Fangyi Wan

Vibration analysis of cracked rotor sliding bearing system with rotor–stator rubbing by harmonic wavelet transform

Abstract In this paper, the vibration of a cracked rotor sliding bearing system with rotor–stator rubbing is investigated using harmonic wavelet transform (HWT). Three non-linear factors, non-linear oil film forces, rotor–stator rubbing and the presence of crack, are taken into account. So the non-linear behavior of the rotor will be much more complex. According to Newmark method, the dynamic response of the rotor is calculated. Using HWT method, the effect of these non-linear factors is analyzed simultaneously in both time and frequency domain. The numerical simulated result shows that HWT will be available to analyze this multi-non-linear factors rotor effectively and can reveal the exact fault characteristics in detail.

Application of Prognostic and Health Management technology on aircraft fuel system

Prognostic and Health Management (PHM), which could provide the ability of fault detection (FD), fault isolation (FI) and estimation of remaining useful life (RUL), has been applied to detect and diagnose device faults and assess its health status, with aiming to enhance device reliability, safety, and reduce its maintenance costs. In this paper, taking an aircraft fuel System as an example, with virtual instrument technology and computer simulation technology, an integrated approach of signal processing method and model-based method is introduced to build the virtual simulation software of aircraft fuel PHM system for overcoming the difficulty in obtaining the failures information from the real fuel system. During the process of constructing the aircraft fuel PHM system, the first step is to analyze the fuel system failure modes and status parameters that can identify the failure modes. The main failure modes are determined as joints looseness, pipe broken, nozzle clogging, and fuel tank leakage. The status parameters are fuel pressure and fuel flow. Then, the status parameter model is constructed to imitate the behavior of sensor which detecting fuel system status. On this basis, utilizing the signal processing module provided by Labview software, the outputs from the virtual sensors, which collect the failure data, are processed to realize the simulation of failure detection and failure diagnosis. All the result shows that the virtual simulation software well accomplishes the task of the aircraft fuel system failure detection and diagnosis.

Research of structural health monitoring based on mode analysis for UAV wings

Unmanned Aerial Vehicle ( UAV ) structures are prone to damage during their service lives, caused by abominable environment factors. Its structural health monitoring can be effective in reducing maintenance costs and increasing service life to ensure safe and reliable operation.

Damage location and identification of the wing structure with Probabilistic Neural Networks

The subject of Structural Health Monitoring (SHM) is emerging as an area of interest for aerospace, mechanical and automotive industry. It is defined as a system with the ability to continuously and automatically monitor the physical states of a structure and outer environment by means of embedded or attached sensors. Then, the SHM system can interpret adverse changes caused by the structure damage with the intention of improving the structures reliability and reducing the maintenance cost. Therefore, the key of implementation of SHM is that SHM system knows what changes in the structure to look for and how to identify them. Usually, the process of the damage identification is to detect the damage, extract the features which can accurately represent the characteristic of the damage, and identify the damage. Although, there has been an amount of work performed in the area of SHM, most efforts are focusing on civil structures and the technology level has reached some modest degree of maturing. For the particular structures like the aircraft structure, due to its special characteristics, there will be a lot of problems needed for analysis. In this paper, taking the aircraft wing structure as an example, its finite element model has been constructed to simulate the fifteen damage patterns according to the actual mechanical properties of the wing structure. Combined with the dissymmetry of the geometry characteristic of the wing structure, the change of the natural frequency is extracted as the feature parameter. Then, the damage feature vector based on the feature parameters is constructed as the input vector of the Probabilistic Neural Network (PNN). Finally, taking σ =0.1, 0.05, 0.01 and 0.001 respectively, the PNN is trained with the damage training samples, and the ability of damage identification of the PNN is vivificated by the verification samples. The results of the PNN training and verification show that the damages of the upper and lower skin at the front spar are hard to distinguish correctly. In order to recognize them correctly, the PNN must increase other feature parameters which are more sensitive to the damages at the two locations. Anyway, the method of PNN has great identification effect for the wing structure, and it can be applied to the aircraft structure health monitoring.

Numerical and Experimental Studies on Nonlinear Dynamic Behaviors of a Rotor-Fluid Film Bearing System With Squeeze Film Dampers

In this paper, the nonlinear oil film forces of bearings and dampers with free boundary conditions are determined by the finite element method (FEM) and the complementary solution for variational inequalities. The mode synthesis technique is used to reduce the linear degrees of the high order finite element model. The periodic solution of the system and its stability are determined by the Poincare mapping method and the Floquet theory, respectively. The results of experiment show that squeeze film dampers (SFDs) can effectively prevent subsynchronous and nonsynchronous vibrations and some structural parameters have significant effects on the dynamic behaviors of the system. Comparing the numerical results with those of experiment, it is shown that the above theories and schemes are feasible and efficient in analyzing nonlinear behaviors of the high-order dynamic system with local nonlinearities.

Real-time monitoring for the actuator mechanism of the aileron

Structural Health Monitoring (SHM) provides a comprehensive assessment of structural state and damage based on monitoring structural parameters. It has definite practical significance in extending the service life of the structure, reducing the maintenance cost and improving the safety and reliability of the structure. In recent years, there were many aircraft faults founded in the aileron control mechanism, which not only affect the success of flight mission, but also seriously impact on aircraft safety. So it would be useful to improve the aircrafts flight performance and guarantee flight safety by analyzing and preventing the faults in the aileron control mechanism. The dynamic responses of the aileron control mechanism could reveal its internal relations between the faults and the external loads. Comparing the different dynamics responses of the normal mechanism (without faults) and the abnormal one (with faults), the probable faults and its characteristics could be extracted. Then prevention and faults diagnosis would be carried. Taking an actuator mechanism of aileron as example, its rigid-flexible coupling dynamic model was constructed to obtain its dynamic responses with natural excitation.

Research on Optimal Sensor Placement for Aircraft Structural Health Management

Prognostic and Health Management (PHM) systems can manage health conditions of airplane real-time. As crucial subsystem of PHM, Aircraft Structural Health Management (ASHM) mainly focus on structural health monitoring and assessment, microstructure fault monitoring and isolation, overload, corrosion monitoring, residual life assessment and so on. It is overwhelmingly difficult for large aircraft structure to optimize sensor placement in ASHM on account of diversity of failure modes, hiddenness of fault position, incalculability of corrosion failure. Especially, corrosion detection, this is an intractable problem because corrosion degree is gradually accumulated with time. However, the Optimal Sensor Placement (OSP) is a vital aspect and plays a crucial role in data acquisition and data identification for the ASHM. Thus, thousands of sensors are installed for aircraft structure. Besides, failure models such as accidental damages, fatigue damages and corrosion, are often synergistic and interactive. Therefore, the OSP must be enough underlined for ASHM. In this paper, the OSP of aircraft wing structure had been discussed. Firstly, the test matrix was gained through modal test and the finite element model of wing structure was built by ANSYS. Secondly, sensor measuring points were optimized by the Singular Value Decomposition (SVD), the QR decomposition and the Fuzzy Measurement Coverage. Adopting singular value difference method and system fixed order method based on singular entropy had coped with sensor placement. The final result of the OSP had been verified by the QR decomposition and the Fuzzy Measurement Coverage. Finally, the scheme of OSP had been analyzed for aircraft wing structure. For the demand of the safety and reliability, at least 92 measuring points should be monitored for wing structure. Through analysis, about 18 measuring points could meet the demand for a wing. The final scenario of the OSP is that the strain of 10 measuring points and longitudinal and horizontal strain of eight wing-body joints are monitored. Numerous measuring points have been simplified and the effective information and data we need can be acquired for the wing.

Complete synchronization of the global coupled dynamical network induced by Poisson noises

The different Poisson noise-induced complete synchronization of the global coupled dynamical network is investigated. Based on the stability theory of stochastic differential equations driven by Poisson process, we can prove that Poisson noises can induce synchronization and sufficient conditions are established to achieve complete synchronization with probability 1. Furthermore, numerical examples are provided to show the agreement between theoretical and numerical analysis.

Failure simulation and identification of shock absorber in carrier-based aircraft landing gear

The gas-oil leakage in the shock absorber of carrier-based aircraft landing gear is a frequent and common failure, which can deteriorate the absorbing performance. However rarely research is done to quantitatively analysis the coupling effect of gas-oil leakage on the absorbing performance. In this paper, the failure simulation and identification of shock absorber is studied by numerical modeling and simulation experiment. To analyze the effect of gas-oil leakage on the shock absorber, the equivalent air spring stiffness is deduced. And Kringing model is introduced to surrogate gas-oil leakage to further present the relation of corresponding shock absorber time to residual gas quantity and oil volume. Then an efficient method is proposed to identify the failure of gas-oil leakage. The simulation experiment is designed to verify the theory presented in this paper. The result of numerical model explains that the gas cushioning property is influenced by both gas and oil property. The simulation model is used to obtain the coupling effect curve of gas-oil leakage on the absorbing time. Eventually the analytical results show that the shock absorber performance varies with different gas-oil ratio caused by gas-oil leakage.

Micromechanics modeling of skin panel with pitting corrosion for aircraft structural health monitoring

Due to the increasing requirements from Aircraft Structural Health Monitoring, it is significantly meaningful to research the impact of pitting corrosion on the mechanical property of aircraft principle structural element. In this paper, micromechanics model of pitting corrosion based on Eshelby-Mori-Tanaka approach has been constructed to analyze the effect of pitting corrosion on structural stiffness. The main aims of this study are to determine the effective stiffness of aircraft skin panel structure under various degree and shape parameter of pitting corrosion. A simple accelerating experiment reveals that aircraft structural aluminum alloy materials are vulnerable to pitting corrosion in severe conditions. The Finite Element models are built to investigate the local stress-strain distribution with three different pits (hemi-spherical, cylinder and box). The effective stiffness of the skin panel with 2024 aluminum alloy or 7075 aluminum alloy has been discussed based on micromechanics model. The results show that structural effective stiffness could significantly decrease with gradual increment of degree of pitting. The variations of structural effective stiffness are relatively bigger for deep hemi-ellipsoidal etch pit (λ>1), yet their changes are comparatively smaller for flat hemi-ellipsoidal etch pit (λ<;1). For the local strain around the corrosion pit, the strain around flat hemi-ellipsoidal etch pit (λ<;1) is comparatively bigger than deep hemi-ellipsoidal etch pit (λ>1). Moreover when value of λ is approximately 0.3726, the stiffness within etch pit is close to zero. The works presented in this paper can provide a preliminary corrosion prediction model for structural corrosion monitoring.