This paper presents a complete design and implementation of a monitoring system for the operation of the three-phase induction motors. This system is built using a personal computer and two types of sensors (current, vibration) to detect some of the mechanical faults that may occur in the motor. The study and examination of several types of faults including (ball bearing and shaft misalignment faults) have been done through the extraction of fault data by using fast Fourier transform (FFT) technique. Results showed that the motor current signature analysis (MCSA) technique, and measurement of vibration technique have high possibility in the detection and diagnosis of most mechanical faults with high accuracy. Subsequently, diagnosis system is developed to determine the status of the motor without the need for an expert. This system is based on artificial neural network (ANN) and it is characterized by speed and accuracy and the ability to detect more than one fault at the same time.
The core objective of this paper was to diagnosis and detect the expected rotor faults in small wind turbine SWT utilize signal processing technique. This aim was achieved by acquired and analyzed the current signal of SWT motor and employed the motor current signature analysis MCSA to detect the sudden changes can have occurred during SWT operation. LabVIEW program as a virtual instrument and (NI USB 6259) DAQ were take advantage of current measurement and data processing.
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 po
... Show MoreThe main aim of this research to study and recognize the specifications and main concepts of (Fuzzy Logic) and its components and studying the practical experiments of the (Fuzzy Logic) techniques in the electrical engineering field through by using the (Fuzzy Logic) for controlling the three-phase AC induction motor by using (Matlab_ simulation_7) for modeling the system by using the computer
Micro wind turbines are generally used in remote locations, and it is difficult and expensive to repair faults which forced the need for condition monitoring and fault diagnosis which has not been used extensively for small turbines. The possibility of utilizing Fast Fourier Transform (FFT) for diagnosis the faults of broken rotor bar in squirrel cage induction motor of a micro wind turbine was investigated. Monitoring and analysis the current spectrum can be effective for diagnosis the early stage of faults and avoid complete catastrophic failure in the motor by powerful virtual instruments and LabVIEW software as an integral part of this instrumentation. Combination advanced signal processing technique with computerized signal processi
... Show MoreThe present study aimed to try to find natural substances stimulate the production of bacteriocin, as well as "for detection of bacteriocin producing isolates. Two hundred and eighty ( 280) bacterial isolates, gram negative only, were collected from 760 different pathogenic samples, consist: (Urinary tract infection, septicemia, Vaginal inflammation and diarrhea). The isolated bacteria are: Escherichia coli, Klebsiella pneumonia Pseudomonas aeruginosa,, Salmonella typhi, Enterobacter cloacae, Acinetobacter baumannii, Serratia liquefaciens, Citrobacter freundii, Proteus mirabilis and Serrattia odorifera. Cup assay method was used to detect bacteriocin production. Loc
... Show More<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
... Show MoreIn this paper, an adaptive integral Sliding Mode Control (SMC) is employed to control the speed of Three-Phase Induction Motor. The strategy used is the field oriented control as ac drive system. The SMC is used to estimate the frequency that required to generates three phase voltage of Space Vector Pulse Width Modulation (SVPWM) invertor . When the SMC is used with current controller, the quadratic component of stator current is estimated by the controller. Instead of using current controller, this paper proposed estimating the frequency of stator voltage since that the slip speed is function of the quadratic current . The simulation results of using the SMC showed that a good dynamic response can be obtained under load
... Show MoreDirect field-orientation Control (DFOC) of induction motor drives without mechanical speed sensors at the motor shaft has the attractions of low cost and high reliability. To replace the sensor, information on the rotor speed and position are extracted from measured stator currents and from voltages at motor terminals. In this paper presents direct field-orientation control (DFOC) with two type of kalman filter (complete order and reduced order extended kalman filter) to estimate flux, speed, torque and position. Simulated results show how good performance for reduced order extended kalman filter over that of complete order extended kalman filter in tracking performance and reduced time of state estimation.