Huageng Luo

Dynamic Characteristics of Shape Memory Alloy Metal Mesh Dampers

*† ‡ The study presented in this paper involved characterizing the amplitude and frequency dependent stiffness and damping coefficients for oil-free metal mesh dampers weaved from several different types of materials. The material test matrix consisted of stainless steel 304, Inconel 600, copper, and nickel-titanium (NiTi) shape memory alloy. The research specifically focuses on NiTi alloy damper and how the stiffness and damping performance compares with the other metal mesh damper materials. Steady state forced vibration and transient vibration tests were used to characterize the stiffness and damping as functions of frequency and vibration amplitude. The results show that vibration amplitude has the opposite influence on the NiTi material damping when compared to the other materials, whereas the influence of vibration amplitude on NiTi stiffness was the same as the other materials. While the conventional metal samples give decreasing damping as vibration amplitude increases, the NiTi samples generated increasing damping as vibration levels increased. In addition to comparisons of stiffness and damping between different materials with the same mesh density, a lower mesh density for NiTi was tested and compared to the higher mesh density damper.

Investigation of Granular Damping in Transient Vibrations Using Hilbert Transform Based Technique

Granular damping results from a combination of energy dissipation mechanisms including the impact and the friction between the vibrating structure and granules and among the granules. Although simple in concept, granular damping is very complicated and its performance depends on a number of factors, such as vibration level, granular material properties, packing ratio, etc. In this study, free vibration experiments are conducted on a cantilevered beam incorporated with granular damping. A signal analysis approach based on the Hilbert transform (HT) is then employed to identify the nonlinear damping characteristics from the acquired responses, such as the dependency of the natural frequency and damping ratio on the vibration level. This HT based analysis can produce an effective temporal-frequency amplitude/energy analysis, which provides us with physical insights of the nonlinear transient response. A direct comparison between the granular damping and the impact damping (with single impactor to dissipate vibratory energy) is performed to highlight the difference between these two and the advantages of granular damping. Finally, the validity of the proposed approach is also examined by the successful prediction of vibration response using the extracted granular damping characteristics.

Characterization of Granular Damper Using Hilbert Transform and Free Vibration Response

(Abstract) In this study, we developed and implemented a Hilbert transform based procedure for nonlinear parameter identification of granular damper from experimentally obtained free response data. The fundamentals of the Hilbert transform based identification technique are described first. Then we consider an example of cantilever beam with a granular damper attached to the tip of the free end. The response data were collected by exciting the system with an initial tip displacement. While the beam has an infinite number of degrees-of-freedom, it is convenient to investigate the effect of granular damping on each mode of interest separately. In addition, experimental data inevitably contain noise. To remove the noise and the undesirable modal responses, the wavelet transform technique is applied to the experimental data. Then Hilbert transform based identification is applied to de-noise the modal response. With this method, the vibration amplitude dependent characteristics of granular damper, such as the equivalent damping and frequency, can be successfully identified, which provides new insight to granular damping mechanisms.

An Off-Resonance Synchronous Vibration Based Method for Rotor System Damage Detections

This paper presents a methodology of detecting rotor imbalances, such as mass imbalance and crack-induced imbalance, using shaft synchronous vibrations. A vibration detection algorithm is derived based on the first order nonresonant synchronous vibration response. A detection system is integrated by using state-of-the-art commercial analysis equipment. A laboratory rotor test rig with controlled mass imbalances was used to verify the integrated system. The system is then deployed to an engine sub-assembly test setup. Four specimens were used in the subassembly test and the test results are reported in the final section.Copyright

A Method for Enclosed Rotating System Multiple-Plane Equivalent Imbalance Detection

In this paper, we present an approximation procedure for identifying lumped mass imbalances at multiple locations without accessing to the shaft 1/rev signal. As a first step, an experimental or analytical procedure is applied to optimize the sensor locations, such that a transmissibility matrix with minor off-diagonal terms can be established. Transfer functions between the mass imbalance correction planes and the vibration sensor locations are established by rotordynamics analytical modeling, finite element methods, or experimental testing through a specially designed unit with access to the 1/rev signal. Then, the synchronous responses of the system are obtained by peak-hold average spectrum or waterfall measurement and post-processing to get the synchronous vibration amplitudes as a function of the running speed. For multiple-plane imbalance detection without access to the rotor 1/rev signal, it is mathematically underdetermined to obtain both the amplitude and the phase of the imbalance. A unique estimation method is developed to extract the lumped mass imbalances from the recorded data. Numerical simulations results are reported in the end.Copyright

Analysis of Granular Damping Using Hilbert Transform Based Technique

Granular damping results from a combination of energy dissipation mechanisms including the impact and the friction between the vibrating structure and granules and among the granules. Although simple in concept, granular damping is very complicated and its performance depends on a number of factors, such as vibration level, granular material properties, and packing ratio, etc. In this study, free vibration tests are conducted on a cantilevered beam incorporated with granular damping. A signal analysis approach based on the Hilbert transform (HT) is then employed to identify the nonlinear damping characteristics from the acquired responses, such as the dependency of the natural frequency and damping ratio on vibration level. This HT based analysis can produce an accurate temporal-frequency amplitude/energy analysis which provides us with physical insights of the nonlinear transient response. A direct comparison between the granular damping and the impact damping (with single impactor to dissipate vibratory energy) is performed to highlight the difference between these two as well as the advantages of granular damping. Finally, validity of the proposed approach is also examined by the successful prediction of vibration response using the extracted granular damping characteristics.Copyright

A Resonant Synchronous Vibration Based Approach for Rotor Imbalance Detection

This paper presents a methodology of detecting rotor imbalances, such as mass imbalance and crack-induced imbalance, using shaft synchronous vibrations. An iterative scheme is developed to identify parameters from measured synchronous vibration data. A detection system is integrated by using state-of-the-art commercial analysis equipment. A laboratory rotor test rig is used to verify the system integration and algorithm validation. A real engine test has been carried out and the results are reported.

Learning Rate Effect in Neural Network for Damage Detection

Neural network is a powerful tool that can be utilized for structural damage detection and health monitoring. Since damage usually varies/reduces stiffness, frequency response variation can be used as indicator for damage occurrence. A well designed neural network can correlate frequency response variation to damage localization/severity without resorting to detailed structural modeling. While various neural network based approaches have been developed, their effectiveness, efficiency, and robustness oftentimes rely on the selection of several important parameters in the network construction. One of the key performance metrics for a neural network is the learning rate. Although the dynamic steepest descent algorithm (DSD) and fuzzy steepest descent algorithm (FSD) have shown promising possibility of improving the learning convergence speed significantly without increasing the computational effort, its performance still depends on the selection of control parameters and control strategy. In this paper, a tunable steepest descent algorithm (TSD) improving the performance of the dynamic steepest descent algorithm is proposed. A numerical benchmark example shows that the proposed algorithm significantly improves the convergence rates of the backpropagation algorithm. A structural health monitoring system incorporated with the neural network trained by the adaptive learning algorithm is developed for detecting the impact damage.Copyright