Comparative case studies on ring gear fault diagnosis of planetary gearboxes using vibrations and acoustic emissions

被引:0
|
作者
Leaman, Felix [1 ]
Baltes, Ralph [1 ]
Clausen, Elisabeth [1 ]
机构
[1] Rhein Westfal TH Aachen, Inst Adv Min Technol, Wullnerstr 2, D-52062 Aachen, Germany
来源
关键词
LOW-SPEED BEARINGS; SPUR GEARS;
D O I
10.1007/s10010-021-00451-4
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The analysis of vibrations and acoustic emissions (AE) are two recognized non-destructive techniques used for machine fault diagnosis. In recent years, the two techniques have been comparatively evaluated by different researchers with experimental tests. Several evaluations have shown that the AE analysis has a higher potential than the vibration analysis for fault diagnosis of mechanical components for certain cases. However, the distance between the AE sensor and the fault is an important factor that can considerably decrease the potential to detect damage and that has not been sufficiently investigated. Moreover, the comparisons have not yet addressed conditions of slow speed that for example are usual for wind turbine gearboxes. Therefore, in this paper we present two comparative case studies that address both topics. Both case studies consider planetary gearboxes with faults in their ring gears. The first case study corresponds to a small planetary gearbox in which the AE and vibration sensors were installed together at two different positions. The second case study corresponds to a full-size wind turbine gearbox in which three pairs of AE and vibration sensors were installed on the outside of the ring gear from a low-speed planetary stage. The results of the evaluations demonstrate the important influence of the distance between sensors and fault. Despite this, the good results from the AE analysis indicate that this technique should be considered as an important complement to the traditional vibration analysis. The main contribution of this paper is comparing AE and vibration analysis by using not only experimental data from a small planetary gearbox but also from a full-size wind turbine gearbox. The comparison addresses the topics of proximity of the sensor to the fault and low-speed conditions.
引用
收藏
页码:619 / 628
页数:10
相关论文
共 50 条
  • [41] Case Studies on Transformer Fault Diagnosis using Dissolved Gas Analysis
    Shanker, T. Bhavani
    Nagamani, H. N.
    Antony, Deepthi
    Punekar, Gururaj S.
    2017 IEEE PES ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), 2017,
  • [42] Fault diagnosis of industrial robots using acoustic signals and case-based reasoning
    Olsson, E
    Funk, P
    Bengtsson, M
    ADVANCES IN CASE-BASED REASONING, PROCEEDINGS, 2004, 3155 : 686 - 701
  • [43] A novel vibro-acoustic fault diagnosis approach of planetary gearbox using intrinsic wavelet integrated GE-EfficientNet
    Hu, Huangxing
    Lv, Yong
    Yuan, Rui
    Xu, Shijie
    Zhu, Weihang
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2024, 35 (02)
  • [44] A fault diagnosis method for planetary gearboxes under non-stationary working conditions using improved Vold-Kalman filter and multi-scale sample entropy
    Li, Yongbo
    Feng, Ke
    Liang, Xihui
    Zuo, Ming J.
    JOURNAL OF SOUND AND VIBRATION, 2019, 439 : 271 - 286
  • [45] A comparative study on classification of features by SVM and PSVM extracted using Morlet wavelet for fault diagnosis of spur bevel gear box
    Saravanan, N.
    Siddabattuni, V. N. S. Kumar
    Ramachandran, K. I.
    EXPERT SYSTEMS WITH APPLICATIONS, 2008, 35 (03) : 1351 - 1366
  • [46] FAULT DIAGNOSIS AND FAULT TOLERANT CONTROL USING SET-MEMBERSHIP APPROACHES: APPLICATION TO REAL CASE STUDIES
    Puig, Vicenc
    INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE, 2010, 20 (04) : 619 - 635
  • [47] Feature-level fusion based on wavelet transform and artificial neural network for fault diagnosis of planetary gearbox using acoustic and vibration signals
    Khazaee, M.
    Ahmadi, H.
    Omid, M.
    Banakar, A.
    Moosavian, A.
    INSIGHT, 2013, 55 (06) : 323 - 329
  • [48] Assessment of embodied carbon emissions for building construction in China: Comparative case studies using alternative methods
    Zhang, Xiaocun
    Wang, Fenglai
    ENERGY AND BUILDINGS, 2016, 130 : 330 - 340
  • [49] Planetary gear fault diagnosis using stacked denoising autoencoder and gated recurrent unit neural network under noisy environment and time-varying rotational speed conditions
    Yu, Jun
    Xu, Yonggang
    Liu, Ke
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2019, 30 (09)
  • [50] A case study on classification of features by fast single-shot multiclass PSVM using Morlet wavelet for fault diagnosis of spur bevel gear box
    Saravanan, N.
    Ramachandran, K. I.
    EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (08) : 10854 - 10862