Vibration Based Gear Fault Diagnosis under Empirical Mode Decomposition and Power Spectrum Density Analysis

• Autorzy: Akram M. Ammar , Khushnood Shahab , Tariq Syeda Laraib , Ali Hafiz Muhammad , Nizam Luqman Ahmad

Identyfikatory

DOI

10.12913/22998624/111663

• Języki publikacji: EN

Abstrakty

EN

Rotating machinery plays a significant role in industrial applications and covers a wide range of mechanical equipment. A vibration analysis using signal processing techniques is generally conducted for condition monitoring of rotary machinery and engineering structures in order to prevent failure, reduce maintenance cost and to enhance the reliability of the system. Empirical mode decomposition (EMD) is amongst the most substantial non-linear and non-stationary signal processing techniques and it has been widely utilized for fault detection in rotary machinery. This paper presents the EMD, time waveform and power spectrum density (PSD) analysis for localized spur gear fault detection. Initially, the test model was developed for the vibration analysis of single tooth breakage of spur gear at different RPMs and then specific fault was introduced in driven gear under different damage conditions. The data, recorded by means of a wireless tri-axial accelerometer, was then analyzed using EMD and PSD techniques and the results were plotted. The results depicted that EMD algorithms are found to be more functional than the ordinarily used PSD and time waveform techniques.

Słowa kluczowe

EN

spur gears; tooth breakage; vibration amplitude; empirical mode decomposition; power spectrum density; time waveform

PL

koła zębate czołowe; pękanie zęba; amplituda drgań; rozkład w trybie empirycznym; gęstość widmowa mocy; przebieg czasowy

• Wydawca: Lublin University of Technology ; Polish Society of Ecological Engineering (PTIE), Branch of PTIE in Lublin
• Czasopismo: Advances in Science and Technology. Research Journal
• Rocznik: 2019
• Tom: Vol. 13, no 3
• Strony: 192--200
• Opis fizyczny: Bibliogr. 38 poz., fig.

Twórcy

autor

Akram M. Ammar

• Department of Mechanical Engineering, University of Engineering and Technology, Taxila, Pakistan

autor

Khushnood Shahab

• Department of Mechanical Engineering, University of Engineering and Technology, Taxila, Pakistan

autor

Tariq Syeda Laraib

• Department of Mechanical Engineering, University of Engineering and Technology, Taxila, Pakistan

autor

Ali Hafiz Muhammad

• Department of Mechanical Engineering, University of Engineering and Technology, Taxila, Pakistan

autor

Nizam Luqman Ahmad

• Department of Mechanical Engineering, University of Engineering and Technology, Taxila, Pakistan

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).