Tito G. Amaral

• Polytechnic Institute of Setúbal

The use of load-monitoring systems in residential homes is fundamental in the context of smart homes and smart grids. Specifically, these systems will allow, for example, the provision of efficient energy management and/or load forecasting for residential homes. To achieve this goal, these systems can be based on the concept of a smart meter. Howev...

This article deals with fault detection and the classification of incipient and intermittent open-transistor faults in grid-connected three-level T-type inverters. Normally, open-transistor detection algorithms are developed for permanent faults. Nevertheless, the difficulty to detect incipient and intermittent faults is much greater, and appropria...

Pumping systems play a fundamental role in many applications. One of the applications in which these systems are very important is to pump water. However, in the real world context, the use of renewable energies to supply this kind of system becomes essential. Thus, this paper proposes a water pumping system powered by a photovoltaic (PV) generator...

Solar photovoltaic simulators are valuable tools for the design and evaluation of several components of photovoltaic systems. They can also be used for several purposes, such as educational objectives regarding operation principles, control strategies, efficiency, maintenance, and other aspects. This paper presents an automated solar photovoltaic s...

Neutral Point Clamped Asymmetric-Half-Bridge ( NPC-AHB ) has been proposed as one of the power converter topologies for the Switched Reluctance Machine ( SRM ) drive. This topology is characterized by multilevel operation and the capability to operate in fault tolerant mode, which is most indicated for use in applications that require high reliab...

Photovoltaic power plants nowadays play an important role in the context of energy generation based on renewable sources. With the purpose of obtaining maximum efficiency, the PV modules of these power plants are installed in trackers. However, the mobile structure of the trackers is subject to faults, which can compromise the desired perpendicular...

The power electronic converter design is essential for the operation of the switched reluctance motor (SRM). Thus, a fault-tolerant power converter is fundamental to ensure high reliability and extend the drive operation. To achieve fault tolerance, fault detection and diagnosis methods are critical in order to identify, as soon as possible, the fa...

In many photovoltaic (PV) power plants, the PV modules are installed in trackers. In these systems, the PV modules are fixed in a mobile structure to always maintain a perpendicular position to the brightest point in the sky, obtaining in this way the maximum power from the sun, during the all day. Nevertheless, these systems are subject to problem...

Automated Optical Inspection (AOI) Systems are commonly used on Printed Circuit Boards (PCB) manufacturing. The use of this technology has been proven as highly efficient for process improvements and quality achievements. The correct extraction of the component for posterior analysis is a critical step of the AOI process. Nowadays, the Pattern Matc...

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...

Automated optical inspection (AOI) systems are commonly used in PCB manufacturing. The use of this technology has been proven as highly efficient for process improvements and quality achievements. The most challenging point in inspection of surface mounting devices (SMD) is the component solder joints, due to their specular reflects. Several studie...

Voltage source inverters are essential systems in many applications. Thus, the diagnosis of the faults that could appear in these systems allows detecting, isolating, and identifying the faults. In this context the teaching of this subject is becoming very important. However, laboratory experience is fundamental in order to provide a real understan...

In grid-connected photovoltaic systems (PV) the inverter is a fundamental component. In fact, a fault in a switch of this power converter could result in an important system malfunction. Thus, fault detection and diagnosis of this fault type is fundamental to overcome this problem. This paper proposes a fault detection diagnosis for the T-type thre...

The study of fault detection and diagnosis of electrical machines, in particular induction motors, as well as the teaching of their behavior requires practical experience in this field. To provide this experience to the students this paper presents an experimental system that can be used with a standard industrial electrical induction machine. This...

This paper proposes a methodology that analysis and classifies the EMG and MMG signals using a linear neural network to control prosthetic members. Finger motions discrimination is the key problem in this study. Thus the emphasis is put on myoelectric signal processing approaches in this paper. The EMG and MMG signals classification system was esta...

This paper describes a shot segmentation algorithm for online video event detection in broadcast news. The algorithm is based on image detection contour with an adaptive threshold. The performance of this algorithm is evaluated in terms of shot boundaries detection. The relevance of the boundaries detected is also evaluated in order to preview the...

This paper investigates the use of the current trajectory mass center in a three dimensional referential. The proposed approach uses the inverter output currents. These currents are used to obtain a typical pattern in a three dimensional referential. According the fault type different patterns is obtained. In this way, with the proposed approach it...

This paper proposes the use of the S-Transform applied to the stator currents as a method for diagnosing the occurrence of rotor electrical fault (broken bars or faulty rotor windings) in induction motor. Induction motor stator currents are first measured and recorded. Then, the S-Transform is applied to the obtained currents in order to get a spec...

In this paper a new approach for power quality (PQ) event detection and classification is proposed. This approach is based on an automatic four step algorithm. First the acquired voltage signals are represented in a 3-D space referential. Then principal component analysis is performed. In the third, features are extracted from the obtained eigenval...

Automated Optical Inspection (AOI) Systems are commonly used on Printed Circuit Boards (PCB) manufacturing process. The use of this technology has been proved to be highly efficient on process improvements and quality achievements. The most difficult point on Surface Mounting Devices (SMD) inspection is the solder joint due to their specular reflec...

In the last few decades the continuous monitoring of complex dynamic systems has become an increasingly important issue across diverse engineering areas. This paper presents a pattern recognition based system that uses visual-based efficient invariants features for continuous monitoring of induction motors. The procedures presented here are based o...

Teaching manipulative therapy is one of the most relevant issues in a physiotherapy course. However, for an effective instruction of this topic practical experience is considered fundamental. To achieve this purpose, this paper presents a computer assisted environment for the practical learning of manipulative therapy. The implementation of such a...

Automated systems based on optical inspection are widely used in the production of electronic systems, mainly on the printed circuit board level. Detection of defects in the early stages of production, reduce costs by lowering the number of scraps and elevate overall quality standards. One of the main areas where defects arise, are in the solders o...

Three-phase voltage-source inverter is one of the most widely used power converters. Therefore, the need to insure a continuous and safety operation for this power converter with fault detection technique is a need, more or less, depending on their application. For this power converter several faults can appear. This paper presents a method for the...

This paper proposes the use of the park transformation mass center applied to the stator currents as a method for diagnosing the occurrence of stator winding faults in induction motor. Induction motor stator currents are first measured and recorded. Then, the park transform is applied to the obtained currents in order to obtain a specific pattern t...

In this chapter an image processing based classifier for detection and diagnosis of induction motor stator fault was presented. This system is based on the obtained stator currents and the correspondent Clark-Concordia transformation. This results in a circular or an elliptic pattern, of the Clark-Concordia stator currents. From the obtained curren...

This paper proposes a methodology that analyses and classifies the electromyographic (EMG) signals using neural networks to control multifunction prostheses. The control of these prostheses can be made using myoelectric signals taken from surface electrodes. Finger motions discrimination is the key problem in this study. Thus the emphasis, in the p...

The aim of this paper is to present a remote learning laboratory for physiotherapists. The implementation of such laboratory uses standard PCs, the popular software package Matlab, gloves with sensors and a camera. This system allows the students to do practical experiences at a long distance. They use a glove that measure the force applied by the...

In this paper a new approach to detect skin in coloured images is proposed. The new method uses the classification of the three colour components of the RGB system (Red, Green and Blue), with a skin classifier. The proposed approach uses an adaptive methodology embedded in the skin classifier algorithm for pixel classification. The adaptive algorit...

The paper presents the concept of genetic algorithm based optimization for the EMG pattern recognition system controlling the hand prosthesis. The recognition of EMG signals for determining the hand movements is made by a linear neural network discriminating between five predefined grasps. The input feature vector for the classification was establi...

In this paper a Web based teaching of electrical drives using a mechanical load simulator is presented. The developed system allows testing the behavior of an electrical machine for different load types. Several typical loads in which the torque depends of time or speed are implemented. In this way, using this tool it is possible to study the dynam...

The study of power system of relays requires some previous experience in this field. Laboratories focusing on teaching and researching the area of power-system protection have therefore been amply reported. However, these facilities require the actual presence of the students in the laboratories. To overcome this problem, a power-system-relaying re...

This paper proposes a methodology that analysis and classifies the EMG and MMG signals using neural networks to control prosthetic members. Finger motions discrimination is the key problem in this study. Thus the emphasis is put on myoelectric signal processing approaches in this paper. The EMG and MMG signals classification system was established...

This paper proposes a movement searching methodology based on 2-D Images, with variable dimension of rectangular cells. The cell dimension is defined automatically based on a statistical adaptive method, which accounts for previous searching results. The main contribution of the present paper in relation to usual image movement searching methods is...

In this paper a new algorithm for the detection of three-phase induction motor stator fault is presented. This diagnostic technique is based on the identification of a specified current pattern obtained from the transformation of the three- phase stator currents to an equivalent two-phase system. This new algorithm proposes a pattern recognition me...

In this paper it is presented an Auxiliary Quantification System of Applied Force in Posteroanterior Movements Technique. This system measures the force applied by the physiotherapist, on the vertebrae of the patients during the application of PosteroAnterior movements, allowing the quantification of the applied force on the therapy. The upper limi...

This paper proposes different topologies for cell dimensioning in 2D-images for movement detection in consecutive frames. These topologies use variable dimension working cells, in 2D-images, and the criteria for cell reduction are based on adaptive methods that account for previous searching results. The developed image processing methodology chang...

In this paper a new algorithm for the detection of a three-phase induction motor stator fault is presented. Several fault detection methods are based on the analysis of the input current Park's vector. This diagnostic technique is based on the identification of a specified current pattern obtained from the transformation of the three-phase stator c...

In this paper it is presented an approach to improve the interpretability of a neuro-fuzzy system. This improvement is achieved through the modification of the Sugeno form of the consequent polynomials into corresponding triangular membership functions. The resulting neuro-fuzzy inference system has the same performance as the initial one and is an...

In this paper, the design and implementation of a real-time landing algorithm for an autonomous helicopter is presented. The helicopter uses an onboard acquisition system to obtain the GPS and the sonar data to update its landing parameters. To control the path during the land step a fuzzy logic controller located in the fixed station is used. This...

In this paper, an adaptive neural-fuzzy walking control of an autonomous biped robot is proposed. This control system uses a feed forward neural network based on nonlinear regression. The general regression neural network is used to construct the base of an adaptive neuro-fuzzy system. The neural network uses an iterative grid partition method for...

This chapter describes the application of a general regression neural network (GRNN) to control the flight of a helicopter. This GRNN is an adaptive network that provides estimates of continuous variables and is a one-pass learning algorithm with a highly parallel structure. Even with sparse data in a multidimensional measurement space, the algorit...

This chapter describes the application of a general regression neural network (GRNN) to control the flight of a helicopter. This GRNN is an adaptive network that provides estimates of continuous variables and is a one-pass learning algorithm with a highly parallel structure. Even with sparse data in a multidimensional measurement space, the algorit...

This paper proposes an adaptive neuro-fuzzy inference controller using a feed forward neural network based on nonlinear regression. The general regression neural network is used to construct the base of an adaptive neuro-fuzzy system. This neural network uses a different learning capability when compared with the classical clustering algorithm. The...

A new approach for an adaptive neuro-fuzzy inference system for modeling and control is proposed. This approach uses a general regression neural network with a different learning capability from the classical clustering algorithm normally used by this specific network. The antecedent parameters of the regression network are obtained through an iter...

In this paper, we address the visual servo control of a robot manipulator under a camera-in-hand configuration. The goal is to recognise several types of different objects in a moving conveyer belt using a camera attached to a robot arm. To accomplish the object recognition three different methods are proposed: statistic based on Hu moments, statis...

This paper describes the application of the fuzzy logic control (FLC) theory to control the helicopter flight on two basic flight modes: hovering and forward. Hovering is a formidable stability problem, where helicopter pilots typically train for weeks before managing to do it manually. Hence automating this operation is in itself an impressive ach...

This paper presents a neuro-fuzzy controller to control a non-linear system such as the flight of a helicopter in the hover and forward flight mode positions. Hovering is a formidable stability problem, where helicopter pilots typically train for weeks before managing to do it manually. Hence automating this operation is in itself an impressive ach...

This paper proposes an adaptive fuzzy logic controller for feedback output voltage control of a single-phase sinusoidal rectifier with step-up/down characteristics. These rectifiers, with a sliding mode current controller, ensure a near unity power factor operation and an input current with low harmonic content. The reference of the current control...

This paper describes a study of two fuzzy based thresholding algorithms for digitising images using the index of fuzziness and fuzzy compactness. The problem of histogram sharpening and thresholding by minimizing grey level fuzziness and compactness is considered. The choices of appropriate membership functions and the optimum value of its bandwidt...

Describes a study of two fuzzy based segmentation algorithms to model successfully ambiguities and uncertainties inherent in assigning an image pixel to an object of interest and to help choosing the threshold for binarizing images using the index of fuzziness and fuzzy compactness. The methods detect object contours to different degrees of certain...

In this paper an adaptive neural-fuzzy walking control of an autonomous biped robot is proposed. This control system uses a feed forward neural network based on nonlinear regression. The general regression neural network is used to construct the base of an adaptive neuro-fuzzy system. The membership functions used in the antecedent part of the fuzz...

In this paper, a neuro-fuzzy system identification using measured input and output data are carried out. A model-free learning from "examples" methodology is developed to train a neuro-fuzzy model of a small- size helicopter. The helicopter model is obtained and tuned using training data gathered while a teacher operates the helicopter. Behavior-ba...

This paper proposes a neuro-fuzzy controller to control a pneumatic robot that can be used in the plastic injection industry. In this controller it is used a new hybrid learning algorithm. This approach uses a feed forward neural network based on nonlinear regression to construct the base of the neuro-fuzzy system. The antecedent parameters of the...