On-line diagnostics of transformer winding insulation failures, by Park`s vector approach

This paper presents a non-invasive approach for diagnosing winding insulation failures in three-phase transformers, which is based on the on-line monitoring of the primary and secondary current Park's Vector. Experimental and simulated results demonstrate the effectiveness of the proposed technique, for detecting winding inter-turn insulation faults in operating three-phase transformers.

Comparison of on-line learning algorithms for RBF models in greenhouse environmental control problems

The problem with the adequacy of radial basis function neural networks to model the inside air temperature as a function of the outside air temperature and solar radiation, and the inside relative humidity in an hydroponic greenhouse is addressed.

On-line adaptation of neural network

The Proportional Integral and Devirative (PID) controller autotuning is an important problem, both in practical and theoretical terms. The autotuning procedure must take place in real-time, and therefore the corresponding optimisation procedure must also be executed in real-time and without disturbing on-line control.

On-line operation of an intelligent seismic detector

This study describes the on-line operation of a seismic detection system to act at the level of a seismic station providing similar role to that of a STA /LTA ratio-based detection algorithms. The intelligent detector is a Support Vector Machine (SVM), trained with data consisting of 2903 patterns extracted from records of the PVAQ station, one of the seismographic network's stations of the Institute of Meteorology of Portugal (IM). Records' spectral variations in time and characteristics were reflected in the SVM input patterns, as a set of values of power spectral density at selected frequencies. To ensure that all patterns of the sample data were within the range of variation of the training set, we used an algorithm to separate the universe of data by hyper-convex polyhedrons, determining in this manner a set of patterns that have a mandatory part of the training set. Additionally, an active learning strategy was conducted, by iteratively incorporating poorly classified cases in the training set. After having been trained, the proposed system was experimented in continuous operation for unseen (out of sample) data, and the SVM detector obtained 97.7% and 98.7% of sensitivity and selectivity, respectively. The same type of ANN presented 88.4 % and 99.4% of sensitivity and selectivity when applied to data of a different seismic station of IM. © 2013 Springer-Verlag Berlin Heidelberg.

Transformers on-load exciting current Park`s vector approach as a tool for winding faults diagnostics

This paper presents the development of a new approach for diagnosing the occurrence of inter-turn short-circuits in the windings of three-phase transformers, which is based on the on-line monitoring of the on-load exciting current Park's Vector patterns. Experimental and simulated results demonstrate the effectiveness of the proposed technique for detecting winding inter-turn insulation faults in operating three-phase transformers.

Detection of trasformer intermittent winding faults by the on-load exciting current Park`s vector approach

This paper presents the application of the on-load exciting current Park's Vector Approach for diagnosing permanent and intermittent turn-to-turn winding faults in operating power transformers. First, an experimental investigation of the behaviour of the transformer under the occurrence of both permanent and intermittent winding faults is presented. Finally, experimental test results demonstrate the effectiveness of the proposed diagnostic technique, which is based on the on-line monitoring of the on-load exciting current Park's Vector patterns.

Radio over fiber broadband access networks architectures based on wavelength division multiplexing techniques

The recent remarkable growth in bandwidth of both wired optical and wireless access networks supports a burst of new high bandwidth Internet applications such as: peer-topeer file sharing, cloud storage, on-line gaming, video streaming, etc. Within this scenario, the convergence of fixed and wireless access networks offers significant opportunities for network operators to satisfy user demands, and simultaneously reduce the cost of implementing and running separated wireless and wired networks. The integration of wired and wireless network can be accomplished within several scenarios and at several levels. In this thesis we will focus on converged radio over fiber architectures, particularly on two application scenarios: converged optical 60 GHz wireless networks and wireless overlay backhauling over bidirectional colorless wavelength division multiplexing passive optical networks (WDM-PONs). In the first application scenario, optical 60 GHz signal generation using external modulation of an optical carrier by means of lithium niobate (LiNbO3) Mach- Zehnder modulators (MZM) is considered. The performance of different optical modulation techniques, robust against fiber dispersion is assessed and dispersion mitigation strategies are identified. The study is extended to 60 GHz carriers digitally modulated with data and to systems employing subcarrier multiplexed (SCM) mm-wave channels. In the second application scenario, the performance of WDM-PONs employing reflective semiconductor optical amplifiers (RSOAs), transmitting an overlay orthogonal frequency-division multiplexing (OFDM) wireless signal is assessed analytically and experimentally, with the relevant system impairments being identified. It is demonstrated that the intermodulation due to the beating of the baseband signal and wireless signal at the receiver can seriously impair the wireless channel. Performance degradation of the wireless channel caused by the RSOA gain modulation owing to the downstream baseband data is also assessed, and system design guidelines are provided.