Fault Detection and Behavior Analysis of Wheelset Bearing Using Adaptive Convolutional Sparse Coding Technique Combined with Bandwidth Optimization

Wheelset bearing is a critical and easily damaged component of a high-speed train. Wheelset bearing fault diagnosis is of great significance to ensure safe operation of high-speed trains and realize intelligent operation and maintenance. The convolutional sparse coding technique based on the dictionary learning algorithm (CSCT-DLA) provides an effective algorithm framework for extracting the impulses caused by bearing defect. However, dictionary learning is easily affected by foundation vibration and harmonic interference and cannot learn the key structure related to fault impulses. At the same time, the detection performance of fault impulse heavily depends on the selection of parameters in this approach. Union of convolutional dictionary learning algorithm (UC-DLA) is an efficient algorithm in CSCT-DLA. In this paper, UC-DLA is introduced and improved for wheelset bearing fault detection. Finally, a novel bearing fault detection method, adaptive UC-DLA combined with bandwidth optimization (AUC-DLA-BO), is proposed. The mathematical formulation of AUC-DLA-BO is a sort of constrained optimization problem, which can overcome foundation vibration and harmonic interference and adaptively determine parameters related to UC-DLA. The proposed method can detect the fault resonance band adaptively, eliminate the noise with the same frequency band as the fault resonance band, and highlight the bearing fault impulses. Simulated signals and bench tests are used to verify the effectiveness of the proposed method. The results show that AUC-DLA-BO can effectively detect bearing faults and realize the refined analysis of fault behavior.

A fault diagnosis method for rolling element bearing (REB) based on reducing REB foundation vibration and noise-assisted vibration signal analysis

Owing to the problem of the incipient fault characteristics being difficult to be extracted from the raw vibration signal of rolling element bearing, based on the empirical mode decomposition and kurtosis criteria, a fault diagnosis method for rolling element bearing is proposed by reducing rolling element bearing foundation vibration and noise-assisted vibration signal analysis. Firstly, rolling element bearing vibration signal is decomposed into a set of intrinsic mode functions using empirical mode decomposition and the intrinsic mode function component with the maximal kurtosis value is selected. Afterwards, zero mean normalization is applied to the selected intrinsic mode function component, and then the intrinsic mode function’s foundation vibration components within [Formula: see text] are removed to minimize the interference. In order to eliminate interruption and intermittency after removal of the foundation vibration components, white noise is added to the newly generated signal. The noise-added signal is decomposed via empirical mode decomposition, and later on, IMF1 with the highest frequency band is selected and demodulated using envelope analysis. The resulting envelope spectrum can show more significant fault pulse characteristics, which are highly helpful to diagnose the rolling element bearing incipient faults. The proposed method in this paper was applied to the fault diagnosis for low noise REB 6203 and the testing results showed that the method could identify the rolling element bearing incipient faults accurately and quickly.

A Simple Method of Calculating Safety Vibrating Velocity for Single-Layer Masonry Structures in Blasting Construction

Blasting-induced seismic wave imposes cyclic loadings on adjacent buildings and structures with a combined loading mode of tension, compression, bending, shear and torsion, and it leads to flaking of floated coat, wall cracking, developing of original cracks, etc. This paper presents a blasting case study for the excavation of Wucun tunnel in Xiamen Success Avenue. Field monitoring and numerical calculation of a typical brick masonry structure are adopted to analyze the relationships among the maximum structural displacement, peak vibration velocity of blasting-induced foundation vibration and the change rate of crack width. On the basis of the study above, a method of calculating the safe vibrating velocity for single-layer masonry structure is proposed. Meanwhile, a suggested value of the safe vibrating velocity for single-layer masonry structure is given. All the research results can be useful for the similar construction and research.

Analysis of Foundation Influence Caused by Mechanical Vibration

In order to study excessive foundation vibration produced by mechanical vibration, this paper firstly deduce displacement amplitude formula based on dynamics theory and a simplified 2DOF model consisting of machine and foundation underneath. Functional expression of dynamic magnification factor D and frequency ratio is put forward by assuming stiffness ratio and mass ratio of machine and foundation. Then compared with function graphs under different suppositions, we know how to roughly assess foundation influence produced by mechanical vibration and how to roughly design machine which make foundation be unaffected.

Study on Optimization of Dynamic Characteristics of Turbo Generator Foundation

The dynamic characteristics of turbo generator foundation have an important impact on safe operation of power plant. The study first used the vibration mode superposition method to solve the structural vibration response and sensitivity through establishing the dynamic equations and optimization model of the foundation, and then determined the optimization variables, constraints and objectives according to the process conditions, and at last undertook multivariate optimization research on a 1000MW turbo-generator foundation. Finally, an optimization scheme which reduces both the linear displacement of foundation vibration and the amount of concrete used was obtained. The analysis results showed that the optimization method adopted in this study had higher efficiency and could achieve better technical and economic benefits.