Pressure fluctuations contribute to the instability of separation process in air dense medium fluidized bed, which provides a high motivation for further study of underlying mechanisms. Reasons for generation and prop...Pressure fluctuations contribute to the instability of separation process in air dense medium fluidized bed, which provides a high motivation for further study of underlying mechanisms. Reasons for generation and propagation of pressure fluctuations in the air dense medium fluidized bed have been discussed.Drift rate and collision rate of particles were employed to deduce the correlation between voidage and pressure fluctuations. Simultaneously, a dynamic pressure fluctuation measuring and analysis system was established. Based on frequency domain analysis and wavelet analysis, collected signals were disassembled and analyzed. Results show gradually intensive motion of particles increases magnitudes of signal components with lower frequencies. As a result of violent particle motion, the magnitude of real pressure signal's frequency experienced an increase as air velocity increased moderately. Wavelet analysis keeps edge features of the real signal and eliminates the noise efficaciously. The frequency of denoised signal is closed to that of pressure signal identified in frequency domain analysis.展开更多
Classification systems such as Slope Mass Rating(SMR) are currently being used to undertake slope stability analysis. In SMR classification system, data is allocated to certain classes based on linguistic and experien...Classification systems such as Slope Mass Rating(SMR) are currently being used to undertake slope stability analysis. In SMR classification system, data is allocated to certain classes based on linguistic and experience-based criteria. In order to eliminate linguistic criteria resulted from experience-based judgments and account for uncertainties in determining class boundaries developed by SMR system,the system classification results were corrected using two clustering algorithms, namely K-means and fuzzy c-means(FCM), for the ratings obtained via continuous and discrete functions. By applying clustering algorithms in SMR classification system, no in-advance experience-based judgment was made on the number of extracted classes in this system, and it was only after all steps of the clustering algorithms were accomplished that new classification scheme was proposed for SMR system under different failure modes based on the ratings obtained via continuous and discrete functions. The results of this study showed that, engineers can achieve more reliable and objective evaluations over slope stability by using SMR system based on the ratings calculated via continuous and discrete functions.展开更多
基金support by the Natural Science Foundation of Jiangsu Province of China (No. BK20160266)the National Natural Science Foundation of China (Nos. 51704287 and U1508210)the Priority Academic Program Development of Jiangsu Higher Education Institutions of China
文摘Pressure fluctuations contribute to the instability of separation process in air dense medium fluidized bed, which provides a high motivation for further study of underlying mechanisms. Reasons for generation and propagation of pressure fluctuations in the air dense medium fluidized bed have been discussed.Drift rate and collision rate of particles were employed to deduce the correlation between voidage and pressure fluctuations. Simultaneously, a dynamic pressure fluctuation measuring and analysis system was established. Based on frequency domain analysis and wavelet analysis, collected signals were disassembled and analyzed. Results show gradually intensive motion of particles increases magnitudes of signal components with lower frequencies. As a result of violent particle motion, the magnitude of real pressure signal's frequency experienced an increase as air velocity increased moderately. Wavelet analysis keeps edge features of the real signal and eliminates the noise efficaciously. The frequency of denoised signal is closed to that of pressure signal identified in frequency domain analysis.
文摘Classification systems such as Slope Mass Rating(SMR) are currently being used to undertake slope stability analysis. In SMR classification system, data is allocated to certain classes based on linguistic and experience-based criteria. In order to eliminate linguistic criteria resulted from experience-based judgments and account for uncertainties in determining class boundaries developed by SMR system,the system classification results were corrected using two clustering algorithms, namely K-means and fuzzy c-means(FCM), for the ratings obtained via continuous and discrete functions. By applying clustering algorithms in SMR classification system, no in-advance experience-based judgment was made on the number of extracted classes in this system, and it was only after all steps of the clustering algorithms were accomplished that new classification scheme was proposed for SMR system under different failure modes based on the ratings obtained via continuous and discrete functions. The results of this study showed that, engineers can achieve more reliable and objective evaluations over slope stability by using SMR system based on the ratings calculated via continuous and discrete functions.
