Abstract

In order to study the tribological properties of PTFE modified by hard nanoparticles and soft polymer under dry friction conditions, the tribological properties of polytetrafluoroethylene (PTFE) filled with different volume contents of polyether ether ketone (PEEK) and nano-ZrO2 were investigated at a linear speed of 2 m/s, normal load of 200 N, and ambient temperature conditions for 60 min using a block-on-ring wear tester. A multiple-layer feedforward artificial neutral network (ANN) was used to simulate and analyze the friction coefficient and volume wear rate. The results showed that the friction coefficient and volume wear rate of PTFE composites were effectively reduced when nano-ZrO2 and PEEK were filled separately or simultaneously. The best tribological properties were obtained when the composites were filled with 5–8 vol% nano-ZrO2 and 20 vol% PEEK simultaneously; the volume wear rate was only 1.29 × 10−6 mm3/Nm and the friction coefficient was only 0.15. An ANN can accurately simulate and predict the friction coefficient and volume wear rate of composites, and the predicted results were consistent with the experimental results. A groove appeared in the volume wear rate simulation diagram when the volume content of nano-ZrO2 was about 7% with or without PEEK. This phenomenon indicates that the composites in this region had a lower volume wear rate. Therefore, the addition of nano-ZrO2 and PEEK can effectively improve the tribological properties of PTFE. As a simulation analysis method, an ANN can accurately analyze and predict the tribological properties of composites.

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