Tool Breakage Monitoring System Of Research And Development

As the coming of Flexible Manufacturing System (FMS) technology, the supervision of the tool's state within the on-line monitoring of the machining process makes the key part of FMS. Once the breakage of the tool happened, it would suffer different losses even cause serious losses, therefore total economic benefits of FMS is degraded. Consequently, it is necessary to monitoring the tool's state on realtime.The study of the tool monitoring technology is mainly devided into two parts. The first is the extraction method of signal and the second is signal process which means how to pick-up characteristic parameter for judging the tool state. Among the two parts the last from the low Signal-to-Noise(SNR) signal which means denoise and algorithm for extraction characteristic parameter is the key technology.Cutting force is selected to serve as monitoring foundation in this research, and the problem on collecting sensitive signals, signal transformation, data collecting, signal denoising, feature extraction is systematically studied. This paper presents wireless transmission to solve the limit of wire transmission and also extend the adaptability of collection. Simultaneously, aiming at unsteady feature of state signal of cutting tool and noise interference causing difficulty to feature extraction and state recognition, combining the good efficiency and flexible of LabVIEWF's graphical interfaces programme ability and the convenience of data collection with powerful numerical analysis algorithm of MATLAB, designing a MCU data collection as a lower and the upper virtual instrument which based MATLAB's the kernel algorithm to denoising , extraction characteristic parameter. By dint of a wavelet transform function to signal denoising, furthermore to judge the oddity of the signal and make a forecast for dynamic transformation trend of the signal. Simulation results shows that cutting tool state monitoring based on wavelet has the advantage of strong resistance to interference, high recognition accuracy, good reliability.