Vibration mechanism and improved phenomenological model of the planetary gearbox with broken ring gear fault

Luo, Yingchao; Cui, Lingli; Zhang, Jianyu; Ma, Jianfeng

doi:10.1007/s12206-021-0406-6

Cited by 16 publications

(5 citation statements)

References 33 publications

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“…From the perspective of energy, the process of vibration generated when the gearbox transmission system works is the process of energy transfer, that is, the energy loss in the process of gear transmission. According to the source of vibration excitation of a gearbox transmission system, it can be seen that this is a relatively complex mechanical vibration system, but to study the relationship between vibration signal and vibration energy in the vibration system, we can simplify it into a forced vibration model under the action of simple harmonic excitation with one degree of freedom [6]. The single degree of freedom vibration system can be regarded as an object with 𝑚 mass, a spring with 𝑘 stiffness coefficient without gravity and 𝑐 damping without gravity.…”

Section: Vibration Function Model Of Gearboxmentioning

confidence: 99%

A Health Assessment Technique Based on WPD and Multiple Linear Regression Analysis

Xiong

2023

J. Phys.: Conf. Ser.

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A health assessment technique based on WPD and multiple linear regression analysis is studied in this paper. Firstly, the Temperature-Vibration function model is established by analyzing the mechanism of vibration and temperature of the gearbox. Secondly, the vibration and temperature signals and ambient temperature of the quayside crane lifting gearbox were decomposed by wavelet packet, and the total energy after wavelet packet reconstruction was calculated respectively. Thirdly, multiple linear regression analysis is carried out to obtain the multiple linear regression model of the lifting gearbox based on the established function model. Finally, the absolute error between the total energy of the wavelet packet of the actual and the calculated temperature is calculated to judge the health status of the gearbox during 2009-2015 according to the model. The results show that the judged health state of the quayside crane lifting gearbox is consistent with the actual situation, indicating that the technique can be effectively applied to the health assessment of the gearbox.

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Section: Vibration Function Model Of Gearboxmentioning

confidence: 99%

A Health Assessment Technique Based on WPD and Multiple Linear Regression Analysis

Xiong

2023

J. Phys.: Conf. Ser.

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“…The fault characteristic at the initial stage of tooth wear are weak and easy to be submerged in the noise information. The PGB usually has a serious modulation phenomenon, 4 which together makes it difficult to extract the fault characteristic of tooth wear in the PGB. Therefore, extracting fault-related information from vibration signals becomes the basis of fault diagnosis.…”

Section: Introductionmentioning

confidence: 99%

A novel method for early fault diagnosis of planetary gearbox with distributed tooth surface wear

Gao

Shang

et al. 2023

Structural Health Monitoring

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Planetary gearbox (PGB) usually work in harsh working conditions with low speed and heavy load, and they are prone to wear. Different from the local faults, the distributed faults such as tooth surface wear are often weak and difficult to detect in the early stage, and it is difficult to extract fault characteristic. This paper presents an early fault diagnosis method for the distributed tooth surface wear of PGB to solve this problem. The proposed multi-channel optimal maximum correlation kurtosis deconvolution (MCO_MCKD) algorithm is used to extract fault characteristic. In order to enhance the effect of fault characteristic extraction (FCE), the algorithm first uses the sliding window principle to segment the input signal to establishes multiple channels for maximum correlation kurtosis (max_CK) optimization based on all the short signals obtained. The finite impulse response (FIR) filter with the max_CK is selected to filter the input signal, in order to realize FCE. The influence of tooth wear is mainly reflected in the frequency-domain signal amplitude. In order to realize early fault diagnosis, the frequency-domain statistical indicator fault characteristic energy ratio (FCER) is proposed based on this characteristic. The health status of the equipment is monitored by calculating the FCER of the signal after FCE. Early fault diagnosis is realized based on the mutation of the FCER. The simulation results show that MCO_MCKD algorithm has strong robustness. The experimental results show this proposed method is effective and superior.

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“…As evolved versions of SK, SKRgram [16], Infogram [17], Autogram [18], and Accugram [19] are still restricted by the best frequency band selection [20] and the fixed spectral segmentation strategy, which may lead to the loss of some key faulty information [21]. The deconvolution algorithm, such as the minimum entropy deconvolution (MED) [22], maximum correlated kurtosis deconvolution (MCKD) [23], multipoint optimal minimum entropy deconvolution adjusted (MOEDA) [24], and cyclostationary blind deconvolution (CYCBD) [25], iteratively updates the filter to make the target evaluation index of the output signal reach the optimal value, so that the fault-affected signal can be recovered [26]. The performance of deconvolution algorithm greatly depends on the selection of the objective function and the filter length, which limit the practical application of the deconvolution methods [27].…”

Section: Introductionmentioning

confidence: 99%

An Iterative Modified Adaptive Chirp Mode Decomposition Method and Its Application on Fault Diagnosis of Wind Turbine Bearings

et al. 2022

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Wind turbine bearings usually work with strong background noise, making the faulty properties difficult to extract and detect. To accurately diagnose the faults of rolling bearings in wind turbines, an iterative modified adaptive chirp mode decomposition (IMACMD) method is proposed in this paper. Firstly, an envelope interpolation method is employed to preliminarily determine the iterative mode number and guide the potentially initial frequency selection. Secondly, the upper limits of the iterative mode number and the initial frequency are further determined through correlation analysis. During the iteration process, the optimal weight factor of the reconstructive input signal, which is the residual signal of the previous iterative decomposition, is determined according to the new designed ensemble L-kurtosis index. Experimental and engineering signals are used to validate the proposed IMACMD method. Comparisons with the conventional methods demonstrate the superiority of this proposed method. It is shown that this method can not only identify the weak features for single faults but also separate the multiple features for compound faults.

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Vibration mechanism and improved phenomenological model of the planetary gearbox with broken ring gear fault

Cited by 16 publications

References 33 publications

A Health Assessment Technique Based on WPD and Multiple Linear Regression Analysis

A Health Assessment Technique Based on WPD and Multiple Linear Regression Analysis

A novel method for early fault diagnosis of planetary gearbox with distributed tooth surface wear

An Iterative Modified Adaptive Chirp Mode Decomposition Method and Its Application on Fault Diagnosis of Wind Turbine Bearings

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