Vibration Analysis-Based Diagnosis of High-Power Diesel Generator Turbocharger
Metaga Jeremi SOGOBA1, Badié DIOURTÉ2, Lamissa DIABATÉ3
1Metaga Jeremi SOGOBA, Department of Électromécanique, National School of Engineering, Bamako, Mali,
2Badié DIOURTÉ, Department of physique, Sciences techniques and technologies University, Bamako, Mali,
3Lamissa DIABATÉ, Department of Électromécanique, National School of Engineering, Bamako, Mali,
Manuscript received on 18 December 2018 | Revised Manuscript received on 27 December 2018 | Manuscript published on 30 December 2018 | PP: 63-66 | Volume-8 Issue-2, December 2018 | Retrieval Number: B5549128218/18©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The diesel engine of a high-power generator is equipped with two turbochargers. These are mounted on the gas exhaust above the diesel engine. Most investigative studies on vibration analysis of diesel power generators typically focused on the main bearing line in the diesel engine, on alternator rotor [1]. Turbochargers, however, play a very important role in the working of diesel engine. This article reports a study on the turbochargers of high-power diesel generator. A diesel engine and its turbochargers do not bear the same mechanic loads. While the diesel engine is the seat of violent shocks brought about by explosions in cylinders, the turbochargers are driven by the action of exhaust gas from explosions, without being affected by explosion shocks. Despite its limitations in diesel engine diagnosis, FFT method is adequate for a correct diagnosis of turbochargers. As a result, following several campaigns of measurements we experimentally defined minimal admissible vibration values for turbochargers, and we detected a defect in bearing among the turbochargers tested.
Keywords: Diesel Generator, FFT Method, High-Power, Turbocharger, Vibration.
Scope of the Article: Machine Learning