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
Damping faults in a helicopter rotor hub are diagnosed by using vibration signals from the fuselage. Faults include the defective lag damper and raspings in its flap and feathering hinges. Experiments on the diagnosis...Damping faults in a helicopter rotor hub are diagnosed by using vibration signals from the fuselage. Faults include the defective lag damper and raspings in its flap and feathering hinges. Experiments on the diagnosis of three faults are carried out on a rotor test rig with the chosen fault each time. Fuselage vibration signals from specified locations are measured and analyzed by the fast Fourier transform in the frequency domain. It is demonstrated that fuselage vibration frequency spectra induced by three faults are different from each other. The probabilistic neural network （PNN） is adopted to detect three faults. Results show that it is feasible to diagnose three faults only using fuselage vibration data.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Damping faults in a helicopter rotor hub are diagnosed by using vibration signals from the fuselage. Faults include the defective lag damper and raspings in its flap and feathering hinges. Experiments on the diagnosis of three faults are carried out on a rotor test rig with the chosen fault each time. Fuselage vibration signals from specified locations are measured and analyzed by the fast Fourier transform in the frequency domain. It is demonstrated that fuselage vibration frequency spectra induced by three faults are different from each other. The probabilistic neural network （PNN） is adopted to detect three faults. Results show that it is feasible to diagnose three faults only using fuselage vibration data.
