Crack Fault Diagnosis for Spur Gears Using Gear Frequency-RPM spectrum

Happi, Kemajou Herbert Yakeu; Tchomeni, Bernard Xavier; Alugongo, Alfayo Anyika

doi:10.1109/icmimt52186.2021.9476182

Cited by 5 publications

(2 citation statements)

References 8 publications

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“…The gear mesh frequency 𝑓 𝑚 is 570 Hz, and the sample frequency 𝑓 𝑠 is 30 Hz. To study the dynamic response, the signal 𝑦(𝑡) is averaged across one of the gears with 𝑍 teeth rotating at a frequency of rotation 𝑓 𝑠 in Hz and a phase angle of 𝜃 𝑚 as specified in [26], with and without fault:…”

Section: Numerical Resultsmentioning

confidence: 99%

Experimental study and comparative analysis of pitting fault in spur gear system

Yakeu Happi,

Tchomeni Kouejou,

Anyika Alugongo

2023

J. vibroeng.

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This paper uses a dynamic six-degree-of-freedom model that considers torsional and lateral motions to predict the impact of pitting on vibration parameters in a spur gearbox for various operating speeds and torque loads. The study examines the dynamic characteristics of a gearbox with localized pitting damage on a single gear tooth using theoretical and experimental approaches. The research analyzes the forced vibrations of a single-stage spur gear system with pitting damage, which includes variations in mesh stiffness, damping, and gear error excitation, to identify symptoms of default. The equation of motion for the rotary gearbox system is established using the Lagrangian method in tandem with Short-Time Fourier Transform (STFT) and frequency-RPM map fault diagnosis. During real-time vibration monitoring, vibration signals are captured via accelerometers and processed in both the time and frequency domains using the LabVIEW data acquisition signal processing package to extract diagnostic information. The experimental findings demonstrate how vibration analysis combined with time-frequency processing can recognize machine conditions even in harsh operational conditions. Moreover, the experimental results indicate a significant similarity with the theoretical analysis and validate the effectiveness of the RPM frequency technique-based pitting detection method, which can be an asset in gear fault monitoring.

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Section: Numerical Resultsmentioning

confidence: 99%

Experimental study and comparative analysis of pitting fault in spur gear system

Yakeu Happi,

Tchomeni Kouejou,

Anyika Alugongo

2023

J. vibroeng.

Self Cite

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“…STFT approximates the instantaneous frequency of time-varying signals by windowing the signal as shown in formula (1), where x(m) is the input signal and ω(m) is the window function, and is a common method for analyzing nonstationary signals. However, due to its simple principle, it is difcult to make theoretical breakthroughs in engineering applications, and it is often used as an auxiliary or basic theoretical tool in the latest research [10][11][12]. Te biggest defect of STFT is that it is limited by the uncertainty criterion.…”

Section: Traditional Time-frequency Transform Short-timementioning

confidence: 99%

Application of Time-Frequency Analysis in Rotating Machinery Fault Diagnosis

Bai

Cheng

Wen

et al. 2023

Shock and Vibration

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Fault diagnosis is an important means to ensure the safe and reliable operation of mechanical equipment. In machinery fault diagnosis, collecting and mining the potential fault information of the vibration signal is the most commonly used method to reflect the operating status of the equipment. In engineering scenarios, in the face of rotating machinery with variable speed, simple time domain analysis or frequency domain analysis is difficult to solve the problem. The time-frequency analysis technology that combines time-frequency transformation and data analysis can solve practical engineering problems by capturing the transient information of the signal. At present, a large number of related literatures have been published in academic journals. This paper hopes to provide convenience for relevant researchers and motivate researchers to further explore by summarizing the published literature. First, this paper briefly explains the concept of time-frequency analysis and its development. Then, the time-frequency transformation method proposed for the characteristics of rotating machinery fault vibration signal and related works of literature are reviewed, and the key issues of the application of time-frequency transformation method in rotating machinery fault diagnosis are discussed. Next, this paper summarizes the relevant literature on the combination of data analysis technology and time-frequency transformation and sorts out its development route and prospects. The study reveals that time-frequency analysis technology is able to detect the rotating machinery fault effectively. The time-frequency analysis technology has made abundant achievements in the field of rotating machinery fault diagnosis. It is expected that this review would inspire researchers to explore the potential of time-frequency analysis as well as to develop advanced research in this field.

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