Yang Yongmin

Blade damage prognosis based on kernel principal component analysis and grey model using subsampled tip-timing signals:

Damage prognosis of high-speed blades is very important for industrial turbomachinery. Nowadays, vibration monitoring using blade tip-timing methods is becoming promising. However, its main drawback is blade tip-timing signals are subsampled. Very few works have been done on damage prognosis using subsampled blade tip-timing signals. This paper investigates a novel method of blade damage prognosis based on kernel principal component analysis and grey model. Firstly, a nonaliasing reconstruction algorithm of subsampled blade tip-timing signals is proposed based on the Shannon theorem and wavelet packet transform. Secondly, kernel principal component analysis is done on the damage feature space and a damage index is defined by Mahalanobis distance. Then a grey model (1) model is proposed for damage prognosis. In the end, an experimental setup is built and a long time testing is done for collecting samples. The experimental results validate the superiority of the proposed method.

Modeling and Simulation of Complex Maintenance System Dynamics

Equipment maintenance system is naturally a complex dynamical system. The effective maintenance management must be based on the knowledge of the systems intrinsic dynamics. This paper analyzes the basic structure and elements of maintenance system for complex multi-components equipment. The maintenance system is considered as a dynamic system whose behavior is influenced by its structures feedback and interaction, and available resources. Building the dynamical model with Simulink, we show some results about the maintenance systems nonlinear dynamics, which are never given by stochastic process methods. The model can be used for understanding and determining maintenance system behaviors, towards which operational adjustments of maintenance infrastructure, precise prediction of maintenance requirements and timely supply of maintenance resources can be made in a more informed way.

Wireless Embedded Signals Acquisition for Mechanical Systems

Vibration signal analysis is one of the most effective ways to monitor mechanical systems. Traditional ways are usually to mount additional sensors on the mechanical components; however, those ways have two unavoidable defects: Firstly, sampled vibration signals are susceptible to other useless signals from nearby components or surroundings and the signal-to-noise ratio is often low; Secondly, it may be not allowed to mount additional sensors or wires in some places. In this paper, one way of embedded vibration signals acquisition wirelessly is studied. Firstly, finite element model method is used to analyze and modified mechanical structures. Then micro-sensor module of vibration is designed considering two key factors: lower power consumption and small size. In the end, the proposed method is testified on one bearing and the results demonstrate that it is more effective to obtain useful fault signals than traditional methods.

Observability for coordinate transformation on parameter states of nonlinear systems

Coordinate transformation is an important approach for filter improvement. As nonlinear coordinate transformation cannot naturally ensure the observability of the objective system, this article studies the question of observability insurance of coordinate transformation. A theorem of the sufficient condition for coordinate transformation is proved for the cases when the parameters to be identified are nearly invariable. A case study demonstrated the correctness of the theorem.

Improvement of bispectrum estimation based on one new 2-D combined lag window

Higher-order spectrum (HOS) has been used as a strong tool for non-Gaussian and nonlinear signal processing in many fields and bispectrum is usually employed. Using windows is one important way to improve bispectrum estimation and appropriate window function can reduce the variance and suppress noise, but sidelodes in spectrum of window functions result in spectrum leak. Thus it is one urgent problem needed to be solved for application of bispectrum that how to find one appropriate 2-D window. In this paper one new 2-D combined lag window is constructed by Hanning-Poisson window without sidelobes, which then is used for non-parametric bispectrum estimation instead of rectangle window. In the end simulation is done on QPC signals encountered in fault diagnosis of rotating machinery. The results demonstrate that using the constructed window function can restrain spectrum leak and reduce the variance of estimation better than single windows, like rectangle window.