Minping Jia

Fault diagnosis of rolling element bearing using a new optimal scale morphology analysis method

Periodic transient impulses are key indicators of rolling element bearing defects. Efficient acquisition of impact impulses concerned with the defects is of much concern to the precise detection of bearing defects. However, transient features of rolling element bearing are generally immersed in stochastic noise and harmonic interference. Therefore, in this paper, a new optimal scale morphology analysis method, named adaptive multiscale combination morphological filter-hat transform (AMCMFH), is proposed for rolling element bearing fault diagnosis, which can both reduce stochastic noise and reserve signal details. In this method, firstly, an adaptive selection strategy based on the feature energy factor (FEF) is introduced to determine the optimal structuring element (SE) scale of multiscale combination morphological filter-hat transform (MCMFH). Subsequently, MCMFH containing the optimal SE scale is applied to obtain the impulse components from the bearing vibration signal. Finally, fault types of bearing are confirmed by extracting the defective frequency from envelope spectrum of the impulse components. The validity of the proposed method is verified through the simulated analysis and bearing vibration data derived from the laboratory bench. Results indicate that the proposed method has a good capability to recognize localized faults appeared on rolling element bearing from vibration signal. The study supplies a novel technique for the detection of faulty bearing.

Bispectrum feature extraction of gearbox faults based on nonnegative Tucker3 decomposition with 3D calculations

Nonnegative Tucker3 decomposition(NTD) has attracted lots of attentions for its good performance in 3D data array analysis. However, further research is still necessary to solve the problems of overfitting and slow convergence under the anharmonic vibration circumstance occurred in the field of mechanical fault diagnosis. To decompose a large-scale tensor and extract available bispectrum feature, a method of conjugating Choi-Williams kernel function with Gauss-Newton Cartesian product based on nonnegative Tucker3 decomposition(NTD_EDF) is investigated. The complexity of the proposed method is reduced from o(nN lgn) in 3D spaces to o(R1R2nlgn) in 1D vectors due to its low rank form of the Tucker-product convolution. Meanwhile, a simultaneously updating algorithm is given to overcome the overfitting, slow convergence and low efficiency existing in the conventional one-by-one updating algorithm. Furthermore, the technique of spectral phase analysis for quadratic coupling estimation is used to explain the feature spectrum extracted from the gearbox fault data by the proposed method in detail. The simulated and experimental results show that the sparser and more inerratic feature distribution of basis images can be obtained with core tensor by the NTD_EDF method compared with the one by the other methods in bispectrum feature extraction, and a legible fault expression can also be performed by power spectral density(PSD) function. Besides, the deviations of successive relative error(DSRE) of NTD_EDF achieves 81.66 dB against 15.17 dB by beta-divergences based on NTD(NTD_Beta) and the time-cost of NTD_EDF is only 129.3 s, which is far less than 1 747.9 s by hierarchical alternative least square based on NTD (NTD_HALS). The NTD_EDF method proposed not only avoids the data overfitting and improves the computation efficiency but also can be used to extract more inerratic and sparser bispectrum features of the gearbox fault.

Simulation and Experimental Investigation on the AE Tomography to Improve AE Source Location in the Concrete Structure

Acoustic emission (AE) tomography, which is based on the time-travel tomography with AE events as its signal sources, is a new visualization tool for inspecting and locating the internal damages in the structures. In this paper, AE tomography is applied to examine a man-made damage in a typical heterogeneous concrete structure to validate its effectiveness. Firstly, the finite element (ABAQUS/Explicit) simulation model of the concrete structure with one damaged circle in its center is built, and the simulated AE signals are obtained to establish the AE tomography. The results show that the damaged circle in the created model can be visualized clearly with the AE tomography in its original location. Secondly, the concrete specimen based on the FE model is fabricated, and the pencil lead break (PLB) signal is taken as the exciting source for AE tomography. It is shown that the experimental results have good consistency with the FE simulation results, which also verifies the feasibility of the finite element model for AE tomography. Finally, the damage source location based on AE tomography is compared with the traditional time of arrival (TOA) location method, and the better location accuracy is obtained with the AE tomography. The research results indicate that AE tomography has great potential in the application of structure damage detection.