Intelligent on-line lubricants condition monitoring enabled by durable liquid-solid triboelectric nanogenerator

On-line lubricants condition monitoring can provide real-time machine/components working health status, which is essential for the development of smart machines to eliminate the threatening on humans’ life and health from unexpected and fatal failures of machines/components.

Existing on-line lubricants condition monitoring sensors have problems of low accuracy, restricted to one special contaminant detecting, too large and unwieldy, etc.

Recently studies proved that triboelectric nanogenerator (TENG) had the capability to detect tiny change of different fluids.

In the proposed project we will aim at achieving size adaptable and integrated oil-solid TENG (O-TENG)-based sensors for on-line condition monitoring  different properties of lubricants, e.g., water concentration, anti-oxidation level, wear particle size and concentration, viscosity, etc.

We will elucidate the effects of the physicochemical properties of oils, the sold surface properties, and their interactions on the signal output of O-TENG.

We will also address the challenge of detecting and identifying each contaminant in lubricating oils and clarify the effect of contact area, wetting behavior and their coupling on the performance of O-TENG.

At the same time, we will study the O-TENG’s triboelectric charging mechanism and its time-evolution and space- evolution from molecular level to macro scale