Optimization of torsion and wear characteristics on reinforced steel wire rope

Abstract

This work develops the optimization of torsional, wear, and fatigue life behaviors based on the hybrid emperor penguin social ski-driver for reinforced steel wire. Using granite and rutile particles reinforcement, steel wires are strengthened. Normal steel wire rope and reinforced wire rope are prepared with 7 strands and 15 wires. Using hybrid emperor penguin optimization-based social ski driver Optimization (Hybrid EPSSD), the failure tests such as wear analysis, fatigue life, and torsional behavior are optimized. Besides, the performances of the experimented wire rope are predicted by using hybrid Elman recurrent Neural Network-based EPO (Hybrid ERNN-EPO). Using the Matlab 2018a platform, the optimization and prediction processes are performed. In this, reinforced wire ropes deliver enhanced performances for both experimented and optimization behaviors. From the results, the reinforced wire rope has the best performance which possesses less wear rate, more fatigue life, and torsion behavior are obtained. The experimental outcome of wear depth for reinforced wire rope is 0.18 mm and the optimized wear depth outcome from the Hybrid EPSSD approach is 0.16 mm. For reinforced wire rope, the optimized fatigue life is 4.50 × 104 times at 500 KN and the maximum fatigue life experimentally is 4.20 × 104 times. At a particular hoisting time, the optimization value for the location of maximum torsion angle is 243 to 18 mm is obtained and the experimental values are 240 to 15 m. The reinforced wire rope has a better performance compared to the steel wire rope.