contributor author | Junyue Tang | |
contributor author | Zongquan Deng | |
contributor author | Qiquan Quan | |
contributor author | Shengyuan Jiang | |
date accessioned | 2017-12-16T09:22:44Z | |
date available | 2017-12-16T09:22:44Z | |
date issued | 2016 | |
identifier other | %28ASCE%29AS.1943-5525.0000619.pdf | |
identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4242098 | |
description abstract | Drilling and coring, due to their efficient penetrating and cutting removal characteristics, have been widely applied to planetary sampling and returning missions. In most autonomous planetary drilling, there are not enough prior seismic surveys on sampling sites’ geological information. Sampling drills may encounter uncertain formations of significant differences in mechanical properties. Additionally, given limited orbital resources, sampling drills may have a stuck fault under inappropriate drilling parameters. Hence, it is necessary to develop a real-time drilling strategy that can recognize current drilling conditions effectively and switch to appropriate drilling parameters correspondingly. A concept of planetary regolith drillability based on the rate of penetration (RoP) is proposed to evaluate the difficulty of the drilling process. By classifying different drilling media into several drillability levels, the difficulty level of drilling conditions can be easily acquired. A pattern recognition method of support vector machines (SVMs) is adopted to recognize drillability levels. Next, a set of suitable drilling parameters is tuned online to match the recognized drilling conditions. A multilayered simulant drilling test indicates that this drilling strategy based on drillability recognition can identify different drilling conditions accurately and have good environmental adaptability. | |
publisher | American Society of Civil Engineers | |
title | Real-Time Drilling Strategy for Planetary Sampling: Method and Validation | |
type | Journal Paper | |
journal volume | 29 | |
journal issue | 5 | |
journal title | Journal of Aerospace Engineering | |
identifier doi | 10.1061/(ASCE)AS.1943-5525.0000619 | |
tree | Journal of Aerospace Engineering:;2016:;Volume ( 029 ):;issue: 005 | |
contenttype | Fulltext | |