A Simple Instrumentation System for Large Structure Vibration Monitoring

TELKOMNIKA 12/2010; 8(3). DOI: 10.12928/telkomnika.v8i3.628
Source: DOAJ


Traditional instrumentation systems used for monitoring vibration of large-scale infrastructure building such as bridges, railway, and others structural building, generally have a complex design. Makes it simple would be very useful both in terms of low-cost and easy maintenance. This paper describes how to develop the instrumentation system. The system is built based on distributed network, with field bus topology, using single-master multi-slave architecture. Master is a control unit, built based on a PC equipped with RS-485 interface. Slave is a sensing unit; each slave was built by integrating a 3-axis vibration sensor with a microcontroller based data acquisition system. Vibration sensor is designed using the main components of a MEMS accelerometer. While the software is developed for two functions: as a control system hardware and data processing. To verify performance of the developed instrumentation system, several laboratory tests have been performed. The result shows that the system has good performance.

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    • "Displacement as one component in vibration can be detected by a variety of displacement sensors working based on different principles. These sensors work based on capacitive, inductive, piezoelectric and most recently using optical technology [1]-[2]. Displacement sensor based on optical technology has drawn increasing attention from manufacturers and researchers since it can give remarkable performances in high sensitivity, lightweight, fast response and immunity to electromagnetic interference (EMI) [3]-[4]. "
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    ABSTRACT: This paper presents an improved Fringe Counting Method (FCM) technique in order to enhance the displacement resolution of a Fabry-Perot Displacement Sensor (FPDS). A simulation model of a FPDS based on the improved FCM has been developed and simulated for nanometer displacement range by using MATLAB mathematical software. Unlike conventional FCM that analyzed the number of fringes produced over one time period, the improved FCM analyzed the number of fringes for one largest Free Spectral Range (FSR). In this work, the initial length of Fabry-Perot Interferometer (FPI) cavity has been set at 75 μm due to limitation of the machining precision equipment. For the displacement analysis, the improved FCM technique is used as an algorithm. The research results prove that this FPDS could detect displacement at 10nm resolution over a working range of 40 nm. It showed that the improved FCM technique managed to enhance the capability of the conventional FCM in detecting nanometer displacement.
    Preview · Article · Dec 2014
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    • "MMA7260QT from Freescale Semiconductor and ADXL345 from Analog Devices. Both sensors are three-axis accelerometer but the MMA7260QT has analog output with MEMS technology [1] while the ADXL345 is digital output via I2C bus [2]. Important points for performance evaluation in this research are interfacing to microcontroller, reading sensor data with microcontroller, noise and combination with gyroscope sensor. "
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    ABSTRACT: A self balancing robot (SBR) controller needs to detect platform inclination. For this purpose, an accelerometer is used. From various types of accelerometer, we can divide into digital and analog ones. The problem is how to select the right type for the SBR. This paper evaluates the performance of the ADXL345, 3-axis digital output accelerometer and the MMA7260QT, 3-axis analog output accelerometer. The Arduino is used to read data from the sensor and send it to PC for plotting. Both sensors use the lowest sensitivity. The sensors are evaluated with three criteria, i.e. stationary, dynamical response and collaborating with ITG3200 3-axis gyroscope for Kalman filter fusion. For stationary criterion, the ADXL345 is better than the other sensor for all stationary position. For dynamical response, both sensors suffer from the noise due to acceleration of the platform. The sensors do not only sense the gravity but also the acceleration of the platform when it is moved. But the noise level for the ADXL345 is lower than the other. Using Kalman filter makes both sensors show good performance for a SBR application. If three criteria are combined with hardware aspect, then the authors recommend using the ADXL345. Besides, it has several useful features to handle abrupt acceleration.
    Full-text · Article · Mar 2013