School of Information Science and Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China.
Sensors (Basel). 2023 May 16;23(10):4787. doi: 10.3390/s23104787.
Damping is an important factor contributing to errors in the measurement of rotational inertia using the torsion pendulum method. Identifying the system damping allows for minimizing the measurement errors of rotational inertia, and accurate continuous sampling of torsional vibration angular displacement is the key to realizing system damping identification. To address this issue, this paper proposes a novel method for measuring the rotational inertia of rigid bodies based on monocular vision and the torsion pendulum method. In this study, a mathematical model of torsional oscillation under a linear damping condition is established, and an analytical relationship between the damping coefficient, torsional period, and measured rotational inertia is obtained. A high-speed industrial camera is used to continuously photograph the markers on a torsion vibration motion test bench. After several data processing steps, including image preprocessing, edge detection, and feature extraction, with the aid of a geometric model of the imaging system, the angular displacement of each frame of the image corresponding to the torsion vibration motion is calculated. From the characteristic points on the angular displacement curve, the period and amplitude modulation parameters of the torsion vibration motion can be obtained, and finally the rotational inertia of the load can be derived. The experimental results demonstrate that the proposed method and system described in this paper can achieve accurate measurements of the rotational inertia of objects. Within the range of 0-100 × 10 kg·m, the standard deviation of the measurements is better than 0.90 × 10 kg·m, and the absolute value of the measurement error is less than 2.00 × 10 kg·m. Compared to conventional torsion pendulum methods, the proposed method effectively identifies damping using machine vision, thereby significantly reducing measurement errors caused by damping. The system has a simple structure, low cost, and promising prospects for practical applications.
阻尼是使用扭摆法测量转动惯量时产生误差的一个重要因素。确定系统阻尼可以将转动惯量的测量误差最小化，而对扭转振动角位移进行准确的连续采样是实现系统阻尼识别的关键。针对这一问题，本文提出了一种基于单目视觉和扭摆法的刚体转动惯量测量新方法。本文建立了线性阻尼条件下扭转振动的数学模型，得出了阻尼系数、扭转周期和测量转动惯量之间的解析关系。采用高速工业相机对扭转振动运动测试台上的标记进行连续拍摄。经过图像预处理、边缘检测和特征提取等几个数据处理步骤，借助成像系统的几何模型，计算出与扭转振动运动相对应的每帧图像的角位移。从角位移曲线上的特征点，可以得到扭转振动运动的周期和调幅参数，最终推导出负载的转动惯量。实验结果表明，本文提出的方法和系统可以实现对物体转动惯量的精确测量。在 0-100×10kg·m 的范围内，测量的标准偏差优于 0.90×10kg·m，测量误差的绝对值小于 2.00×10kg·m。与传统扭摆法相比，该方法通过机器视觉有效地识别了阻尼，从而显著降低了阻尼引起的测量误差。该系统结构简单、成本低，具有广阔的实际应用前景。
