INESC-ID

About: INESC-ID is a nonprofit organization based out in Lisbon, Portugal. It is known for research contribution in the topics: Computer science & Context (language use). The organization has 932 authors who have published 2618 publications receiving 37658 citations.

Induction motor broken bar fault detection based on MCSA, MSCSA and PCA: A comparative study

Abstract: The early failure detection of induction motors is considered very important in order to ensure their stability and high performance. Thus, condition monitoring of these motors are essential to ensure that. However, the effectiveness of the fault diagnosis depends on the quality of the fault features selection that is used in the adopted method. In this way, this paper will present a comparative study of three methods based on the electrical signal analysis. The first one is the most known method, motor current signature analysis (MCSA). Another method based on the analysis of spectral current, is the motor square current signature analysis (MSCSA), will also be used. Finally a third method based on principal component analysis (PCA) is also used. The performance of the methods is tested under different fault and load conditions. Experimental results are presented in order to compare the performance between the three methods.

Less errors with TTS? A dictation experiment with foreign language learners.

Abstract: This article reports a contrastive experiment about the use of Text-To-Speech (TTS) synthesis instead of prerecorded utterances in a dictation exercise submitted to students of European Portuguese as a second language (PSL). Forty sentences were extracted from a PSL student book. Twenty of them were synthesized and the other twenty were directly taken from the pre-recorded audio documents of the book. It appeared that the synthetic utterances were easier to transcribe than the prerecorded ones, with word error rates of 26.6% and 33.9% respectively. This result was somehow surprising since the synthetic voice was not built or tuned for learning purposes. Nevertheless, the lower speech rate of the TTS voice (15% slower) may explain this outcome. A manual error categorization showed that less word substitutions and less errors on function words were made on the TTS utterances.

Combing Smart Grid with community clouds: Next generation integrated service platform

Abstract: Collaboration-based distributed systems are becoming more prevalent these days. Two such systems are Community Clouds, where a large number of anonymous private users share their computational resources within the community, and smart grids, a distributed modernized electrical grid. Albeit with differences in ultimate goals, these two systems share many specifications and requirements such as decentralization, pay-as-you-go mechanism, reliability, scalability, availability and security. We argue that a model inspired by the two collaborative systems, with relevant common traits, is a good starting point to sketch the big picture of an economics-driven approach to make collaboration between them. We define a comprehensive economic model as key step towards managing and driving negotiation and resource arbitration, within and among both collaborative distributed systems. The main factors affecting such an economic model are QoS, cost effectiveness and energy efficiency, accounting for their interdependencies that strengthen and weaken each other in different cases. Towards such an economic model, we devise a cost model that controls the level of collaboration or resource sharing among vicinities, via community currency, which enables trading through converting local currencies and managing exchange taxes.

Cascaded H-bridge multilevel inverter with a fault detection scheme based on the statistic moments indexes

Abstract: Multilevel inverters allow to generate AC voltages with low total harmonic distortion (THD) but requires an increased number of power switches. One of the disadvantages of that is the increased probability of a fault in one of the power switches. Thus in order to improve the reliability of the converter a fast and robust fault detection scheme must be used. In this context this paper presents a new fault detection scheme based on the AC voltages of the inverter. The proposed scheme uses fault factors that are based on the statistic moment method. This method was used for the identification of image patterns. Due to this the proposed scheme allows for a robust detection to load or voltage variations. To test the method was used a cascaded H-bridge inverter with five levels. Several tests were performed through numerical results. The use of a laboratory prototype was also used to confirm the proposed scheme.