Developing a sustainable grease from jojoba oil with plant waste based nanoadditives for enhancement of rolling bearing performance.

This paper presents a novel grease from jojoba oil and activated carbon nanoparticles (ACNPs) extracted from banana peel waste. The raw jojoba oil and ACNPs are first characterized for structural properties. Samples of jojoba grease blended with 0.5 and 1.5 wt. % ACNPs are prepared and tested for physicochemical and tribological properties as compared to plain jojoba grease. Adding ACNPs to jojoba grease improves corrosion resistance from grade 2c to 1a while increasing the dropping point from 100 to 109 °C. ACNPs enhanced the viscosity of jojoba oil by up to 33% for testing temperature range of 40-100 °C. The load-carrying capacity of jojoba grease is increased by about 60% when blended with 1.5 wt.% ACNPs. The same blending decreased both the coefficient of friction and the wear scar diameter by 38% and 24%, respectively. A customized test rig is used to test the effectiveness of the grease samples in rolling bearing lubrication in terms of vibration levels and power consumption. The novel jojoba grease proved to show exceptional reductions power consumption reaching 25%. The vibration spectra show the absence of resonant peaks at high frequencies suggesting the capability of jojoba grease to form a stable full film lubrication.

Rolling element bearing fault identification using a novel three-step adaptive and automated filtration scheme based on Gini index.

For early detection of rolling element bearings (REBs) faults in contaminated signals, kurtosis-derived indices are involved in the filtration process prior to demodulation. However, they were found either sensitive to impulsive outliers or requiring many input arguments. In this study, a novel three-step adaptive and automated filtration scheme using Gini index (GI) is proposed as an alternative to kurtosis-based techniques to enhance the weak fault features and eliminate noise and interferences from the raw vibration signal. The proposed approach was tested using experimental signals with different bearing faults. The filtered signals were greatly denoised and the fault impulses were successfully isolated, which indicates the effectiveness of the proposed approach and the superiority of GI over kurtosis-derived indices as a criterion for proper filter design for REBs fault detection.