Papers by Keyword: Power Spectrum Analysis

Abstract: In this paper, cutting force and its power spectrum analysis at different tool wear levels are explored. A dynamic model is established to simulate the measured cutting force compositions, and a series of cutting experiments have been conducted to investigate the cutting force evolution with the tool wear progress. Research results reveal that in the time domain, the cutting force in UPRM is characterized as a force pulse follows by a damped vibration signals, the vibration can be modeled by a second order impulse response of the measurement system. While in the frequency domain, it is found that the power spectrum density at the natural frequency of dynamometer increases with the progress of tool wear, which therefore can be utilized to monitor diamond tool wear in UPRM.

Abstract: Power spectrum analysis can make EEG which the amplitude changes with time transformation for spectrum chart which the EEG power changes with time. From the spectrum chart the distribution of the α-wave, the θ-wave, the δ-wave and the β-wave, and the change of rhythm can be observed directly. On this study, the 1/f wave had been applied on the treatment of patients with mental disease , the analysis and the research of EEG before and after the 1/f wave electrical stimulation. The results show that, the 1/f wave electric stimulation has a significant effect for mental disease patients which were caused by structural damage.

Abstract: According to the characteristics of the rolling bearing fault, we make the research on fault diagnosis. Time domain signal can not perform the fault feature information well. The power spectrum changes the time domain signals into the frequency signals. It sets up the new data model. It uses the principal component analysis on fault diagnosis. It uses T square statistics and Q statistics methods to make fault diagnosis. Simulation experiment results demonstrate that this method provides a high recognition rate.

Abstract: This paper presents a study of effect of cutting conditions on surface quality in FTS machining of optical microstructures such as micro-lens array. A power spectrum analysis is proposed to characterize the surface quality in FTS machining. It is found that there is a strong relationship between the surface roughness and the power spectrum of the surface profile. This provides an important means for the characterization of surface quality in FTS machining of optical microstructures.