The production of advanced manufacturing technology (AMT) is the inevitable result of the development of human history and the progress of civilization. It integrates the achievements of modern science and Technology and industrial innovation. One of the key technologies to achieve this goal is the real-time monitoring of machining process. As the direct executor of cutting process, the tool condition monitoring is an important part of this technology.

The phenomenon of tool wear and even breakage is inevitable in metal cutting process, the time of tool change is usually judged by the sound of cutting, the color of the tool surface or the change of chip state. However, this judgment is based on subjective experience, it affects the surface quality and dimensional precision of the tool, and even causes the damage of the workpiece and the malfunction of the machine tool, resulting in higher production costs and lower production efficiency. According to statistics, about 20% of machine tool downtime is caused by tool breakage, and the cost of tool ability and tool replacement accounted for 3% -12% of the total cost of the product.

In view of the above-mentioned problems, the tool state monitoring technology has been paid attention to and studied by people. It usually uses the sensor information collected in the cutting process to monitor the tool state, and then predict the time needed to change the tool. The results show that the tool monitoring system can reduce the downtime by 75% , increase the productivity by 10% ~ 60% , and increase the utilization rate by more than 50% .

The principle of tool breakage detection is to monitor the tool wear by analyzing the acoustic emission signal produced in the cutting process. The principle is that the material will send out a medium fracture wave during cutting, which is not only related to the nature of the workpiece material, but also closely related to the tool wear state in its frequency range and amplitude. The technique has the advantages of high sensitivity and fast response.