AI‐Enabled Metal‐Polymer Plain Bearing Based on the Triboelectric Principle

With the rapid development of Internet Things and artificial intelligence (AI), requirement for sensing technologies smart bearings has increased dramatically. The general bearing sensors can only recognize basic information from temperature or vibration, far satisfying self-diagnosis self-maintenance. Recently, self-powered based on triboelectric nanogenerators have paved a new route fabricating bearings. In this study, principle is applied to commercial metal-polymer plain (MPPB) bearing, which achieve self-sensing, self-diagnosis, geometrical structure MPPB (T-MPPB) designed balance output efficiency external load, super durability load capability are verified. Besides, mechanism behind change trend under boundary hydrostatic fluid lubrication revealed first time. Furthermore, deep learning algorithm classify states with highly accurate performance. proposed T-MPPB potential self-maintenance lubricating pump according condition classified by AI. This research not establishes feasibility designing but also demonstrates way identifying states, thus achieving ability sensors.