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首页> 外文期刊>Mechanical systems and signal processing >Identification of a scaled-model riser dynamics through a combined computer vision and adaptive Kalman filter approach
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Identification of a scaled-model riser dynamics through a combined computer vision and adaptive Kalman filter approach

机译：通过计算机视觉和自适应卡尔曼滤波方法的组合，确定比例模型立管动力学

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摘要

Aiming at overcoming the difficulties derived from the traditional camera calibration methods to record the underwater environment of a towing tank where experiments of scaled-model risers are carried on, a computer vision method, combining traditional image processing algorithms and a self-calibration technique was implemented. This method was used to identify the coordinates of control-points viewed on a scaled-model riser submitted to a periodic force applied to its fairlead attachment point. To study the observed motion, the riser was represented as a pseudo-rigid body model (PRBM) and the hypotheses of compliant mechanisms theory were assumed in order to cope with its elastic behavior. The derived Lagrangian equations of motion were linearized and expressed as a state-space model in which the state variables include the generalized coordinates and the unknown generalized forces. The state-vector thus assembled is estimated through a Kalman Filter. The estimation procedure allows the determination of both the generalized forces and the tension along the cable, with statistically proven convergence.
机译：为了克服传统相机标定方法记录拖曳水箱水下环境的困难，在此环境下进行了比例尺立管的实验，实现了一种将传统图像处理算法和自标定技术相结合的计算机视觉方法。该方法用于确定在比例模型立管上观察到的控制点坐标，该立管受到施加于其导缆索附着点的周期性力的作用。为了研究观察到的运动，将冒口表示为伪刚体模型（PRBM），并假设顺应性机理理论的假设以应对其弹性行为。将导出的拉格朗日运动方程线性化并表示为状态空间模型，其中状态变量包括广义坐标和未知广义力。通过卡尔曼滤波器估计由此组装的状态向量。估计程序可以确定广义力和沿电缆的张力，并具有统计证明的收敛性。

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  • 来源
    《Mechanical systems and signal processing》 |2014年第2期|124-140|共17页
  • 作者

    F.C. Trigo; E.R.R. Martins; A.T. Fleury; H.C. Silva Jr.;

  • 作者单位

    Escola Politecnica da Universidade de Sao Paulo, Av. Prof. Mello Moraes, 2231, CEP 05508-030 Sao Paulo, SP, Brazil;

    Escola Politecnica da Universidade de Sao Paulo, Av. Prof. Mello Moraes, 2231, CEP 05508-030 Sao Paulo, SP, Brazil;

    Escola Politecnica da Universidade de Sao Paulo, Av. Prof. Mello Moraes, 2231, CEP 05508-030 Sao Paulo, SP, Brazil,Centro Universitdrio da FEl, Av. Humberto de Alencar Castelo Branco, 3972, CEP 09851-000 Sao Bernardo do Campo, SP, Brazil;

    Institute de Pesquisas Tecnologicas do Estado de Sao Paulo, Av. Prof. Almeida Prado, 532, CEP 05508-070 Sdo Paulo, SP, Brazil;

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  • 正文语种 eng
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  • 关键词

    Shaping filter; Non-linear adaptive Kalman filter; Compliant mechanisms; Computer vision; Riser dynamics;

    机译：整形滤波器;非线性自适应卡尔曼滤波器顺应机制;计算机视觉;立管动力学;

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