Failure-Detecting Method Using Fusion of Sensor Information and Visual Knowledge
Kazuo Yamaba* and Yoichi Miyake**
*Mechanical Engineering Laboratory, AIST 1-2 Namiki, Tsukuba, Ibaraki, 305 Japan
**Faculty of Engineering, Chiba University 1-33, Yayoi-cho, Inage-ku, Chiba, 263 Japan
This paper describes a failure-detecting method for thin drills which are often used in NC machine tools and other machining equipment. It is very difficult to accurately detect a failure in a thin drill with less than 2mm in diameter by means of an acoustic emission sensor. A transistor chopper circuit was developed, having a very effective, smoothing reactor to control a DC motor at a constant torque. In this chopper circuit, high-speed switching transistors are used and the current of the DC motor is always saturated perfectly. Thus, the torque at a point of failure can easily be detected even though the value is very small. An experiment for detecting the failure torque is performed on thin drills which have diameters of 1, 1.5, and 2mm. In this paper, a color information processing signal is used to seek for the surface properties of four different kinds of materials and a fusion signal is generated before each act of drilling. On the basis of the experimental results on the metals, it has been proved that the failure detection method can automatically be applicable to the thinnest drill which is 1mm in diameter.