Acoustic emission monitoring to optimize the end-of-cast in blast furnaces

When tapping a blast furnace, break-through of gas through the taphole at end cast needs to be prevented, both preserve healthy state and prevent dust from escaping into environment. In this paper, two acoustic techniques are presented that can used emissions cast. The first approach is by using spectral analysis recorded data, second uses neural network recognize popping sounds announce slag–gas interface approaching level. It was found with methods detected about 4–2 min before ended.