Nonlinear dynamic characteristics of load time series in rock cutting

The characteristics of the cutting load time series were investigated using chaos and fractal theories to study the information and dynamic characteristics of rock cutting. The following observations were made after analyzing the power spectrum, denoising phase reconstruction, correlation dimension and maximum Lyapunov exponent of the time series. A continuous broadband without a significant dominant frequency was found in the power spectrum. The restructured phase space presented a distinct strange attractor after wavelet denoising. The correlation dimension was saturated at an embedding dimension of 7. Lastly, and the maximum Lyapunov exponent exceeded 0 via the small data method. These findings reflected the chaotic dynamic characteristics of the cutting load time series. The box dimensions of the cutting load were further investigated under different conditions, and the difference in cutting depth, cutting velocity and assisted waterjet types were found to be ineffective in changing the fractal characteristic. As cutting depth become small, rock fragment size also decreased, whereas fractal dimension increased. Moreover, a certain range of cutting velocity increased fragment size but decreased fractal dimension. Therefore, fractal dimension could be regarded as an evaluation index to assess the extent of rock fragmentation. The rock-cutting mechanism remained unchanged under different assisted waterjet types. The waterjet front cutter impacts and damages rock, however, the waterjet behind of cutter is mainly used to clean fragments and to lubricate the cutter.