Wear Monitoring of Connecting Rod Bearing via Air-Borne Method Analyzed by Using I-Kaz^TM Multi Level Value

Abstract:

Different techniques have been developed in the area of bearing wear monitoring. This paper proposes a different experimental study on bearing wear monitoring by using an airborne technique. The data captured in the airborne technique will be analyzed by using I-kaz^TM Multi Level (⁷Z) coefficient and then will be correlated with the conventional specific wear rates, K. The wear tests were carried out by using a pin-on-disc configuration at a sliding speed of 7.85 m/s. A set of sliding distance ranging from 20 160 km at a fixed load of 200 N was utilized and the K value was measured at every interval of 20 km for the speed. SAE40 type lubricant was used in the test to simulate the actual operation of the connecting rod bearing. The audio range frequency below 20 kHz in the airborne technique was obtained through a microphone 40SC type which was placed 10 mm from the pin-disc contact. The analysis result showed that the wear rate, K increased from 1.82 to 6.70x10^-8 mm³/Nm as the sliding distance increased, indicating that a mild-abrasion wear regime had occurred. The curve fitting of K as a function of I-kaz^TM Multi Level coefficient showed a similarity to an established of Taylor Tool Life curve. Thus, it was possible to correlate the Taylor curve and worn bearing, mainly in monitoring and identifying the bearing condition with respect to the sliding distance. The trend of I-kaz^TM Multi Level coefficient was found to be consistent with the increase of sliding distance which indicates that the I-kaz^TM Multi Level value can positively be used as wear response indicator for bearing.

• Periodical: Advanced Materials Research (Volume 445)
• Pages: 941-946
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.445.941
• Online since: January 2012
• Authors: Zailan Karim, Mohd Zaki Nuawi, Jaharah A. Ghani, Shahrum Abdullah, Mariyam Jameelah Ghazali
• Keywords: Airborne Technique, Condition Monitoring, I-Kaz, Signal Processing, Wear

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