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  • SAGE Publications  (5)
  • Wu, Xing  (5)
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  • SAGE Publications  (5)
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  • 1
    Online Resource
    Online Resource
    Fault diagnosis of planetary gear backlash based on motor current and Fisher criterion optimized sparse autoencoder
    SAGE Publications ; 2022
    In:  Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science Vol. 236, No. 13 ( 2022-07), p. 7529-7545
    Details
    In: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, SAGE Publications, Vol. 236, No. 13 ( 2022-07), p. 7529-7545
    Abstract: Planetary gear reducer is widely applied in various transmission equipment, and its performance highly affects the operation of a machine. The appearance of unreasonable backlash in planetary gear reducer may lead to undesirable vibration, which may accelerate the degradation of equipment and eventually cause premature failure. In traditional condition-based monitoring (CBM), sensors such as accelerometers have been utilized to detect the fault of planetary gear. However, the complexity and integration of planetary gear limit the installation and application of vibration sensors in practice. In this case, the current signal from motor, as a convenient real-time monitoring approach, is introduced into the CBM of the planetary gear. In this paper, a fault diagnosis method based on drive motor current signal analysis (MCSA) is presented to identify the backlash fault in a planetary gear reducer. In this method, frequency domain data of the original current signal is found and used to automatically extract fault features. A deep sparse autoencoder (DSAE) extracts the required features. In particular, the Fisher criterion is introduced to evaluate the sensitivity of these features. It then selects the most effective ones for improving diagnostic accuracy as well as diagnostic efficiency. Experimental test data shows that under different load conditions, this method outperforms other typical fault diagnosis methods and exhibits the best performance.
    Type of Medium: Online Resource
    ISSN: 0954-4062 , 2041-2983
    URL: Article
    DOI: 10.1177/09544062211070160
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2022
    detail.hit.zdb_id: 2024890-8
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Research on bearing vibration signal generation method based on filtering WGAN_GP with small samples
    SAGE Publications ; 2023
    In:  Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science Vol. 237, No. 20 ( 2023-10), p. 4911-4929
    Details
    In: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, SAGE Publications, Vol. 237, No. 20 ( 2023-10), p. 4911-4929
    Abstract: In the practical application of bearing fault diagnosis, the data imbalance problems caused by the lack of available fault data lead to inaccurate diagnosis. The high cost and difficulty of obtaining fault samples has become an obstacle to the development of intelligent diagnosis technology. Aiming at the problem of data imbalance caused by small samples, this paper proposes a data generation method called FEF_WGAN_GP based on Wasserstein generative adversarial networks with gradient penalty (WGAN_GP) and feature Euclidean distance filtering (FEF) theory. Firstly, WGAN_GP is used to obtain signals with similar distribution to the small sample data, which can alleviate the imbalance of the dataset. Then, the FEF method is used to filter the generated data in order to obtain a higher quality of the samples. In the test validation part, not only the used dataset is evaluated to obtain a more reasonable dataset, but also the generated signals are evaluated from multiple perspectives. In addition, this paper evaluates the effects of the number, length and signal-to-noise ratio of the parent data on the quality of the generated signals, as well as the effect of the setting of the threshold of the data filtering method on the accuracy of the classifier. The experimental results indicate that this method performs well in processing unbalance fault data. It has better stability and diagnostic accuracy than the current stable method.
    Type of Medium: Online Resource
    ISSN: 0954-4062 , 2041-2983
    URL: Article
    DOI: 10.1177/09544062231154077
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
    detail.hit.zdb_id: 2024890-8
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    Online Resource
  • 3
    Online Resource
    Online Resource
    Prognostic value of ALDH1 and Nestin in advanced cancer: a systematic meta-analysis with trial sequential analysis
    SAGE Publications ; 2019
    In:  Therapeutic Advances in Medical Oncology Vol. 11 ( 2019-01), p. 175883591983083-
    Details
    In: Therapeutic Advances in Medical Oncology, SAGE Publications, Vol. 11 ( 2019-01), p. 175883591983083-
    Abstract: Novel prognostic markers and therapeutic targets for advanced cancer are urgently needed. This report with trial sequential analysis (TSA) was first conducted to provide robust estimates of the correlation between aldehyde dehydrogenase 1 (ALDH1) and Nestin and clinical outcomes of advanced cancer patients. Methods: Hazard ratios (HRs) with 95% confidence intervals (CIs) were summarized for overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), cancer-specific survival (CSS), relapse/recurrence-free survival (RFS), and metastasis-free survival (MFS) from multivariable analysis. TSA was performed to control for random errors. Results: A total of 20 studies with 2050 patients (ALDH1: 15 studies with 1557 patients and Nestin: 5 studies with 493 patients) were identified. ALDH1 (HR = 2.28, p 〈 0.001) and Nestin (HR = 2.39, p 〈 0.001) were associated with a worse OS, as confirmed by TSA. Nestin positivity was linked to a poor PFS (HR = 2.08, p 〈 0.001), but ALDH1 was not linked to DFS, RFS, MFS, or PFS, and TSA showed that more studies were needed. Subgroup analysis by tumor type indicated that ALDH1 positivity may be associated with shorter OS in breast, head and neck cancers, but there was no association with colorectal cancer. Subgroup analysis by study source showed that ALDH1 positivity was correlated with a worse OS for Japanese (HR = 1.94, p = 0.002) and European patients (HR = 4.15, p 〈 0.001), but there was no association for Chinese patients. Subgroup analysis by survival rate showed that ALDH1 positivity correlated with poor OS at ⩾ 5 years (HR = 2.33, p 〈 0.001) or 10 years (HR = 1.76, p = 0.038). Conclusions: ALDH1 may be more valuable as an effective therapeutic target than Nestin for improving the long-term survival rate of advanced cancer. Additional prospective clinical trials are needed across different cancer types.
    Type of Medium: Online Resource
    ISSN: 1758-8359 , 1758-8359
    URL: Article
    DOI: 10.1177/1758835919830831
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2019
    detail.hit.zdb_id: 2503443-1
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  • 4
    Online Resource
    Online Resource
    Application of optimized variational mode decomposition based on kurtosis and resonance frequency in bearing fault feature extraction
    SAGE Publications ; 2020
    In:  Transactions of the Institute of Measurement and Control Vol. 42, No. 3 ( 2020-02), p. 518-527
    Details
    In: Transactions of the Institute of Measurement and Control, SAGE Publications, Vol. 42, No. 3 ( 2020-02), p. 518-527
    Abstract: Variational mode decomposition (VMD) is an adaptive signal processing method proposed recently. It has gradually been widely used due to its good performance. According to the problem that the parameters of VMD need to be determined in advance, a simple and feasible method of determining the influence parameters based on the principle of kurtosis maximum is put forward. A novel intrinsic mode function (IMF) selection method based on resonance frequency is proposed in order to select the IMF that contains the abundant fault feature information. Firstly, the parameters of VMD are optimized by the principle of kurtosis maximum, the optimal penalty parameter and mode number of VMD are set, and the original fault signal is processed by the optimized VMD to obtain the established IMF components. Then, the sensitive IMF(s) with the fault information is selected by resonance frequency. Finally, the selected IMF(s) is analyzed by the envelope demodulation analysis to extract the fault characteristic frequency to judge the fault type of the rolling bearing. It is shown that the method can extract the weak characteristics of the early fault signal of the rolling bearing, and it can realize the judgment of the bearing fault accurately through the analysis of simulated signal and the actual data of bearing.
    Type of Medium: Online Resource
    ISSN: 0142-3312 , 1477-0369
    URL: Article
    DOI: 10.1177/0142331219875348
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2020
    detail.hit.zdb_id: 2025882-3
    SSG: 3,2
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  • 5
    Online Resource
    Online Resource
    Bioactive Polyketides From the Potato Endophytic Fungus Aspergillus carneus
    SAGE Publications ; 2020
    In:  Natural Product Communications Vol. 15, No. 12 ( 2020-12-01), p. 1934578X2098522-
    Details
    In: Natural Product Communications, SAGE Publications, Vol. 15, No. 12 ( 2020-12-01), p. 1934578X2098522-
    Type of Medium: Online Resource
    ISSN: 1934-578X , 1555-9475
    URL: Article
    DOI: 10.1177/1934578X20985222
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2020
    detail.hit.zdb_id: 2430442-6
    SSG: 15,3
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