Application of Data Trend Fusion Analysis Method in Rock Failure Identification and Early Warning
Accurate identification of rock failure is of great significance to ensure the safety of mine production.For this reason,the trend fusion analysis method of binary was proposed for rock failure identification and early warning.In this method,the single trend index parameter Ti of different data elements was formed into quadrant coordinate points,and the fusion trend index C_Ti value of coordinate points was calculated.The combination of multiple indicators such as the numerical magnitude of the trend indicator,the continuity and the trend rate of change R were analyzed to discriminate the rock rupture stage.For the three kinds of accompanying information of rock damage,such as stress,displacement and acoustic emission,the trend fusion early warning mode of quadrant coordinate binary data was constructed,including displacement-stress data trend fusion,acoustic emission-stress data trend fusion and displacement-acoustic emission data trend fusion warning model respectively.By using the trend fusion early warning method to establish the standard of warning level,and classify the danger level into four signal categories,namely,danger,more danger,safer and safety,the accurate identification and grading warning of the rock can be realized.The binary date trend fusion analysis method was also validated using laboratory test data and field monitoring data,respectively.The research shows that the binary date trend fusion analysis method can accurately identify the fracture stage of different lithology rocks in laboratory tests.When the method is applied to the analysis of field monitoring data,the distribution of the warning results in the quadrant coordinates has obvious characteristics,and the warning danger signals are located in the fourth quadrant.The field verification shows that the early warning results of the method are highly consistent with the actual geopressure activities,realizing the multi-level hazard warning without threshold by the trend fusion of binary data.
rock failurebinary datatrend indicatorfusion analysisearly warning identificationrupture stage
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