MODARES TECHNICAL AND ENGINEERING
Year:2008 | Volume:- | Issue:30 (SPECIAL ISSUE ON ELECTRICAL ENGINEERING)|Papers Count:16

High processing loads, need for complicated and frequent updating, and high false alarm are some of the challenges in designing anomaly detection and misuse detection systems. We propose a new network-based intrusion detection system (IDS) that resolves such shortcomings. Our scheme fuses anomaly detection and misuse detection systems, which has not been utilized so far in existing systems. In doing so, we have employed a mix of modified back -propagation (BP) and self-organizing map (SOM) neural networks that perform pattern recognition and classification in an effective and efficient manner. Results indicate that the performance of our proposed IDS is significantly improved as compared to the existing systems. 

In this paper, an interactive model for individual normal behaviour of drivers is presented in which the mutual effect of vehicles has been incorporated. Temporal features obtained from vehicles tracking and their motion history is utilized for generating a model of normal behaviour. Because of nonstationarity of behavior, Hidden Markov Model has been used for interactive model. This model has three main parts. The first part is the history of antecedent trajectory which for this purpose has proposed a Centers Transition Matrix (CTM) that is some type of spatia-temporal information-data bank from motions seen in the old frames. The second part is based on the linguistic features or motion recognition of vehicles, these motions contain forward, turn right and left, lane changing to right and left motion. The third part is constituted from low level features which contain Velocity and distance to neighbor object. Also CTM is efficient in search at similar blob in image sequences and it can determine the radius and region of search. This top-down feedback caused an increment of performance of RLS tracker and object searching. In the presented system, we obtained a 81.2% membership rate to normal model. Also types of motion are recognized using HMM with a recognition rate of up to 82.7%. Prediction error is reduced on many vehicles trajectory by at least 80% using a feedback system.

Sensor less speed torque control of induction machines has been widely used in many industrial applications. The-simple method of direct vector control can provide touchholes control as well as more complex approaches. In this method, the motor flux can be obtained by measuring voltage and current and integrating motor back electromotive force. The only required motor parameter is stator resistance. However, implementation of an integrator is not an easy task because a pure integrator has dc-offset problem. In addition, variations of stator resistance due to changes in temperature highly deteriorate the accuracy of this method at low speeds. In this paper, to overcome the dc-offset problem, a modified integrator is used, and a method for estimating stator resistance is proposed. This method represents accurate torque control over a wide range of speed and load conditions, even at zero rotor speed and heavy load torque.

One of the challenges in non-destructive testing schemes using the ultrasound pulse-echo technique is to identify those defects whose sizes are less than or equal to the detection resolution that is dependent on the width of the ultrasound pulse. Existing methods also require a reference specimen of the same defective material, which may not be available in some cases. We present a new method for detecting and identifying such defects. In the proposed approach, each layer of the test specimen is modeled as a linear time invariant (LTI) filter, and therefore, each defect are characterized by its corresponding impulse response. We use a combination of time gating and system identification techniques to detect and identify the defects, and as such, do not require a reference specimen. To demonstrate the performance of the proposed approach, we tested metallic blocks in which specific defects were impregnated. Results show that the proposed method can detect such defects, does not depend on the test set-up (including the ultrasound transducer), does not require a reference specimen, and is capable of detecting several defects situated in different depth on top of each other.

Different methods for detecting broken bars in induction motors can be found in literature. Many of these methods are based on evaluating special frequency magnitudes in machine signals spectrums. Current, power, flux, etc are among these signals. Frequencies related to broken rotor fault depend on slip. In industrial environment due to some phenomena - such as load oscillation, other faults and disturbances - obtrusive frequency components appear in the vicinity of fault components; therefore, correct diagnosis of fault depends on accurate determination of motor velocity and slip. The traditional methods typically require several sensors that should be pre-installed in some cases. This paper presents a diagnosing method based on vibration spectrum. Motor velocity oscillation due to broken rotor causes frequency components at twice slip frequency (2st) difference around speed frequency in vibration spectrum. Speed frequency and its harmonics as well as twice supply frequency, can easily and accurately be found in vibration spectrum, therefore the motor slip can be computed. Now components related to rotor fault can be found. Evaluation of these fault components magnitudes can be a good measure for fault diagnosis.

Presence of Distributed Generation (DG) in electric distribution systems provides an attractive new alternative in capacity expansion planning of these systems. In this paper a new model is developed for solving simultaneous placement of HV/MV substations and DG units as a static planning tool. This model aims to minimize fixed and variable costs of planning. Constraints related to DGs, substation and network are incorporated in the developed model. Proposed model can be used for optimal sizing, sitting and defining associated service area of HV/MV substations and DGs in distribution capacity expansion. The proposed model is a mixed-integer nonlinear mathematical model which optimized using genetic algorithm. The effectiveness of proposed model is illustrated through numerical examples.

This paper presents a new arc starter circuit that is usable in Manual Metal Arc welding (MMA) power supplies. The proposed circuit uses an auxiliary circuit and a series coupling transformer for adding high frequency spikes to output DC voltage during arc striking. The proposed circuit is usable in inverter based arc welding supplies and it could result in a decrease of weigh, volume and expense of the high frequency transformer. In addition, a cycle -by- cycle arc welding current control strategy is proposed that is useful in reduction of spatters and increasing of welding quality. The effectiveness of proposed circuit and control strategy is verified using simulation and experimental results. 

Arbitrage is a known economic term, implying simultaneous transaction on commodities. For instance, a Generation Company (GenCo) may involve itself in selling fuel, emission allowance and etc., instead of generating either active or reactive power. Moreover, arbitrage between active and reactive powers can, in turn, be considered.In this paper, arbitrage between active and reactive power is considered from Independent System Operator (ISO) viewpoint. A pool model is employed. ISO runs an optimization problem, by which, it could determine and predict GenCos behaviours; in terms of participating in active and reactive power markets for the next twelve months. A normal distribution function is used for price forecasting. Two 3-bus and 14-bus test systems are used to demonstrate the capabilities of the proposed algorithm.

In some mobile systems, intelligent antennas are used to increase efficiency in a wide frequency band and different environmental and electromagnetic conditions. Environmental factors, such as position of nearby objects, antenna mobility and even user type, can vary the antenna input impedance appreciably. Therefore, it is necessary to incorporate an adaptive impedance matching circuit between the antenna array elements and the transceiver to maximize the antenna radiation power; In this research note, the design of adaptive matching circuit for intelligent quadrifilar helical antenna in the UHF band (for GSM) is presented. The GA algorithm is used to optimize the results. The designed circuit can decrease the VSWR from 20 to less than 2 at any frequency within the GSM bandwidth.

This paper investigates the islands formation in initial stages of restoration process in blackout condition and studies the impacts of islands number variation on the process execution. In addition, a method is proposed to determining each island optimal boundaries. Then the effects of transmission lines Thyistor Controlled Series Compensators (TCSC) to facilitate restoration process and improvement of optimal solutions are studied. Energy Not supplied (ENS) index minimization is the objective function and the optimization method is Genetic Algorithm. The test network modeling has been done using a special appropriate chromosome coding. Various operational constraints such as voltage margins in buses, transmission lines capacities and generators loading limits have been considered in optimization process and final solution evaluation. The IEEE-I 18 bus network has been used as test system to assess the capabilities of the proposed method. Some obtained results have been given in the case study section.