DEVELOPEMENT OF INTEGRATION AND DIFFERENTIATION METHOD TO REDUCE NOISE EFFECT

There are three variables commonly used in vibration measurement; those are displacement, velocity, and acceleration. Mathematically, each of those variables has a <br /> <br /> <br /> simple relationship to anothers. For example, displacement is the integration result of velocit...

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主要作者: PURNAMA (NIM : 231 08 023); Pembimbing : Dr. Ir. Zainal Abidin, FANDI
格式: Theses
語言:Indonesia
在線閱讀:https://digilib.itb.ac.id/gdl/view/15627
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機構: Institut Teknologi Bandung
語言: Indonesia
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總結:There are three variables commonly used in vibration measurement; those are displacement, velocity, and acceleration. Mathematically, each of those variables has a <br /> <br /> <br /> simple relationship to anothers. For example, displacement is the integration result of velocity with respect to time and velocity itself is the integration result of acceleration with respect to time. In other words velocity is the differentiation result of displacement with respect to time while acceleration is the differentiation result of velocity with respect to time. <br /> <br /> <br /> Integration as well as differentiation processes are widely used in industry for vibration measurement. As the most popular portable vibration instrument used is accelerometers while online instruments commonly use displacement and velocity sensors, the conversion process is inevitable. Unfortunately, these integration and differentiation processes may cause problems due to numerical approximation especially when unwanted noise present in the signal. This research is dedicated to propose a new integration and differentiation method which can reduce the noise effect. <br /> <br /> <br /> In addition to the developement of integration and differentiation methods with ability to reduce noise, a mathematical analysis has been made to investigate the characteristics of the proposed methods. Furthermore a numerical simulation and an experiment testing have also been conducted to validate the mathematical analysis. Based on the validation, it can be concluded that the analysis developed in this work is correct.