Estimation of electrical machine speed using sensorless technology and neural networks

The use of sensorless technologies is an increasing tendency on industrial drivers for electrical machines. The estimation of electrical and mechanical parameters involved with the electrical machine control is used very frequently in order to avoid measurement of all variables related to this process. The cost reduction may also be considered in industrial drivers, besides the increasing robustness of the system, as an advantage of the use of sensorless technologies. This work proposes the use of a recurrent artificial neural network to estimate the speed of induction motor for sensorless control schemes using one single current sensor. Simulation and experimental results are presented to validate the proposed approach. ©2008 IEEE.

A New Approach for Real Time Fault Diagnosis in Induction Motors Based on Vibration Measurement

Condition monitoring is used to increase machinery availability and machinery performance, reducing consequential damage, increasing machine life, reducing spare parts inventories, and reducing breakdown maintenance. An efficient real time vibration measurement and analysis instruments is capable of providing warning and predicting faults at early stages. In this paper, a new methodology for the implementation of vibration measurement and analysis instruments in real time based on circuit architecture mapped from a MATLAB/Simulink model is presented. In this study, signal processing applications such as FIR filters and fast Fourier transform are treated as systems, which are implemented in hardware using a system generator toolbox, which translates a Simulink model in a hardware description language - HDL for FPGA implementations.

Rotor Failure Diagnosis of Induction Motors by Wavelet Transform and Fourier Transform in Function of the Load

This paper presents two diagnostic methods for the online detection of broken bars in induction motors with squirrel-cage type rotors. The wavelet representation of a function is a new technique. Wavelet transform of a function is the improved version of Fourier transform. Fourier transform is a powerful tool for analyzing the components of a stationary signal. But it is failed for analyzing the non-stationary signal whereas wavelet transform allows the components of a non-stationary signal to be analyzed. In this paper, our main goal is to find out the advantages of wavelet transform compared to Fourier transform in rotor failure diagnosis of induction motors.

Proposta de uma metodologia para obtenção de um gerador síncrono com rotor de ímãs permanentes inclinados axialmente para microcentrais elétrica a partir de motor de indução

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Vibration Attenuation in Rotating Machines Using Smart Spring Mechanism

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Analysis of the electrical conductivity in milking fractions as a mean for detecting and characterizing mastitis in goats

The aim of the work was to study the effect of milking fraction on electrical conductivity of milk (EC) to improve its use in dairy goat mastitis detection using automatic EC measurements during milking. The experiment was carried out on a group of 84 Murciano-Granadina goats (28 primiparous and 56 multiparous). Goats were in the fourth month of lactation. A linear mixed model was used to analyse the relationship between EC or somatic cell count (SCC) of gland milk and parity, mammary gland health status, analysed fraction (first 100 mL=F-1; machine milk=F-2; and stripping milk=F-3) and their first order interactions. Additionally, the mastitis detection characteristics (sensitivity, specificity, positive predictive value and negative predictive value) of SCC and EC were studied at different thresholds.All factors considered were significant for EC and SCC. EC decreased significantly as milking progressed (from F-1 to F-3) in both healthy and infected glands. EC was not significantly different between healthy and infected glands in F-1 and F-2 fractions, but EC of healthy glands (5.01 mS/cm) was significantly lower than in infected glands (5.03 mS/cm) at F-3.Mastitis detection characteristics of EC did not differ amongst studied fractions. The small significant difference of EC between healthy and infected glands obtained in F-3 fraction did not yield better sensitivity results compared to F-1 and F-2. The best EC mastitis detection characteristics were obtained at 5.20 mS/cm threshold (sensitivity of 70% and specificity of 50%). The best SCC mastitis detection characteristics were obtained at 300,000 cells/mL threshold and F-3 fraction (sensitivity of 85% and specificity of 65%).It was concluded that mastitis detection characteristics of EC were similar in the three milking fractions analysed, being slightly better for SCC in F-3 fraction. As shown in previous studies, there are no factors other than the mammary gland health status that affect milk EC and should be considered in the algorithms for mastitis detection to improve the results. (C) 2012 Elsevier B.V. All rights reserved.

A comment on a nonideal centrifugal vibrator machine behavior with soft and hard springs

This paper concerns a type of rotating machine (centrifugal vibrator), which is supported on a nonlinear spring. This is a nonideal kind of mechanical system. The goal of the present work is to show the striking differences between the cases where we take into account soft and hard spring types. For soft spring, we prove the existence of homoclinic chaos. By using the Melnikov's Method, we show the existence of an interval with the following property: if a certain parameter belongs to this interval, then we have chaotic behavior; otherwise, this does not happen. Furthermore, if we use an appropriate damping coefficient, the chaotic behavior can be avoided. For hard spring, we prove the existence of Hopf's Bifurcation, by using reduction to Center Manifolds and the Bezout Theorem (a classical result about algebraic plane curves).

Stepping-motor-driven constant-shear-rate rotating viscometer

Despite the frequent use of stepping motors in robotics, automation, and a variety of precision instruments, they can hardly be found in rotational viscometers. This paper proposes the use of a stepping motor to drive a conventional constant-shear-rate laboratory rotational viscometer to avoid the use of velocity sensor and gearbox and, thus, simplify the instrument design. To investigate this driving technique, a commercial rotating viscometer has been adapted to be driven by a bipolar stepping motor, which is controlled via a personal computer. Special circuitry has been added to microstep the stepping motor at selectable step sizes and to condition the torque signal. Tests have been carried out using the prototype to produce flow curves for two standard Newtonian fluids (920 and 12 560 mPa (.) s, both at 25 degrees C). The flow curves have been obtained by employing several distinct microstep sizes within the shear rate range of 50-500 s(-1). The results indicate the feasibility of the proposed driving technique.

Analytical method for the design of a machine with aligned and skewed permanent magnets

This work aims to present the design and the evaluation of a standard multi-pole machine with permanent magnets inserted in the rotor by two different geometrical forms: aligned and skewed magnets. The design (new analytical method) was based on a standard 250 W three phase 12-pole induction motor (squirrel cage rotor type), beginning with the original stator constructive data to calculate the magnetic flux density to determine the permanent magnets. In the development of the work, a simple and modular rotor was built reusing the original 12-pole stator (concentrated windings). The machine was evaluated in a laboratory for the purpose of checking the quantity and quality of energy produced with the machine operating as a generator and its start, torque, and performance working as a motor. In conclusion, the modular skewed magnet is an option for electrical machines, for the generation of a reasonable quality, in the context of decentralized generation and a motor with high torque and low energetic consumption.

Transient stability analysis of electrical power systems using a neural network based on fuzzy ARTMAP

This work presents a methodology to analyze transient stability for electric energy systems using artificial neural networks based on fuzzy ARTMAP architecture. This architecture seeks exploring similarity with computational concepts on fuzzy set theory and ART (Adaptive Resonance Theory) neural network. The ART architectures show plasticity and stability characteristics, which are essential qualities to provide the training and to execute the analysis. Therefore, it is used a very fast training, when compared to the conventional backpropagation algorithm formulation. Consequently, the analysis becomes more competitive, compared to the principal methods found in the specialized literature. Results considering a system composed of 45 buses, 72 transmission lines and 10 synchronous machines are presented. © 2003 IEEE.

Active control in rotating machinery using magnetic actuators with linear matrix inequalities (LMI) approach

The recent years have seen the appearance of innovative system for acoustic and vibration attenuation, most of them integrating new actuator technologies. In this sense, the study of algorithms for active vibrations control in rotating machinery became an area of enormous interest, mainly due to countless demands of an optimal performance of mechanical systems in aircraft, aerospace and automotive structures. In this way, this paper presents an approach that is numerically verified for active vibration control in a rotor using Active Magnetic Bearings (AMB). The control design in a discrete state-space formulation is carried out through feedback technique and Linear Matrix Inequalities (LMI) approach. LMI is useful for system with uncertainties. The AMB uses electromagnetic forces to support a rotor without mechanical contact. By monitoring the position of the shaft and changing the dynamics of the system accordingly, the AMB keeps the rotor in a desired position. This unique feature has broadened for the applications of AMB and now they can be considered not only as a main support bearing in a machine but also as dampers for vibration control and force actuators. © 2009 Society for Experimental Mechanics Inc.

Development of an instrumentation system embedded on FPGA for real time measurement of mechanical vibrations in rotating machinery

The real-time monitoring of events in an industrial plant is vital, to monitor the actual conditions of operation of the machinery responsible for the manufacturing process. A predictive maintenance program includes condition monitoring of the rotating machinery, to anticipate possible conditions of failure. To increase the operational reliability it is thus necessary an efficient tool to analyze and monitor the equipments, in real-time, and enabling the detection of e.g. incipient faults in bearings. To fulfill these requirements some innovations have become frequent, namely the inclusion of vibration sensors or stator current sensors. These innovations enable the development of new design methodologies that take into account the ease of future modifications, upgrades, and replacement of the monitored machine, as well as expansion of the monitoring system. This paper presents the development, implementation and testing of an instrument for vibration monitoring, as a possible solution to embed in industrial environment. The digital control system is based on an FPGA, and its configuration with an open hardware design tool is described. Special focus is given to the area of fault detection in rolling bearings. © 2012 IEEE.

Hot turning of a difficult-to-machine steel (sae xev-f) aided by infrared radiation

A possible way for increasing the cutting tool life can be achieved by heating the workpiece in order to diminish the shear stress of material and thus decrease the machining forces. In this study, quartz electrical resistances were set around the workpiece for heating it during the turning. In the tests, heat-resistant austenitic alloy steel was used, hardenable by precipitation, mainly used in combustion engine exhaustion valves, among other special applications for industry. The results showed that in the hot machining the cutting tool life can be increased by 340% for the highest cutting speed tested and had a reduction of 205% on workpiece surface roughness, accompanied by a force decrease in relation to conventional turning. In addition, the chips formed in hot turning exhibited a stronger tendency to continuous chip formation indicating less energy spent in material removal process. Microhardness tests performed in the workpieces subsurface layers at 5 m depth revealed slightly higher values in the hot machining than in conventional, showing a tendency toward the formation of compressive residual stress into plastically deformed layer. The hot turning also showed better performance than machining using cutting fluid. Since it is possible to avoid the use of cutting fluid, this machining method can be considered better for the environment and for the human health.

Expert system to detect incipient fauts in rotating machines using fuzzy logic and virtual instrumentation

This paper refers to the design of an expert system that captures a waveform through the use of an accelerometer, processes the signal and converts it to the frequency domain using a Fast Fourier Transformer to then, using artificial intelligence techniques, specifically Fuzzy Reasoning, it determines if there is any failure present in the underlying mode of the equipment, such as imbalance, misalignment or bearing defects.