optimal values of state and noise covariance matrices. The main objectives of genetic algorithm to be minimized are the mean square errors (MSE) between actual and estimation of speed, current, and flux. Simulation results show the optimal state and noise covariance matrices can improve the estimation of speed, current, t
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