Unscented Kalman Filter Based State and Parameter Estimation in Percussive Drilling Systems

被引:0
|
作者
Song, Xianfeng [1 ]
Kane, Pascal-Alexandre [2 ]
Abooshahab, Mohanunad Ali [1 ]
机构
[1] Norwegian Univ Sci & Technol, Trondheim, Norway
[2] SINTEF Ind, Trondheim, Norway
关键词
Percussive drilling; Unscented Kalman Filter; State estimation; ROCK;
D O I
10.23919/chicc.2019.8865401
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Down-The-Hole (DTH) percussion tool is recognized for its high average rate of penetration (ROP), when drilling medium hard to very hard rock formations. This ROP which depends on the bit-rock contact conditions at the well bottom to efficiently transfer the impact energy to an intact rock can be maximized for certain parameter sets. including the static weight on bit (WOB, also known as thrust force/feed force). Indeed, recent experimental and numerical investigations of the bit-rock interface (BRI) have revealed an optimum WOB which is rooted in the dependence of the BRI law on the WOB force. That is an optimal state of pseudo-stiffness at the BRI can be obtained with the applied WOB for which the impact energy transmitted to rock is maximized. Therefore, accurate estimation and control of the BRI stiffness is crucial in order to optimize drilling operation. In this paper, a numerical solution is proposed which can estimate the state of drilling dynamics and evolving BRI stiffness. This approach combines a ID phenomenological percussive drilling model accounting for the longitudinal wave transmission during bit-rock interaction and a joint Unscented Kalman Filter (UKF) designed to simultaneously estimate the unknown parameters in the nonlinear BRI stiffness expression as well as the inaccessible states at the BRI. The results show that this approach has the potential to provide an accurate estimation of the percussive drilling dynamics and nonlinear BRI stiffness evolution over a wide range of initial conditions and static deformations that induced from changing WOB.
引用
收藏
页码:2149 / 2154
页数:6
相关论文
共 50 条
  • [21] USV Parameter Estimation: Adaptive Unscented Kalman Filter-Based Approach
    Shen, Han
    Wen, Guanghui
    Lv, Yuezu
    Zhou, Jun
    Wang, Linan
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2023, 19 (06) : 7751 - 7761
  • [22] SOC Estimation with an Adaptive Unscented Kalman Filter Based on Model Parameter Optimization
    Guo, Xiangwei
    Xu, Xiaozhuo
    Geng, Jiahao
    Hua, Xian
    Gao, Yan
    Liu, Zhen
    APPLIED SCIENCES-BASEL, 2019, 9 (19):
  • [23] Vehicle State Estimation Based on Adaptive Fading Unscented Kalman Filter
    Liu, Yingjie
    Cui, Dawei
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2022, 2022
  • [24] The Square-Root Spherical Simplex Unscented Kalman Filter for State and Parameter Estimation
    Tang, Xiaojun
    Zhao, Xiaobei
    Zhang, Xubin
    ICSP: 2008 9TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, VOLS 1-5, PROCEEDINGS, 2008, : 260 - 263
  • [25] Automated Design of an Unscented Kalman Filter for State- and Parameter Estimation on unknown Models
    Schweers, Christoph
    Kruse, Daniel
    Oesterwinter, Tobias
    Traechtler, Ansgar
    2013 INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND EMBEDDED SYSTEMS (CARE-2013), 2013,
  • [26] A novel battery state estimation model based on unscented Kalman filter
    Li, Jiabo
    Ye, Min
    Gao, Kangping
    Jiao, Shengjie
    Xu, Xinxin
    IONICS, 2021, 27 (06) : 2673 - 2683
  • [27] A parameter estimation method based on discontinuous unscented Kalman filter for non-smooth gap systems
    Zhu, Juntao
    Li, Tuanjie
    Wang, Zuowei
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2023, 204
  • [28] Dynamic State Estimation of Power Systems with Uncertainties Based on Robust Adaptive Unscented Kalman Filter
    Hou, Dongchen
    Sun, Yonghui
    Wang, Jianxi
    Zhang, Linchuang
    Wang, Sen
    JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY, 2023, 11 (04) : 1065 - 1074
  • [29] An improved unscented Kalman filter based dynamic state estimation algorithm for electric distribution Systems
    Ahmad, Fiaz
    Rashid, Kabir Muhammad Abdul
    Rasool, Akhtar
    Ozsoy, Esref Emre
    Sabanovic, Asif
    Elitas, Meltem
    COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING, 2017, 36 (04) : 1220 - 1236
  • [30] Dynamic State Estimation of Power Systems with Uncertainties Based on Robust Adaptive Unscented Kalman Filter
    Dongchen Hou
    Yonghui Sun
    Jianxi Wang
    Linchuang Zhang
    Sen Wang
    Journal of Modern Power Systems and Clean Energy, 2023, 11 (04) : 1065 - 1074