Precision Of D.M.S. Columns From Real Time In-place Measurements And Improvement In Micro-movements Analysis With Early Warning Function
Free (open access)
M. Lovisolo & A. Della Giusta
This paper contains results of statistics on inclinometric data sets obtained from the in-place multiparametric differential system D.M.S. The data analysed here have been collected continuously at prescribed time intervals, and refer to landslide case histories. An estimate of measurements precision was obtained combining the results of both laboratory tests and ‘in-situ’ strings of sensors in vertical boreholes of different depth. Measurement uncertainty is well within the requirements for In Place Inclinometers (Dunnicliff and La Fonta , La Fonta and Beth ). The statistically redundant data collected by D.M.S. allows an appreciable improvement of precision in field measurements. This is a first step towards the solution of the problem of early warning systems for public safety. Keywords: D.M.S., inclinometric data, multiparametric differential system, precision, systematic errors, landslide, micro-movement, early warning. 1 Introduction Knowing the accuracy and precision of inclinometric data is very relevant, particularly when even the smallest indication of displacement is a matter of concern. As thoroughly discussed for the case of probe inclinometers among others by Mikkelsen , field measurements can be influenced by several systematic errors, thus producing false indication of displacement. As a consequence, data must always be accurately screened to evaluate the error
D.M.S., inclinometric data, multiparametric differential system, precision, systematic errors, landslide, micro-movement, early warning.