Current fault diagnosis methods for rotor-bearing system are mostly based on analyzing the vibration signals collected at steady rotating speeds. In those methods, the data collected under one operating condition cannot be accurately used for diagnosis under a different condition. Moreover, in vibration monitoring, installing the necessary sensors will affect the equipment structure and hence the vibration response itself. The present paper proposes a new method based on two-stage parameter transfer and infrared thermal images for fault diagnosis of rotor-bearing system under variable rotating speeds. The method of parameter transfer enables the use of data (or parameters) acquired under one operating condition (called the source domain) to be extended for use in a different operating condition (called the target domain). First, scaled exponential linear unit (SELU) and modified stochastic gradient descent (MSGD) are used to construct an enhanced convolutional neural network (ECNN). Second, a stacked convolutional auto-encoder (CAE) trained based on unlabeled source-domain thermal images is employed to initialize a source-domain ECNN. Third, model parameters from the pre-trained source-domain ECNN are transferred to the target-domain ECNN to adapt to the characteristics of the target domain. The collected thermal images for a rotor-bearing system under variable speeds are used to test the transfer diagnosis performance of the proposed method. The experimental results demonstrate the performance improvement and the advantages of the proposed method.
The rotor systems of an aero engine will endure additional centrifugal force and gyroscopic moment during maneuver flight. A maneuver fly mechanical simu lator is designed and experimental investigations on dy namics of squeeze film damper (SFD) under the different additional centrifugal force and gyroscopic moment are carried out. The results show that the maneuver flight weaken effectiveness of the SFD, the additional centrif ugal force and gyroscopic moment caused by maneuver flight will change film damping, film stiffness. And the influence of maneuver flight can be effective relieved by increasing the film clearance.
The nonlinear integral resonant controller (NIRC) is implemented and analyzed to control the vibration of a viscoelastic isolation system under harmonic excitation. The NIRC consists of a first-order resonant integrator, which provides additional damping in the closed-loop system to reduce the high-amplitude vibration near the resonance frequency. The method of multiple scales is applied to analytically find the relationship of the amplitude–frequency response of the viscoelastic isolation system. Besides, the equation of the backbone curve satisfied is derived. Meanwhile, the suppression performance is verified based on time-domain analysis. It is found that the NIRC can effectively suppress vibration and improve stability of the viscoelastic isolation system. Furthermore, the influence of the detuning parameters, the real-power exponent, the viscoelastic damping, and the external excitation amplitude on the stability regions is investigated. Overall, the vibration reduction mechanism of the NIRC on the viscoelastic isolation system is revealed.
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