Abel Cavalcante Lima Filho

Telemetric system for monitoring and automation of railroad networks

This paper describes a new method of real-time train monitoring based on the ZigBee/IEEE 802.15.4 protocol. The system consists of a mobile device embedded in the moving train which transmits parameter signals that are being measured by a base unit with the help of routers. When applied, the technique monitors and controls vehicles operating on permanent routes, making a real-time evaluation of their performance and location, and allowing an effective planning of trains. It consists of a low cost, low power consumption and safe modular technology capable of monitoring many different variables simultaneously.

Experimental and theoretical study of a telemetric dynamic torque meter

This paper presents the development of a dynamic torque meter to be applied to rotating shafts using electronic transduction, strain gage, telemetry and LabView Graphic programming. A mathematical model was developed. The electronic transduction signal is transmitted by digital modulation from a remote transduction unit fixed to a shaft to a base station, sending the signal to a PC, by means of a VI (Virtual Instrument) developed in LabView. It can also be delivered to other units besides the PC. The use of digital modulation to transmit the radiofrequency signal, replacing conventional couplings, allows communication with a high signal/noise ratio. A clamp acts as sealant, protecting it from the environment and making it easier to install. The prototype can be used at situation that it is impossible to use flanges or sockets (the most of the industrial applications) and it is installed directly on the surface of the shaft. The use of superbatteries allows the remote unit to remain independent of a feed for several days, with long periods between maintenance. After thousands of experimental essays, the theoretical model seems to confirm the proposed idea. The system presented has a potential for high precision, low cost, long work life and easy maintenance.

Self-Powered Telemetric Torque Meter

This paper presents a self-powered telemetric torque meter. The idealized instrument uses strain gauge, telemetry, and LABVIEW graphic programming. The electronic transduction signal is transmitted by digital modulation from a remote transduction unit fixed to a rotation shaft to a base station sending signals to a personal computer (PC) by means of a virtual instrument developed in LABVIEW . The signal can also be delivered to other units besides the PC. The ZigBee/IEEE 802.15.4 protocol is the standard protocol for wireless communications and is highly used in industrial monitoring and control applications. A low-noise method for supplying the remote transduction unit components in the rotation shaft—using its rotating movement to generate the demanded energy—has also been developed. After extensive experimentation, the theoretical model seems to confirm the idea proposed. The system presented in this study is robust, precise, cost-effective, and has high-noise immunity even in abrasive and strong vibration environments.

Real-time link quality estimation for industrial wireless sensor networks using dedicated nodes

Adaptive mechanisms, such as dynamic channel allocation or adaptive routing, are used to deal with the variations in the link quality of Wireless Sensor Networks (WSN). In both cases, the first step is to estimate the link quality, so that the network nodes can decide if a channel or route change is needed. This paper proposes a Link Quality Estimator (LQE) for Industrial WSN, and a new type of node, the LQE node, that estimates the link quality in real-time, using the Received Signal Strength Indication (RSSI), and information obtained from received data packets. The proposed LQE is capable of capturing the effects of multipath, interference, and link asymmetry. Experiments were performed in a real industrial environment using IEEE 802.15.4 radios, and models were developed to allow the use of RSSI samples to proper estimate the link quality. A comparison was performed with a state-of-the-art LQE, the Opt-FLQE, and the results showed that the proposed estimator is more accurate and reactive for the type of environment in study. Different from other LQEs in literature, in the proposed LQE the sensor nodes do not need to send broadcast probe packets. Besides, using the LQE node, the other nodes of the WSN do not need to stop their operation to monitor the link quality.

Distributed approach for channel quality estimation using dedicated nodes in industrial WSN

A way to deal with the variations in the link quality of Wireless Sensor Networks (WSN) is the use of strategies for Dynamic Channel Allocation (DCA). The first step to perform DCA is estimating the channel quality, so that the network nodes can decide if a channel change is needed, and the best channel to be used. This paper proposes a distributed approach with nodes dedicated to monitor channel quality, by using the Received Signal Strength Indication (RSSI) and the Link Quality Indicator (LQI) to identify low quality channels. This approach is acceptable in industrial WSN, since the network deployment can be performed with adequate planning. Furthermore, the sensor nodes do not need to stop their operation for monitoring the channel quality. As a first step, experiments were performed in a real industrial environment to identify the relation between RSSI and LQI traces, and the Packet Error Rate for different channels, by using IEEE 802.15.4 radios operating in the 2.4 GHz band.

New Contactless Torque Sensor Based on the Hall Effect

Measuring and controlling torque in rotary systems is essential to preventing wear, damage, breakage, and other machine malfunctions caused by excessive shaft torque. The classical methods and those currently available on the market utilize systems that must be electrically powered and for which their data must be acquired by collector rings, transformers or telemetry systems. This paper develops a torque transducer for rotating shafts using a new approach that utilizes neodymium magnets and Hall effect sensors. A pair of magnets is attached to the rotating shaft, and a magnetic field measurement system with Hall effect sensors is positioned in a stationary unit close to the shaft. The relative movement between the magnets due to deformation resulting from torsion will increase or decrease the magnetic field strength. By measuring the strength of this resulting field, it is possible to determine the radial deformation of the shaft. Dynamic tests were performed in the laboratory to validate this technique and to compare it with widespread industrial techniques. The results show the efficacy of the technique and point to potential applications of this dynamic torque sensor using the Hall effect.

Application of Wireless Sensor Networks Technology for Induction Motor Monitoring in Industrial Environments

In an industrial environment, mechanical systems driven by electric motors are used in most production processes, accounting for more than two thirds of industry electricity consumption. Regarding the type of motors usually employed, about 90% are three-phase AC induction based [1], mainly due to its cost effectiveness and mechanical robustness [2].

Embedded System for Speed Estimation by Means of Sound Analysis in Three-Phase Induction Motors

Electric motors consume a large portion of the electric power generated. Three-phase induction motors are the most used in industries, for their robustness, reliability and easy operation. They are inserted in the most diverse processes as the main electromotive force. Measuring speed directly on the motor shaft is no trivial task, because it requires time and additional cost due to adaptations of speed transducers to the axis, which causes costly stops to the process in which this motor is inserted. For this reason, manufacturers and research centers around the world have been developing speed estimation methods based on sensorless techniques. The speed measurement in motors can be used for various applications from vector control of the machine to failure analysis. In this work, a new method was developed and installed in an embedded system to estimate the speed in threephase induction motors through the FFT motor sound analysis. This technique proved to be reliable, showing good accuracy in comparison to the measured speed on the shaft, demonstrating the effectiveness of the method and applicability in other areas of technical and scientific relevance such as analysis and prevention of bearing failures or any mechanism involving shaft rotation.

A Hybrid System Based on Fuzzy Logic to Failure Diagnosis in Induction Motors

The induction motors are the main equipment used for electromechanical conversion in the world, and are present in almost all production processes, accounting for about two thirds of the industrial electrical consumption. Faults in induction motors can result in operational disasters, and stop entire sectors of a plant, causing economic and human losses. Therefore, the development of appropriate techniques for fault diagnosis in induction motors is critical. Classical methods for induction motors fault diagnosis do not always provide satisfactory results. This paper proposes a hybrid system that uses data obtained from vibration, and current sensors to detect failures at an early stage, since each technique has limitations and disadvantages when used individually. The signals are processed in the frequency and time domain through short time Fourier transform and wavelet multi-resolution analysis, which provides inputs to an intelligent system based on fuzzy logic. The failures due to unbalanced load in the motor shaft and in the motor helix were correctly detected. Experiments with broken bars were also performed, and the system was also validated for this type of failure. The signal processing, and the classification of the failure severity, through fuzzy logic, were developed using Matlab.

GeneticBee: A theoretic and evolutionary formulation for the energy efficiency problem of urban trains

The electric motors of the trains in a railway system are powered by electricity, and the energy demand is high. In addition, rail-based transport systems continue to grow, and therefore, solutions are currently sought to optimise energy consumption. This article presents an analysis of electric multiple units (EMUs) of the Companhia Brasileira de Trens Urbanos — Brazilian Urban Train Company (CBTU) — Recife, Brazil and the use of electric power provided by the engines during acceleration and braking. To this end, a general model is proposed that encompasses an analysis of the speed and driving profiles, herein termed speed profile optimisation. This model is validated by empirical simulations with the aid of MATLAB software and the implementation of a genetic algorithm of artificial intelligence using the Java programming language. We intend to demonstrate that by controlling the train speed profiles and considering some limits, restrictions and parameters, a decrease in energy consumption in the analysed stations will follow, which will promote more sustainable transport and cost savings.