Zhe Wu

Dr. Zhe Wu


Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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13 November 2018 in Entropy
Verified
Journal Article
Open access
PDF file
ZWZhe Wu
Zhe Wu
QZQiang Zhang
Qiang Zhang
LWLixin Wang
Lixin Wang
CLCheng Lifeng
Cheng Lifeng
JZJingbo Zhou
Jingbo Zhou
It is a difficult task to analyze the coupling characteristics of rotating machinery fault signals under the influence of complex and nonlinear interference signals. This difficulty is due to the strong noise background of rotating machinery fault feature extraction and weaknesses, such as modal mixing problems, in the existing Ensemble Empirical Mode Decomposition (EEMD) time–frequency analysis methods. To quantitatively study the nonlinear synchronous coupling characteristics and information transfer characteristics of rotating machinery fault signals between different frequency scales under the influence of complex and nonlinear interference signals, a new nonlinear signal processing method—the harmonic assisted multivariate empirical mode decomposition method (HA-MEMD)—is proposed in this paper. By adding additional high-frequency harmonic-assisted channels and reducing them, the decomposing precision of the Intrinsic Mode Function (IMF) can be effectively improved, and the phenomenon of mode aliasing can be mitigated. Analysis results of the simulated signals prove the effectiveness of this method. By combining HA-MEMD with the transfer entropy algorithm and introducing signal processing of the rotating machinery, a fault detection method of rotating machinery based on high-frequency harmonic-assisted multivariate empirical mode decomposition-transfer entropy (HA-MEMD-TE) was established. The main features of the mechanical transmission system were extracted by the high-frequency harmonic-assisted multivariate empirical mode decomposition method, and the signal, after noise reduction, was used for the transfer entropy calculation. The evaluation index of the rotating machinery state based on HA-MEMD-TE was established to quantitatively describe the degree of nonlinear coupling between signals to effectively evaluate and diagnose the operating state of the mechanical system. By adding noise to different signal-to-noise ratios, the fault detection ability of HA-MEMD-TE method in the background of strong noise is investigated, which proves that the method has strong reliability and robustness. In this paper, transfer entropy is applied to the fault diagnosis field of rotating machinery, which provides a new effective method for early fault diagnosis and performance degradation-state recognition of rotating machinery, and leads to relevant research conclusions.

1 January 2021 in Shock and Vibration
Verified
Journal Article
Open access
PDF file
ZWZhe Wu
Zhe Wu
QZQiang Zhang
Qiang Zhang
ZMZeyu Ma
Zeyu Ma
JLJialong Lu
Jialong Lu
ZQZhiying Qin
Zhiying Qin
Planetary gear transmission system is an important transmission part of large machinery and is prone to failure. Aiming at the problem of how to extract fault information from vibration signals of nonlinear and nonstationary planetary gearboxes, a performance degradation evaluation index of planetary gearboxes based on improved distributed compressed sensing and modified multiscale symbolic dynamic entropy (DCSMDE) is proposed. DCSMDE combines distributed compression sensing with modified multiscale symbol dynamic entropy and solves the problem of strong nonlinearity and strong vibration signal coupling of the planetary transmission system from the homologous signals of multiple sensors. A distributed compression sensing parameter optimization algorithm based on Rényi entropy is proposed, which uses improved distributed compression sensing technology to simultaneously sample, compress, and denoise the multisource vibration data of rotating machinery. DCSMDE is used to calculate the reconstructed signal, extract the features with higher recognition characteristics, and use the change trend of the DCSMDE value to judge the working status of the planetary gearbox. Experimental results show that DCSMDE can be applied to dynamic evolution and fault identification of mechanical systems and accurately classify actual fault signals. It provides a new idea for the classification of planetary gear faults and the recognition of performance degradation.

12 December 2018 in IOP Conference Series: Materials Science and Engineering
Verified
Conference Paper
Open access
PDF file
QZQiang Zhang
Qiang Zhang
ZWZhe Wu
Zhe Wu
HLHongwu Li
Hongwu Li
In this paper, the structure and properties of Q355NH weathering steel welded joints were studied. Through the analysis of the micro-structure of welded joint, the results showed that the fine grain area, columnar crystal and equiaxial crystal existed both before and after the annealing, and the grain size at the bottom of the cover welds was larger than that of the bottom welds. After annealing, the grain size became uniform and the size was reduced. Moreover, the fusion line became less obvious. After annealing treatment, the distribution of martensite inside the welds was more uniform than that of untreated ones.