In the mining industry, most of the underground injuries and fatalities are due to rock falls (i.e., fall of hanging wall/roof). The method that has been used for many years in the mines when...



In the mining industry, most of the underground injuries and fatalities are due to rock falls (i.e., fall of hanging wall/roof). The method that has been used for many years in the mines when determining the integrity of the hanging wall is to tap the hanging wall with a sounding bar and listen to the sound emitted. An experienced miner can differentiate an intact/solid hanging wall from a detached/ loose hanging wall by the sound that is emitted. This method is subjective. The Council for Scientific and Industrial Research (CSIR) in South Africa has developed a device that assists any miner in making an objective decision when determining the integrity of the hanging wall. A trained neural network model is embedded into the device. The device then records the sound emitted when a hanging wall is tapped.


The sound is then preprocessed before being input into a trained neural network model, and the trained model classifies the hanging wall as either intact or detached. Mr. Teboho Nyareli, working as a research engineer at CSIR, who holds a master’s degree in electronic engineering from the University of Cape Town in South Africa, used NeuroSolutions, a popular artificial neural network modeling software developed by NeuroDimensions, Inc., to develop the classification type prediction models. The multilayer per ceptron-type ANN architecture that he built achieved better than 70 percent prediction accuracy on the hold-out sample. Currently, the prototype system is undergoing a final set of tests before deploying it as a decision aid, followed by the commercialization phase. The following figure shows a snapshot of Neuro Solution’s model building platform.


1. How did neural networks help save lives in the mining industry?


2. What were the challenges, the proposed solution, and the obtained results?

Dec 09, 2021
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