Gear fault diagnosis based on the structured sparsity time-frequency analysis

The evolutionary periodogram has been introduced to mechanical fault diagnosis and relationship between the evolutionary periodogram and time-frequency spectrogram has been investigated. The evolutionary periodogram is unveiled as an especially windowed spectrogram, and is applied to gearbox fault diagnosis. It has been shown that the window used in the evolutionary periodogram is not a single function but a combination of a set of functions. Two cases of gearbox diagnosis are presented as examples of application. Vibration signals and a synchronous signal are collected for the analysis. The time synchronous averaging is used to reduce background noise or random transients to enhance the periodicity of a specific gear rotation. The performance of the evolutionary periodogram has been compared with the spectrogram for gear diagnosis, showing that the evolutionary periodogram is an alternative technique in time-frequency analysis for fault detection and better resolution can be obtained as more choices are offered by the way of constructing the window.

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Data-driven time-frequency analysis method based on variational mode decomposition and its application to gear fault diagnosis in variable working conditions

Mechanical Systems and Signal Processing ◽

10.1016/j.ymssp.2018.06.055 ◽

2019 ◽

Vol 116 ◽

pp. 462-479 ◽

Cited By ~ 23

Author(s):

Fuhao Li ◽

Rong Li ◽

Lili Tian ◽

Lin Chen ◽

Jian Liu

Keyword(s):

Fault Diagnosis ◽

Working Conditions ◽

Frequency Analysis ◽

Data Driven ◽

Variational Mode Decomposition ◽

Analysis Method ◽

Time Frequency ◽

Mode Decomposition ◽

Gear Fault ◽

Gear Fault Diagnosis

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Fault Diagnosis for Rolling Element Bearings with VMD Time-Frequency Analysis and SVM

2015 Fifth International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC) ◽

10.1109/imccc.2015.22 ◽

2015 ◽

Cited By ~ 3

Author(s):

Wenlong Fu ◽

Jianzhong Zhou ◽

Yongchuan Zhang

Keyword(s):

Fault Diagnosis ◽

Frequency Analysis ◽

Rolling Element Bearings ◽

Time Frequency Analysis ◽

Time Frequency ◽

Rolling Element

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Adaptive parameterless empirical wavelet transform based time-frequency analysis method and its application to rotor rubbing fault diagnosis

Signal Processing ◽

10.1016/j.sigpro.2016.07.023 ◽

2017 ◽

Vol 130 ◽

pp. 305-314 ◽

Cited By ~ 63

Author(s):

Jinde Zheng ◽

Haiyang Pan ◽

Shubao Yang ◽

Junsheng Cheng

Keyword(s):

Wavelet Transform ◽

Fault Diagnosis ◽

Frequency Analysis ◽

Analysis Method ◽

Time Frequency Analysis ◽

Time Frequency ◽

Empirical Wavelet Transform

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Current-Aided Time-Frequency Analysis of Vibration Signals for Gearbox Fault Diagnosis

Volume 8: 30th Conference on Mechanical Vibration and Noise ◽

10.1115/detc2018-85550 ◽

2018 ◽

Author(s):

Xiaotong Tu ◽

Yue Hu ◽

Fucai Li

Keyword(s):

Fault Diagnosis ◽

Frequency Analysis ◽

Vibration Signal ◽

Vibration Monitoring ◽

Current Signal ◽

Reliable Technique ◽

Time Frequency Analysis ◽

Rotating Speed ◽

Planetary Gearbox ◽

Time Frequency

Vibration monitoring is an effective method for mechanical fault diagnosis. Wind turbines usually operated under varying-speed condition. Time-frequency analysis (TFA) is a reliable technique to handle such kind of nonstationary signal. In this paper, a new scheme, called current-aided TFA, is proposed to diagnose the planetary gearbox. This new technique acquires necessary information required by TFA from a current signal. The current signal is firstly used to estimate the rotating speed of the shaft. These parameters are applied to the demodulation transform to obtain a rough time-frequency distribution (TFD). Finally, the synchrosqueezing method further enhances the concentration of the obtained TFD. The validation and application of the proposed method are presented by a simulated signal and a vibration signal captured from a test rig.

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A Fast Three-Dimensional Display Method for Time-Frequency Spectrogram Used in Embedded Fault Diagnosis Devices

Applied Sciences ◽

10.3390/app8101930 ◽

2018 ◽

Vol 8 (10) ◽

pp. 1930 ◽

Cited By ~ 2

Author(s):

Lina Wang ◽

Chengdong Wang ◽

Yong Chen

Keyword(s):

Fault Diagnosis ◽

Frequency Analysis ◽

Low Cost ◽

Three Dimensional ◽

Surface Generation ◽

Depth Information ◽

Time Frequency Analysis ◽

Time Frequency ◽

Mesh Surface ◽

General Computer

Time-frequency analysis is usually used to reveal the appearance of different frequency components varying with time, in signals, of which time-frequency spectrogram is an important visual tool to display the information. The Mesh Surface Generation (MSG) algorithm is widely used in three-dimensional (3D) modeling. Removing hidden lines from the mesh plot is an essential process that produces explicit depth information. In this paper, a fast and effective method has been proposed for a time-frequency Spectrogram Mesh Surface Generation (SMSG) display, especially, based on the painter’s algorithm. In addition, most portable fault diagnosis devices have little function to generate a 3D spectrogram, which generally needs a general computer to realize the complex time-frequency analysis algorithms and a 3D display. However, general computer is not portable and then not suitable for field test. Hence, the proposed SMSG algorithm is applied to an embedded fault diagnosis device, which is light, low-cost, and real-time. The experimental results show that this approach can realize a high degree of accuracy and save considerable time.

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