Unlike fault diagnosis approaches based on the direct analysis of current and voltage signals, this paper proposes a diagnosis of induction motor faults through monitoring the variations in motor's parameters when it is subjected to an open circuit or short circuit faults. These parameters include stator and rotor resistances, self-inductances, and mutual inductance. The genetic algorithm and the trust-region method are used for the estimation process. Simulation results confirm the efficiency of both the genetic algorithm and the trust-region method in estimating the motor parameters; however, better performance in terms of estimation time is obtained when the trust-region method is adopted. The results also show the possibility of extracting fault signatures from the motor's parameter values because each type of the mentioned faults has a different impact on these parameters. Under a 10% short circuit fault condition, the mutual inductance and rotor resistance deviate by almost 10% from their original values to lower values. While the stator resistance noticeably reduces by up to 20% during the open circuit fault condition.
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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The grey system model GM(1,1) is the model of the prediction of the time series and the basis of the grey theory. This research presents the methods for estimating parameters of the grey model GM(1,1) is the accumulative method (ACC), the exponential method (EXP), modified exponential method (Mod EXP) and the Particle Swarm Optimization method (PSO). These methods were compared based on the Mean square error (MSE) and the Mean Absolute percentage error (MAPE) as a basis comparator and the simulation method was adopted for the best of the four methods, The best method was obtained and then applied to real data. This data represents the consumption rate of two types of oils a he
... Show MoreThe activation energy and optical band gap of different regions (p-type) polysilicon have been measured. Both microscopic studies and current-voltage characteristics of diodes prepared on different surface regions were carried out. Comparison of diodes parameters and microscopic studies indicate that the type of angles between boundaries has a significant effect on diodes parameters while the boundary lengths per unit area has less effect. The mechanism of Al-interaction with grain boundaries and their intersecting points at different temperature were also studies. The X-ray fluorescence spectrometry has been used for detection of diffused A1%.
In this work, we studied the effect of power variation on inductively coupled plasma parameters using numerical simulation. Different values were used for input power (750 W-1500 W), gas temperature 300K, gas pressure (0.02torr), 5 tourns of the copper coil and the plasma was produced at radio frequency (RF) 13.56 MHZ on the coil above the quartz chamber. For the previous purpose, a computer simulation in two dimensions axisymmetric, based on finite element method, was implemented for argon plasma. Based on the results we were able to obtain plasma with a higher density, which was represented by obtaining the plasma parameters (electron density, electric potential, total power, number density of argon ions, el
... Show MoreThe paper uses the Direct Synthesis (DS) method for tuning the Proportional Integral Derivative (PID) controller for controlling the DC servo motor. Two algorithms are presented for enhancing the performance of the suggested PID controller. These algorithms are Back-Propagation Neural Network and Particle Swarm Optimization (PSO). The performance and characteristics of DC servo motor are explained. The simulation results that obtained by using Matlab program show that the steady state error is eliminated with shorter adjusted time when using these algorithms with PID controller. A comparative between the two algorithms are described in this paper to show their effectiveness, which is found that the PSO algorithm gives be
... Show MoreThe effect of gamma radiation at the doses (0 , 5 , 10 or 15 ) Gray on the callus of four Triticum aestivum immature embryos genotypes (AL-Hashmiya , AL-Noor AL-Zahraa and AL-Mellad ) were studied . The fresh and dry weight for callus and shoot tips beside numbers and lengths of the shoots were used as indicators after 8 weeks . Results revealed that (AL-Noor and AL-Zahraa ) was superior by giving highest fresh and dry weight reached 274.2 and 269.2 mg and 26 and 24.3 mg respectively as compared with AL-Hashmiya and AL-Mellad. Moreover, the control treatment and the dose 10 Gray gave highest fresh weight reached 277.4 and 259.1 mg while the dry weight was highest in the control treatment and the dose 5 Gray. addition 10 Gra
... Show MoreWireless Body Area Sensor Network (WBASN) is gaining significant attention due to its applications in smart health offering cost-effective, efficient, ubiquitous, and unobtrusive telemedicine. WBASNs face challenges including interference, Quality of Service, transmit power, and resource constraints. Recognizing these challenges, this paper presents an energy and Quality of Service-aware routing algorithm. The proposed algorithm is based on each node's Collaboratively Evaluated Value (CEV) to select the most suitable cluster head (CH). The Collaborative Value (CV) is derived from three factors, the node's residual energy, the distance vector between nodes and personal device, and the sensor's density in each CH. The CEV algorithm operates i
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Experimental work from Magnetic Abrasive Finishing (MAF) tests was carried out design parameters (amplitude, and number of cycle which are formed the shape of electromagnetic pole), and technological parameters (current, cutting speed, working gap, and finishing time) all have an influence on the mechanical properties of the surface layer in MAF process. This research has made to study the effect of design and technological parameters on the surface roughness (Ra), micro hardness (Hv) and material removal (MR) in working zone. A set of experimental tests has been planned using response surface methodology according to Taguchi matrix (36) with three levels and six factors
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