RESUMEN
To extract fault features of rolling bearing vibration signals precisely, a fault diagnosis method based on parameter optimized multi-scale permutation entropy (MPE) and Gath-Geva (GG) clustering is proposed. The method can select the important parameters of MPE method adaptively, overcome the disadvantages of fixed MPE parameters and greatly improve the accuracy of fault identification. Firstly, aiming at the problem of parameter determination and considering the interaction among parameters comprehensively of MPE, taking skewness of MPE as fitness function, the time series length and embedding dimension were optimized respectively by particle swarm optimization (PSO) algorithm. Then the fault features of rolling bearing were extracted by parameter optimized MPE and the standard clustering centers is obtained with GG clustering. Finally, the samples are clustered with the Euclid nearness degree to obtain recognition rate. The validity of the parameter optimization is proved by calculating the partition coefficient and average fuzzy entropy. Compared with unoptimized MPE, the propose method has a higher fault recognition rate.
RESUMEN
Informative frequency band (IFB) selection is a challenging task in envelope analysis for the localized fault detection of rolling element bearings. In previous studies, it was often conducted with a single indicator, such as kurtosis, etc., to guide the automatic selection. However, in some cases, it is difficult for that to fully depict and balance the fault characters from impulsiveness and cyclostationarity of the repetitive transients. To solve this problem, a novel negentropy-induced multi-objective optimized wavelet filter is proposed in this paper. The wavelet parameters are determined by a grey wolf optimizer with two independent objective functions i.e., maximizing the negentropy of squared envelope and squared envelope spectrum to capture impulsiveness and cyclostationarity, respectively. Subsequently, the average negentropy is utilized in identifying the IFB from the obtained Pareto set, which are non-dominated by other solutions to balance the impulsive and cyclostationary features and eliminate the background noise. Two cases of real vibration signals with slight bearing faults are applied in order to evaluate the performance of the proposed methodology, and the results demonstrate its effectiveness over some fast and optimal filtering methods. In addition, its stability in tracking the IFB is also tested by a case of condition monitoring data sets.
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The chaos detection of the Duffing system with the fractional-order derivative subjected to external harmonic excitation is investigated by the Melnikov method. In order to apply the Melnikov method to detect the chaos of the Duffing system with the fractional-order derivative, it is transformed into the first-order approximate equivalent integer-order system via the harmonic balance method, which has the same steady-state amplitude-frequency response equation with the original system. Also, the amplitude-frequency response of the Duffing system with the fractional-order derivative and its first-order approximate equivalent integer-order system are compared by the numerical solutions, and they are in good agreement. Then, the analytical chaos criterion of the Duffing system with the fractional-order derivative is obtained by the Melnikov function. The bifurcation and chaos of the Duffing system with the fractional-order derivative and an integer-order derivative are analyzed in detail, and the chaos criterion obtained by the Melnikov function is verified by using bifurcation analysis and phase portraits. The analysis results show that the Melnikov method is effective to detect the chaos in the Duffing system with the fractional-order derivative by transforming it into an equivalent integer-order system.
RESUMEN
In this paper, the computation schemes for periodic solutions of the forced fractional-order Mathieu-Duffing equation are derived based on incremental harmonic balance (IHB) method. The general forms of periodic solutions are founded by the IHB method, which could be useful to obtain the periodic solutions with higher precision. The comparisons of the approximate analytical solutions by the IHB method and numerical integration are fulfilled, and the results certify the correctness and higher precision of the solutions by the IHB method. The dynamical analysis of strongly nonlinear fractional-order Mathieu-Duffing equation is investigated by the IHB method. Then, the effects of the excitation frequency, fractional order, fractional coefficient, and nonlinear stiffness coefficient on the complex dynamical behaviors are analyzed. At last, the detailed results are summarized and the conclusions are made, which present some useful information to analyze and/or control the dynamical response of this kind of system.
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Wheelset bearing is one of the crucial rotating elements in the train bogie. Detection of wheelset bearing defect comes with many challenges due to complex wheel/rail excitation and the horrible working condition. The parametric dictionary sparse representation provides a practical path to detect the weak fault of wheelset bearing. However, the parametric dictionary obtained by the classical correlation filtering algorithm (CFA) is hard to match the analyzed signal's underlying fault impact characteristic. A novel parametric dictionary design algorithm named fault impact matching algorithm (FIMA) combining Orthogonal matching pursuit (OMP) is proposed to address the problem in this paper. The core of the FIMA mainly comprises two stages: partial segmentation and global analysis. Two indexes, correlation function (CF) and kurtosis, are used to comprehensively evaluate the partial and global matching degree between the Laplace wavelet and the signal. The proposed method's effectiveness is verified by the fault simulation analysis and the practical wheelset bearing fault signals (outer and inner race fault). Some comparison studies demonstrate that the proposed method outperforms the CFA-OMP, the K-SVD-OMP and some time-frequency decomposition methods, such as EWT and VMD, in detecting the bearing weak defects.
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Dynamic vibration absorber (DVA) with large auxiliary mass has better control performance, but it is also more bulky. Therefore, the mass ratio (the ratio of auxiliary mass of DVA to mass of controlled object) is usually limited to make the DVA easy to install and suitable for engineering practice. In this paper a grounded type DVA with lever component is proposed, which aims to increase the effective mass and reduce unnecessary mass to improve control performance of the DVA. Firstly, the motion differential equations of the DVA are established and solved. Secondly, the optimum parameters are obtained based on H∞ and H2 optimization criterion. Then, the performances of the grounded type DVA equipped with and without the lever are investigated. Finally, the control performance of the DVA is compared with other three typical DVAs under H∞ and H2 criterion. In this type DVA there are no global optimum parameters, and larger frequency ratio will get better control performance. If the amplification ratio (the ratio of lever power arm to lever resistance arm) is greater than 1, the introduced lever will contribute to control performance of the DVA. Its control performance is better than those of other three typical DVAs. The use of the lever can increase the effective mass of the DVA, thereby improving the control performance of the DVA. The DVA can achieve good performance at small mass ratio by adjusting amplification ratio, which may provide theoretical basis for the design of new kinds of DVAs.
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A new type of responses called as periodic-chaotic motion is found by numerical simulations in a Duffing oscillator with a slowly periodically parametric excitation. The periodic-chaotic motion is an attractor, and simultaneously possesses the feature of periodic and chaotic oscillations, which is a new addition to the rich nonlinear motions of the Duffing system including equlibria, periodic responses, quasi-periodic oscillations and chaos. In the current slow-fast Duffing system, we find three new attractors in the form of periodic-chaotic motions. These are called the fixed-point chaotic attractor, the fixed-point strange nonchaotic attractor, and the critical behavior with the maximum Lyapunov exponent fluctuating around zero. The system periodically switches between one attractor with a fixed single-well potential and the other with time-varying two-well potentials in every period of excitation. This behavior is apparently the mechanism to generate the periodic-chaotic motion.
RESUMEN
This paper presents a method of ultrasonic-assisted laser metal deposition of Al-12Si alloy. The effects of the ultrasonic power and remelting treatment on the development of porosity, microstructural evolution, and tensile properties of the deposits were investigated. The results suggested that a combination of an ultrasonic vibration and remelting treatment could prolong the existence of the molten pool and the effect of the ultrasound. Therefore, the density of the samples increased from 95.4% to 99.1% compared to the as-prepared samples. The ultrasonic action in the molten pool could not only increase the density of the samples but also refine the grains and improve the tensile properties of the samples. Metallographic observation showed that the maximum size of the primary α-Al dendrites were refined from 277.5 µm to 87.5 µm. The ultimate tensile strength and elongation of the remelting treatment samples with ultrasonic vibration were ~227 ± 3 MPa and 12.2% ± 1.4%, respectively, which were approximately 1.17 and 1.53 times those of the as-prepared samples, respectively. According to the tensile properties and fracture analysis, the density increase dominated the improvement of the mechanical properties.