ANALYSIS OF DFOS-BASED ASSOCIATION RULES ON MULTI-FIELDS DATA MONITORING OF SLOPE

The distribution information of multi-fields in slope can be obtained using distributed optical fiber sensing(DFOS)technology. Nevertheless, it is still a quite complicated work to analyze massive amounts of information about multiple fields relatively, and to evaluate the slope stability under multi-fields coupling effect. This paper introduces the basic principle of analysis method of association rules in data mining. It designs distributed optical fiber monitoring projects on strain field, deformation field, seepage field, temperature field, environmental parameter of slope respectively. Taking Majiagou slope of Three Gorges as an example, this paper analyzes monitoring data of different fields with the method of data mining association rules, and it finds rules on matching attribute between monitoring time and fluctuation of reservoir water level, coordination between fluctuation of reservoir water level and groundwater level of slope's leading edge. Comparing with practical monitoring data, it proves that it is effective to analyze multiple fields of slope by adopting association rules, thereby providing scientific basis for slope stability evaluation and landslide forecast warning.