A methodology for reducing the effect of meteorological parameters on a continuously recording gravity meter

Gravity changes in geodynamically active areas are usually monitored by usi ng discrete measurements. The temporal resolution, which is only as good as the repeat rate of the observations (usually ranging between one month and one year), is the main drawback of such measurements. To achieve a better temporal resolution and thus improve the possibilities of the investigation task, continuous gravity measurements have to be performed. However, tempe rature and pressure fluctuations seriously affect the output of continuousl y running spring gravity meters. In this paper, a methodology allowing the signal from a recording gravity meter to be compensated for the effect of t emperature and pressure is discussed. To model how the meter output depends on the interfering signals, both polynomial (LMS) and nonlinear (neuro-fuz zy) forms of three different model structures have been tested. The results obtained through the nonlinear algorithm are satisfactory and could consti tute the background for the implementation of a real-time correction system using a fuzzy micro-controller chip.