فهرست مطالب abdolhamid zahedi

In this paper, three different regimes including annular, stratified and homogeneous in the range of 5%-90% void fraction, were simulated by Mont Carlo N-Particle (MCNP) Codes. In simulated structure, a cesium 137 source and two Nal detectors were used to record received photons. In this study, the Fast Fourier Transform (FFT) was applied to the registered signals from two detectors in order to analyze in the frequency domain. Several features of signals in the frequency domain were extracted using average value of fast Fourier transform, the amplitude of dominant frequency, kurtosis, Standard Deviation (STD), RMS (Root Mean Square) and Variance. The same features were extracted from analyzed signals of both detectors in order to find the best separation patterns. These extracted features were used as inputs of artificial neural networks (ANNs) to increase the efficiency of two-phase flowmeters. Two multi-layer perceptrons (MLP) neural networks were implemented in MATLAB software in order to classify flow regimes (annular, stratified and homogeneous) and predict the void fraction. All of the training and testing data were obtained correctly and the mean relative error percentage of the predicted void fraction was 1/15 %.

Digital switches are one of the main components of the data transmission networks, and their modeling in applications such as traffic measurement, fault diagnosis, and operator training,have significant importance. In this paper, signaling of a digital switch is modeled and simulatedusing Colored Petri Nets. Colored PetriNet can support various data types and due to its intuitive graphical representationis known as an efficient tool for modeling of Discrete Event Systems (DES). In this papera digital switch is considered as a DES and its signaling is modeled using a CPN. Signalingis a sustainable and comprehensiveprotocol that can integrate various communication services into digital and analog telephone subscribers. The protocol cited in this paper,meets all the requirements for communication between digital databases and its role in the communications system is the same as one in computer networks. In this paper the signaling state is limited to a successful call between twosubscribers. In addition, the reachability graph is extracted for the CPN which contains all possible events in the DES and can be used for supervisory control tasks such as fault diagnosis process.

Modeling and diagnosis of signaling faults in digital telecommunication switches is very important. Providing practical approaches to this issue can be effective in increasing the speed and security of traffic information in the telecommunications network. In this paper, the signaling of the NEAX digital switch, which is a commonly used switch in the Iran telecommunication network, is simulated using the concept of Petri Nets (PNs), and then based on this model, a new algebraic method is proposed for detecting fault signaling. Unlike most of the methods presented in this field, the method proposed in this paper, without using of the reachability graph, uses algebraic approaches to detect the faults. The low complexity of computations, the needles of observablity of transitions, possibility of fault detection both in places and transitions of PN are the advantages of this method. Here, for more illustration, signaling in a successful single-call mode and busy mode is simulated and faults such as incomplete sending of destination phone numbers are detected.