An Extended EEMD Method for Localized Faults Detection of a Planetary Gearbox

Due to planetary movement of planet gears, the vibration signal perceived by a stationary sensor is modulated and difficult to diagnose. This paper proposed a vibration separation methodology compensated by a time-varying transfer function (TVTF-VS), which is a further development of the vibration separation (VS) method in the diagnosis of non-hunting tooth planetary gearboxes. On the basis of VS, multi-teeth VS is proposed to extract and synthesize the meshing signal of a planet gear using a single transducer. Considering the movement regularity of a planetary gearbox, the time-varying transfer function (TVTF) is represented by a generalized expression. The TVTF is constructed using a segment of healthy signal and an evaluation indicator is established to optimize the parameters of the TVTF. The constructed TVTF is applied to overcome the amplitude modulation effect and highlight fault characteristics. After that, experiments with baseline, pitting, and compound localized faults planet gears were conducted on a non-hunting tooth planetary gearbox test rig, respectively. The results demonstrate that incipient failure on a planet gear can be detected effectively, and relative location of the local faults can be determined accurately.

Download Full-text

Study on Fault Diagnosis of Planetary Gearbox in Unmanned Aerial Vehicle Using Multi sensor Data

Journal of Applied Reliability ◽

10.33162/jar.2020.12.20.4.332 ◽

2020 ◽

Vol 20 (4) ◽

pp. 332-342

Author(s):

Hyung Jun Park ◽

Seong Hee Cho ◽

Kyung-Hwan Jang ◽

Jin-Woon Seol ◽

Byung-Gi Kwon ◽

...

Keyword(s):

Fault Diagnosis ◽

Unmanned Aerial Vehicle ◽

Sensor Data ◽

Planetary Gearbox ◽

Aerial Vehicle

Download Full-text

Fault detection for planetary gearbox based on an enhanced average filter and modulation signal bispectrum analysis

ISA Transactions ◽

10.1016/j.isatra.2020.02.010 ◽

2020 ◽

Vol 101 ◽

pp. 408-420 ◽

Cited By ~ 4

Author(s):

Junchao Guo ◽

Dong Zhen ◽

Haiyang Li ◽

Zhanqun Shi ◽

Fengshou Gu ◽

...

Keyword(s):

Fault Detection ◽

Planetary Gearbox ◽

Modulation Signal ◽

Average Filter

Download Full-text

Analysis method of the cavitation vibration signals in poppet valve based on EEMD

Advances in Mechanical Engineering ◽

10.1177/1687814021998114 ◽

2021 ◽

Vol 13 (2) ◽

pp. 168781402199811

Author(s):

Beibei Li ◽

Qiao Zhao ◽

Huaiyi Li ◽

Xiumei Liu ◽

Jichao Ma ◽

...

Keyword(s):

Ensemble Empirical Mode Decomposition ◽

Center Frequency ◽

Analysis Method ◽

Vibration Signals ◽

Poppet Valve ◽

Mode Decomposition ◽

Marginal Spectrum ◽

Cavitation Intensity ◽

Eemd Method ◽

Peak Value

To study the vibration characteristics of the poppet valve induced by cavitation, the signal analysis method based on the ensemble empirical mode decomposition (EEMD) method was studied experimentally. The component induced by cavitation was separated from the vibration signals through the EEMD method. The results show that the IMF2 component has the largest amplitude and energy of all components. The root mean square (RMS) value, peak value of marginal spectrum, and center frequency of marginal spectrum of the IMF2 component were studied in detail. The RMS value and the peak value of the marginal spectrum decrease with a decrease of cavitation intensity. The center frequency of marginal spectrum is between 12 kHz and 20 kHz, and the center frequency first increases and then decreases with a decrease of cavitation intensity. The change rate of the center frequency also decreases with an increase of inlet pressure.

Download Full-text

Preliminary Evaluation of the Influence of Surface and Tooth Root Damage on the Stress and Strain State of a Planetary Gearbox: An Innovative Hybrid Numerical–Analytical Approach for Further Development of Structural Health Monitoring Models

Computation ◽

10.3390/computation9030038 ◽

2021 ◽

Vol 9 (3) ◽

pp. 38

Author(s):

Franco Concli ◽

Athanasios Kolios

Keyword(s):

Structural Health Monitoring ◽

Health Monitoring ◽

Analytical Approach ◽

Surface Defects ◽

Local Stress ◽

Computational Effort ◽

Preliminary Evaluation ◽

Tooth Root ◽

Planetary Gearbox ◽

Structural Health

Wind turbine gearboxes are known to be among the weakest components in the system and the possibility to study and understand the behavior of geared transmissions when subject to several types of faults might be useful to plan maintenance and eventually reduce the costs by preventing further damage. The aim of this work is to develop a high-fidelity numerical model of a single-stage planetary gearbox selected as representative and to evaluate its behavior in the presence of surface fatigue and tooth-root bending damage, i.e., pits and cracks. The planetary gearbox is almost entirely modelled, including shafts, gears as well as bearings with all the rolling elements. Stresses and strains in the most critical areas are analyzed to better evaluate if the presence of such damage can be somehow detected using strain gauges and where to place them to maximize the sensitivity of the measures to the damage. Several simulations with different levels, types and positions of the damage were performed to better understand the mutual relations between the damaged and the stress state. The ability to introduce the effect of the damage in the model of a gearbox represents the first indispensable step of a Structural Health Monitoring (SHM) strategy. The numerical activity was performed taking advantage of an innovative hybrid numerical–analytical approach that ensures a significant reduction of the computational effort. The developed model shows good sensitivity to the presence, type and position of the defects. For the studied configuration, the numerical results show clearly show a relation between the averaged rim stress and the presence of root cracks. Moreover, the presence of surface defects seems to produce local stress peaks (when the defects pass through the contact) in the instantaneous rim stress.

Download Full-text

Study on Fault Diagnosis Method of Planetary Gearbox Based on Turn Domain Resampling and Variable Multi-Scale Morphological Filtering

Symmetry ◽

10.3390/sym13010052 ◽

2020 ◽

Vol 13 (1) ◽

pp. 52

Author(s):

Tongtong Liu ◽

Lingli Cui ◽

Chao Zhang

Keyword(s):

Frequency Conversion ◽

Interpolation Method ◽

Spline Interpolation ◽

Operating Efficiency ◽

Planetary Gearbox ◽

Noise Interference ◽

Multi Scale ◽

Morphological Filtering ◽

Diagnosis Method ◽

Simulation Signal

The turn domain resampling (TDR) method is proposed in the paper on the basis of the existing angle domain resampling for solving the problem of non-fixed fault frequency under variable working conditions. TDR can select the appropriate sampling order according to the influence of frequency conversion, which avoided the error caused by the spline interpolation method. It can provide accurate parameters for the subsequent calculation of the equivalent frequency order. Variable multi-scale morphological filtering (VMSMF) method is proposed for the purpose of further reducing the interference of noise in resampling signal to feature extraction. VMSMF adaptively selects structural elements according to the parameter change of impact signal to make its scale more targeted. It only needs to calculate once using the optimal structural unit for a particular impact, and the filtering accuracy and operating efficiency have been greatly improved. The main steps of this article are as follows. First, the TDR is used to resample the original signal as to get the resampling signal which is still submerged by the strong noise. In the second step, VMSMF is used to filter the resampling signal to obtain the signal with less noise interference. Finally, the fault characteristics of the filtering signal was extracted and compared with the possible fault frequency calculated by the sampling parameters provided by resampling, so as to determine the fault type of the planetary gearbox. By analyzing the simulation signal and the experimental signal respectively, this method can find out the corresponding fault characteristics effectively.

Download Full-text