Diagnosis of the Tapping Process by Information Measure and Probability Voting Approach

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Abstract
A new method for the diagnosis of the tapping process using the information measure and multiple probability voting scheme is proposed. Considering the features of short cutting-duration and the large uncertainties existing in a tapping process, a set of indices based on the time-domain statistical analysis has been formed. These indices have then been evaluated and ranked using an algorithm that calculates the information gain of each index about the tapping process. The final classification decision can be made by a voting scheme based on the conditional probability functions for multiple indices. Furthermore, the information gains estimated in the index evolution process can be used as a weighting function during voting to improve efficiency and reliability. From a tapping test, which includes five different tapping conditions, a success rate of 95 percent has been achieved.

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