Automatic pattern identification of rock moisture based on the Staff-RF model

作者：Zheng, Wei^*; Tao, Kai; Jiang, Wei

来源：Journal of Geophysics and Engineering, 2018, 15(2): 438-448.

DOI：10.1088/1742-2140/aa949f

• rock moisture
• acoustic emission
• pattern identification
• staff-RF model

Studies on the moisture and damage state of rocks generally focus on the qualitative description and mechanical information of rocks. This method is not applicable to the real-time safety monitoring of rock mass. In this study, a musical staff computing model is used to quantify the acoustic emission signals of rocks with different moisture patterns. Then, the random forest (RF) method is adopted to form the staff-RF model for the real-time pattern identification of rock moisture. The entire process requires only the computing information of the AE signal and does not require the mechanical conditions of rocks.

• 出版日期2018-4
• 单位重庆大学