Abstract
In this study, dynamic modeling of an accelerometer based inclinometer is carried out. Empirical methods are used in order to obtain the model of the system and an experimental setup is designed and constructed to realize the required experiments. Classical system identification and neural network methods are used to acquire the dynamic models. Since, accelerometers/inclinometers are commonly used in spatially moving vehicles; simulation models of these are needed. Taking advantage of this dynamic model, the simulation results, which include accelerometers/inclinometers, can become more realistic and extensive filtering techniques would work more efficiently with better sub-system models.
Keywords
Inclinometer
Accelerometer
Computer science
Artificial neural network
System identification
Control engineering
Simulation
Artificial intelligence
Data modeling
Engineering
Subject Areas
Hydrological Forecasting Using AI
·Environmental Engineering ·Physical Sciences
Flow Measurement and Analysis
·Mechanics of Materials ·Physical Sciences
Structural Health Monitoring Techniques
·Civil and Structural Engineering ·Physical Sciences
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