02555nam a2200241 a 4500 vtls000078557 KUKTEM 20251114204613.0 140523t2013 my a f m 000 0 eng d THE0005500(Local) 201905160945 hanafiah 201405231544 training4 UMP QA76.9.D343 S93 2013 rs Bc. Nur Syazwani Samsudin Data filtering of 5-axis inertial measurement unit using kalman filter / Nur Syazwani Samsudin Kuantan, Pahang : UMP, 2013 xv, 55 p. : ill. (some col.) ; 30 cm. + 1 CD-ROM Project paper (Bachelor of Mechatronics Engineering) -- Universiti Malaysia Pahang -- 2013 Bibilography : p. 39-41 This thesis has the purpose to design and develop data filtering of 5-axis Inertial Measurement Unit (IMU) using Kalman Filter. This project endeavour to verify that the data from 5DOF IMU can be filtered using Kalman Filter method so that it can be used as an algorithm in motion alignment. The IMU consists of 2-axis of gyroscopes and 3-axis of accelerometer. The Kalman filter is a set of mathematical equations that provides an efficient computational (recursive) means to estimate the state of a process, in a way that minimizes the mean of the squared error. The main contribution of these algorithms is the in-motion alignment approach with unknown initial conditions. This study explores the use of Kalman filtering of measurements from an inertial measurement unit (IMU) to provide information on the orientation. The performances of each filter are evaluated in terms of the roll, pitch, and yaw angles. In this thesis, I had made an entire required analysis, design circuit, output and input data measurement and other important parameters to develop the data filtering of 5-axis IMU that can be implemented by using Kalman filter method. Simulation with constructed data has been done to verify the algorithm. Also the sensor errors and their effects are discussed. Furthermore the strategy for calibration, initialization and alignment for the system is proposed. On the other hand, this thesis is aim to provide objective and scope of the research, the literature review study, research methodology, and fabrication process with result analysis and conclusion as part requirement in submitted the thesis to FYP supervisor. Data filtering 0 0 0 1 20000 20000 2019-09-04 0 QA76.9.D343 S93 2013 rs Bc. 0000080270 2019-09-04 00:00:00 1 2019-09-04 PSM 0 0 0 1 20000 20000 2019-09-04 0 CD 7740 | QA76.9.D343 S93 2013 rs Bc. 0000080271 2019-09-04 00:00:00 1 2019-09-04 PSM VIRTUA40 4913 4919 VTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*9992