심해저 환경인자를 고려한 시험집광기 주행장치의 곱분해 기법 기반의 통계 모멘트를 이용한 효율적인 강건 최적설계

Abstract

A deep-sea manganese nodule miner consists of 4 parts: pickup device, crusher, disposal device and tracked vehicle. The tracked vehicle is an essential component in the self-propelled mining system moving on soft soil. Performances of the tracked vehicle are influenced by noise factors; track speed, seafloor slope, shear stress, bottom currents and reaction forces of flexible hose. It is necessary to adopt robust design method that improves performances as well as minimize the variation of performances due to noise factors. Robust design optimization using statistical moments based on multiplicative decomposition method, calculate statistical moments using explicit integral of kriging metamodel and probability density functions of noise factors, can accurately and efficiently search for the robust optimum. In this paper, we adopt robust design optimization using statistical moments based on multiplicative decomposition method for test miner tracked vehicle on collecting operation.