Research And Implementation Of On Position And Gesture Measurement Module In Beef Meat Yield Predictive Device

This research aims to develop a module used for measuring the position and rotation attitude of the living body predictive device for beef meat yield, which can make preparation for building three-dimensional beef body model and predicting living beef meat yield. According to the principle of inertial navigation, this module calculates the predictive device’s position and rotation attitude using the acceleration velocity and angular velocity data collected by ZigBee wireless data transmission technique. The main work of this paper is as follows:(1) Designing and implementation of the position and attitude measurement module. For the purpose of convenience and low cost, MEMS accelerometer, gyroscope and ZigBee are used to compose this module. According to the real requirements for the beef meat yield prediction device, this paper designs the hardware and software for the position and attitude measurement module. The acceleration velocity data and angular velocity data are collected by the ZigBee module, which controls the accelerometer and gyroscope with its main chip CC2530. The collected is then sent to PC to be processed.(2) Building of error model for accelerometer and gyroscope. By analyzing the error components of accelerometer and gyroscope, this study builds the error model for accelerometer and gyroscope, which contains 24 undetermined parameters with the main parameters being zero bias, scale factor, cross coupling and random error. The12-position method and the angular position method are respectively used to calibrate the parameters in the error model for accelerometer and the error model for gyroscope. Then devided the undetermined parameters of error models and worked out the matematical expressions of error models. In above process, the Kalman filtering is also used to deal with random error so as to reduce the random error of accelerometer and gyroscope. The experimental results of the testing for error models show that, compared with the variance of the accelerometer without error model, the variance of the accelerometer with error model reduces by 84.78%; compared with the measuring error of the gyroscope without error model, the measuring error of the gyroscope with error model reduces by 88.25%.(3) The calculation of carriers’ attitude and position. In this part, quaternions are adopted for calculating the carriers’ attitude with using collected acceleration velocity and angular velocity data and 4th order Runge-Kutta algorithm is used to update quaternions. The author takes carriers’ attitude information calculated by angular velocity as measuring data, takes the accelerometer data as observing data and fuses these two kinds of data with UKF filtering algorithm. The error caused by gyroscope drift in the process of attitude calculation is reduced and the precision of attitude calculation is improved because of using UKF filtering algorithm. The results of the attitude calculation experiments show that the static deviation in 300 seconds is within-0.2o~+0.2o and the dynamic deviation is within-2o~+2o. This study also derives the force ratio equation suitable for the position and attitude measurement module and works out the calculation method for speed and attitude. The maximum errors of position calculation along X- axis, Y- axis and Z- axis are 0.0216 m, 0.0959 m and-0.0289 m respectively when the position and attitude measurement module is carried out along a 1-meter long segment.