OntoSPIT: SPIT management through ontologies

VoIP enables new ways for communication. At the same time, it provides new means, in terms of transmitting bulk unsolicited messages and calls, namely SPam over Internet telephony (SPIT). In this paper, we propose a conceptual model, based on an underlying ontology, which describes the SPIT domain. The ontology provides capabilities, such as modeling the SPIT phenomenon in a SIP-based VoIP environment, a common understanding of SPIT domain, as well as reusable SPIT-related knowledge interoperability, aggregation and reasoning. We demonstrate that the proposed ontology, combined with a set of SPIT identification criteria, as its underlying axioms and rules, could enhance the correlation and management of SPIT incidents. It could also support SPIT detection, thus facilitating the better protection of VoIP environments in a holistic, cooperative, and effective way.     

Integration properties of disaggregated solar,geothermal and biomass energy consumption in the U.S.

This paper investigates the integration properties of disaggregated solar, geothermal and biomass energy consumption in the U.S. The analysis is performed for the 1989–2009 period and covers all sectors which use these types of energy, i.e., transportation, residence, industrial, electric power and commercial. The results suggest that there are differences in the order of integration depending on both the type of energy and the sector involved. Moreover, the inclusion of structural breaks traced from the regulatory changes for these energy types seem to affect the order of integration for each series.     

Principal Component Analysis of the start-up transient and Hidden Markov Modeling for broken rotor bar fault diagnosis in asynchronous machines

This article presents a novel computational method for the diagnosis of broken rotor bars in three phase asynchronous machines. The proposed method is based on Principal Component Analysis (PCA) and is applied to the stator’s three phase start-up current. The fault detection is easier in the start-up transient because of the increased current in the rotor circuit, which amplifies the effects of the fault in the stator’s current independently of the motor’s load. In the proposed fault detection methodology, PCA is initially utilized to extract a characteristic component, which reflects the rotor asymmetry caused by the broken bars. This component can be subsequently processed using Hidden Markov Models (HMMs). Two schemes, a multiclass and a one-class approach are proposed. The efficiency of the novel proposed schemes is evaluated by multiple experimental test cases. The results obtained indicate that the suggested approaches based on the combination of PCA and HMMs, can be successfully utilized not only for identifying the presence of a broken bar but also for estimating the severity (number of broken bars) of the fault.     

Asynchronous Machine Rotor Fault Diagnosis Technique Using Complex Wavelets

This paper introduces a novel approach for the detection of rotor faults in asynchronous machines, based on wavelet analysis of the stator phase current. To be more specific, the measured stator phase current is filtered through a complex wavelet. Theoretical analysis validates that the spectrum of the modulus of the result of the filtering is free from the fundamental supply frequency component, and the fault characteristics can be highlighted. This is advantageous, especially if the induction machine operates at low slip values, where the characteristic frequency components of the rotor fault are very close to the fundamental frequency component. At the same time, by matching the wavelet function to the frequencies of the faulty components, a narrow bandpass filter at the frequency region of the fault characteristic spectral components is obtained. Furthermore, in the context of this paper, features extracted using the proposed technique are used as input to a support vector machine classifier that is employed for the detection of the rotor fault. Simulation and experimental results demonstrate the effectiveness of the proposed technique.