This paper focuses on the evaluation of a low-cost MEMS based sensor combining gyroscope and accelerometer, using integrated monitoring solutions based on advanced numerical techniques developed in the NI LabVIEW software. The low-cost sensor was housed in a robust enclosure and used, alongside high precision calibrated equipment to evaluate its performance, in dynamic shaking table tests on a soil embankment scale model. User-modified Kalman and Complementary filters developed in LabVIEW code were used to calculate the induced tilt during tests, by fusion of acceleration and rotation rate in post-processing. A data acquisition LabVIEW script was developed to collect tilt and acceleration data from the sensor in real-time, with data being derived by sensor embedded high-accuracy filters utilizing Quaternion theory. A high-performance LabVIEW code was also developed specifically for processing the sensor’s accelerometer data, intended for SHM applications using the Modified Butterworth Filter to integrate the recorded accelerometer values into displacement. The low-cost sensor results for acceleration, tilt and displacement were verified against high-end acceleration and displacement measurements translated into displacement and/or tilt respectively.
 

MEMS,Kalman Filter,LabVIEW,Butterworth Filter,Field monitoring