Evaluation of a Low-cost Inertial Dynamic Measurement System

For a parallel kinematic machine (PKM), encoders may be used to measure the relative change in length of the strut but they cannot detect any deformation of the strut due to thermal expansion and load. To obtain this type of data displacement should be directly measured for each strut. The use of inertial sensors provides a possible solution for the PKM strut length measurement. However, due to the dynamic characteristics of an inertial system and the effect of the machine tool environment, the inertial data contained bias error, misalignment and wide band random noise, and thus resulted in system position inaccuracy. In this paper, an inertial sensor based dynamic measurement system is introduced. Errors contained in the measurement system are analysed. To suppress the residual error which causing drifting error in position due to double integration process, an external measurement is used to estimate the system state variables through Kalman Filter data fusion. Results from these data processing methods applied are presented and analysed.

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