Drilling State Recognition Based On Source Signal Enhancement Processing

Analyzing drilling process state sensor signal characteristics is conducive to unearthing drilling mechanism, to protecting and improving the quality of drilling. The source signal acquisition target is usually subjected to varying degrees of interference of ambient noise. Therefore, how to extract the source signal characteristics is very important. In this dissertation, according to the key issues must be addressed in research process, we present a detailed study on the aspects of drilling monitor platform set-up, signal enhancement processing, signal generation mechanism, drilling a transient state of the source signal characteristics and so on. So that the real-time monitoring of drilling state recognition can be realized.(1)The experimental design and data analysis of drilling monitor. Constructed by the acceleration sensors, acoustic emission sensors and related equipment to monitor test drilling platform. The experimental data obtained monitoring signal drilling, drilling and tool images. Feasibility and noise interference experiments to monitor signals conducted a preliminary analysis.(2)The application of wavelet spectral subtraction on drilling source signal enhancement. Since the processing machine and the ambient noise, causing the vibration characteristics of the source signal is closely related with the state of the drilling can’t be accurately identified. Based on the basic principles of classical spectral subtraction algorithm, combined with drilling signal frequency characteristics, we propose a new wavelet spectral subtraction algorithm. Obtained drilling vibration source signals by this method. It provides a more accurate and clear experimental data.(3)The study of classification and relationships between the drilling state and enhanced transient source signal characteristics. By analyzing the drilling mechanism, combined with the drilling process vibration and acoustic emission source signal mechanism. Theoretically typical drilling state and the corresponding source signal characteristics to classify recognition. Under the guidance of theory, research and enhancement of the drilling state after the mapping between the source signal characteristics between the instantaneous mutation. Get the cutting slip surface scratches, chips broken down the drilling tool breakage and other typical source signals corresponding to the state of transient characteristics.In this dissertation, proposed source signal enhancement method of wavelet spectral subtraction, effectively enhance the source signal and the drilling process is closely related to drilling. On this basis, we obtain a mapping between the common drilling state with the source signal transients between features. Has laid a good foundation for online monitoring Recognition drilling state, also for the single-channel high-frequency sources like signal enhancement technology provides an effective method.