Normalization of gearbox vibration signal for tooth crack diagnosis under variable speed conditions

2021 ◽  
Author(s):  
Xingkai Yang ◽  
Peng Zhou ◽  
Ming J. Zuo ◽  
Zhigang Tian
Keyword(s):  
Vibration Signal ◽  
Variable Speed ◽  
Gearbox Vibration

scholarly journals A combined generalized Warblet transform and second order synchroextracting transform for analyzing nonstationary signals of rotating machinery

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kai Wei ◽  
Xuwen Jing ◽  
Bingqiang Li ◽  
Chao Kang ◽  
Zhenhuan Dou ◽  
...  
Keyword(s):  
Vibration Signal ◽  
Rotating Machinery ◽  
Second Order ◽  
Variable Speed ◽  
Short Time Fourier Transform ◽  
Stationary Characteristic ◽  
Nonstationary Signals ◽  
Time Frequency ◽  
Effective Technology ◽  
Short Time

AbstractIn recent years, considerable attention has been paid in time–frequency analysis (TFA) methods, which is an effective technology in processing the vibration signal of rotating machinery. However, TFA techniques are not sufficient to handle signals having a strong non-stationary characteristic. To overcome this drawback, taking short-time Fourier transform as a link, a TFA methods that using the generalized Warblet transform (GWT) in combination with the second order synchroextracting transform (SSET) is proposed in this study. Firstly, based on the GWT and SSET theories, this paper proposes a method combining the two TFA methods to improve the TFA concentration, named GWT–SSET. Secondly, the method is verified numerically with single-component and multi-component signals, respectively. Quantized indicators, Rényi entropy and mean relative error (MRE) are used to analyze the concentration of TFA and accuracy of instantly frequency (IF) estimation, respectively. Finally, the proposed method is applied to analyze nonstationary signals in variable speed. The numerical and experimental results illustrate the effectiveness of the GWT–SSET method.

Research on the Gear Box Fault Diagnosis of Self-Propelled Artillery Based on Vibration Signal Analysis

2014 ◽  
Vol 940 ◽  
pp. 136-139
Author(s):  
Ren Bin Zhou ◽  
Yong Feng Zhang ◽  
Jie Min Yang ◽  
Feng Ling
Keyword(s):  
Fault Diagnosis ◽  
Data Acquisition ◽  
Real Time ◽  
Signal Analysis ◽  
Great Influence ◽  
Vibration Signal ◽  
Vibration Data ◽  
Gearbox Vibration ◽  
Gear Box ◽  
Vibration Signal Analysis

As a universal component connection and power transmission gear box, is widely used in the modern industrial equipment, but also an easy failure parts, has a great influence on the running state of the working performance of the whole machine. This paper first analyzes the gear box fault form and characteristics, the gear box fault diagnosis method based on vibration signal analysis, and analysis of the vibration signal processing method for gear vibration signal analysis in time domain, including parameters, resonance demodulation method and cepstrum analysis method. Then using Visual C + + language and data acquisition card for real-time acquisition of gearbox vibration data software, including parameter setting, data acquisition module, signal real-time display module and data storage module. The data acquisition program is developed, the actual acquisition of gearbox vibration data of gear fault and bearing fault, and analyzed.

Application of EEMD Energy Distribution and Grey Incidence in Gearbox Fault Diagnosis

2013 ◽  
Vol 347-350 ◽  
pp. 430-433
Author(s):  
Wen Bin Zhang ◽  
Jia Xing Zhu ◽  
Ya Song Pu ◽  
Yan Jie Zhou
Keyword(s):  
Fault Diagnosis ◽  
Energy Distribution ◽  
Rank Order ◽  
Vibration Signal ◽  
Ensemble Empirical Mode Decomposition ◽  
Small Sample ◽  
Morphological Filter ◽  
Intrinsic Mode Functions ◽  
Vibration Signals ◽  
Gearbox Vibration

In this paper, a new comprehensive gearbox fault diagnosis method was proposed based on rank-order morphological filter, ensemble empirical mode decomposition (EEMD) and grey incidence. Firstly, the rank-order morphological filter was defined and the line structure element was selected for rank-order morphological filter to de-noise the original acceleration vibration signal. Secondly, de-noised gearbox vibration signals were decomposed into a finite number of stationary intrinsic mode functions (IMF) and some IMFs containing the most dominant fault information were calculated the energy distribution. Finally, due to the grey incidence has good classify capacity for small sample pattern identification; these energy distributions could serve as the feature vectors, the grey incidence of different gearbox vibration signals was calculated to identify the fault pattern and condition. Practical results show that the proposed method can be used in gear fault diagnosis effectively.

Application of Speed Transform to Diagnosis of Rotating Machinery With Varying Speeds

2015 ◽  
Author(s):  
Tingpeng Zang ◽  
Guangrui Wen ◽  
Guanghua Xu
Keyword(s):  
Fault Diagnosis ◽  
Vibration Signal ◽  
Rotating Machinery ◽  
Diagnostic Methods ◽  
Variable Speed ◽  
Dynamic Information ◽  
Simulated Signal ◽  
Transient Nature ◽  
Fault Features ◽  
Speed Up

The rotor startup vibration signals carry abundant dynamic information of the machinery and are very useful for feature extraction and potential early fault diagnosis. Due to the non-stationary and transient nature of the signals in speed up process, the traditional diagnostic methods that have been put forward based on stationary assumption are no longer satisfactory. This paper proposes a new Speed Transform based method for the fault diagnosis of rotating machinery in variable speed. Speed Transform decomposes a complicated signal over a basis of elementary oscillatory functions, whose frequencies follow the speed variation. The effectiveness of the proposed method is demonstrated by both simulated signal and startup vibration signal collected from a rotor system with early rub-impact fault. Analyzed results showed that the proposed method could effectively extract fault features of the rotor under varying speed condition.

scholarly journals Gearbox Vibration Signal Amplitude and Frequency Modulation

2012 ◽  
Vol 19 (4) ◽  
pp. 635-652 ◽  
Author(s):  
Fakher Chaari ◽  
Walter Bartelmus ◽  
Radoslaw Zimroz ◽  
Tahar Fakhfakh ◽  
Mohamed Haddar
Keyword(s):  
Vibration Signal ◽  
Signal Amplitude ◽  
Spur Gear ◽  
Main Task ◽  
Time Varying ◽  
Vibration Signals ◽  
Gearbox Vibration ◽  
Load Effects ◽  
Short Time ◽  
Load Conditions

Gearboxes usually run under fluctuating load conditions during service, however most of papers available in the literature describe models of gearboxes under stationary load conditions. Main task of published papers is fault modeling for their detection. Considering real situation from industry, the assumption of stationarity of load conditions cannot be longer kept. Vibration signals issued from monitoring in maintenance operations differ from mentioned models (due to load non-stationarity) and may be difficult to analyze which lead to erroneous diagnosis of the system. The objective of this paper is to study the influence of time varying load conditions on a gearbox dynamic behavior. To investigate this, a simple spur gear system without defects is modeled. It is subjected to a time varying load. The speed-torque characteristic of the driving motor is considered. The load variation induces speed variation, which causes a variation in the gearmesh stiffness period. Computer simulation shows deep amplitude modulations with sidebands that don't differ from those obtained when there is a defective tooth. In order to put in evidence the time varying load effects, Short Time Fourier Transform and then Smoothed Wigner-Ville distribution are used. Results show that the last one is well suited for the studied case.The experimental validation presented at the end of the paper confirms the obtained results. Such results offer useful information when diagnosing gear transmissions by avoiding confusing conclusions from vibration signals.

scholarly journals Dynamics simulation of mechanical gearbox vibration

2018 ◽  
Vol 234 ◽  
pp. 02002 ◽  
Author(s):  
Jan Furch ◽  
Cao Vu Tran
Keyword(s):  
Vibration Signal ◽  
Technical Condition ◽  
Dynamics Simulation ◽  
Virtual Model ◽  
Design Work ◽  
Practical Applications ◽  
3D Cad ◽  
Gearbox Vibration ◽  
The Cost ◽  
Multi Body

This paper focuses on creating a virtual model of mechanical gearbox used in medium-sized terrain vehicle using MSC.Adams software. This software is regarded as the most common and effective tool to simulate the gearbox as multibody system and to record and analyse the vibration signal from the gearbox. The paper makes an overview of modelling and simulation and performs an analysis with frequency spectrum. The paper demonstrates that it is possible to simulate vibration signals through the model of the gearbox created in 3D CAD software and then analyse in multi-body dynamics software MSC.Adams. Successful application of the virtual model not only help us decrease the cost of design work, but also help us identify the patterns of the vibration signal and the relations between the signal and the technical condition of the gearbox. The goal is to create a virtual model of a mechanical gearbox. In MSC.Adams, the vibration values of the rotating components can be detected in different gears. These values are then analysed and evaluated. The result is a simulation of fault states and identification of vibration frequencies for practical applications.

scholarly journals Condition Monitoring of Variable Speed Worm Gearbox Lubricated with Different Viscosity Oils

2015 ◽  
Vol 773-774 ◽  
pp. 178-182 ◽  
Author(s):  
Maznan Ismon ◽  
Izzuddin Zaman ◽  
Mohd Imran Ghazali
Keyword(s):  
Temperature Profile ◽  
Condition Monitoring ◽  
Vibration Amplitude ◽  
Sliding Friction ◽  
Vibration Signal ◽  
Worm Gear ◽  
Variable Speed ◽  
Monitoring Techniques ◽  
Different Types ◽  
Worm Gears

Over the years, condition monitoring of gear transmission systems have captured significant worldwide attention from both industries and academia. This is in light of the fact that an effective condition monitoring techniques will unquestionably extend the life span of the rotating equipment. In this research, both the vibration and temperature monitoring techniques were utilized to characterize the vibration behavior of worm gear as function of gear lubricant’s viscosity. Three different types of lubricant’s viscosity; VG100, VG460 and VG680 were used in the study to serve the sliding friction of worm gears. The predetermined speeds of electric motor at 900, 1150 and 1400 rpm were introduced to the gearbox prior to the measurement of vibration signal and temperature profile. The results revealed that a lubricant with higher viscosity contributes to less vibration amplitude. At 1150 rpm, it was recorded that the vibration amplitudes are higher compare to the other motor speeds, for all lubricant's types. In this case, VG100 showed the highest vibration amplitude followed by VG460 and VG680. This result was corroborated well with the obtained temperature profiles which are 35.0°C, 35.7°C and 39.3°C for the respective VG100, VG460 and VG680. Thus, concludes the correlation between the lubrication’s viscosity, vibration level, temperature profile and worm gear speed.

Gearbox Fault Detection Using Hilbert and TT-Transform

2005 ◽  
Vol 293-294 ◽  
pp. 79-86 ◽  
Author(s):  
Xianfeng Fan ◽  
Ming J. Zuo
Keyword(s):  
Fault Detection ◽  
Hilbert Transform ◽  
Detection Method ◽  
Vibration Signal ◽  
Fault Detection And Diagnosis ◽  
Time Representation ◽  
Machine Vibration ◽  
S Transform ◽  
Gearbox Vibration ◽  
Detection And Diagnosis

Machine vibration signal has been used in fault detection and diagnosis. Modulation and non-stationarity existing in the signal generated by a faulty gearbox present challenges to effective fault detection. Hilbert transform has the ability to address the modulation issue. This paper outlines a novel fault detection method called Hilbert & TT-transform (HTT-transform) which combines Hilbert transform and TT-transform obtained from the inverse Fourier transform of the S-transform. The principle of the proposed method is to analyze the modulating signal created by a faulty gear using a time-time representation. The method has the advantage of providing a new way of localizing the time features of the modulating signal around a particular point on the time axis through scaled windows. It is verified with simulated signals and real gearbox vibration signals. The results obtained by CWT, S-transform, TT- transform, and HTT-transform are compared. They show that utilizing the proposed method can improve the effectiveness of gearbox fault detection.

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