In the past two decades, many tool condition monitoring (TCM) methods have been developed, such as pattern recognition method, decision tree, and Artificial Neural Network (ANN). This paper introduces a new method, called the transition fuzzy probability. It begins with an introduction on the theory of transition fuzzy probability. Then, a computation procedure is given. The new method is validated using a practical TCM application in boring. Using the means of the main spindle motor current and the feed motor current, the new method achieved a success rate about 95 percent. This result is better than the compared methods. Its success may be attributed to the tact that the new method uses the available information to the maximum extent, while the existing methods use only partial information. A number of future research topics are also given.
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