Sensitivity of total charge and maximum charge per delay on ground vibration

Abstract

Frequency is among the most used properties for determining the detrimental effect of ground blasting on the surrounding areas. In this paper, an attempt has been made to calculate the frequency of the blast by developing an adaptive neuro-fuzzy inference system (ANFIS) model. Blast design and explosive parameters are incorporated in the intelligent model. The sugeno type fuzzy inference system was generated using the subtractive clustering partition method. Two separate ANFIS networks have been generated, each with five inputs (maximum charge per delay and total charge, respectively in two different cases) and one output parameter (frequency) was trained using a hybrid parameter optimization method. A set of 160 data obtained from blast monitoring at a major surface coal mine in India was used for training the network. A different set of 27 data was used for validating and testing the designed network. It has been observed that for a given distance the frequency of the vibration is affected not only by the maximum charge per delay but by total charge also. The results obtained from ANFIS were able to predict that the frequency of ground blast operation is obtained with higher precision when the maximum charge per delay is used as an input parameter instead of total charge.