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首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Real-Time Monitoring of Jet Trajectory during Jetting Based on Near-Field Computer Vision
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Real-Time Monitoring of Jet Trajectory during Jetting Based on Near-Field Computer Vision

机译：基于近场计算机视觉的喷射过程中喷射轨迹的实时监控

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摘要

A novel method of near-field computer vision (NFCV) was developed to monitor the jet trajectory during the jetting process, which was used to precisely predict the falling point position of the jet trajectory. By means of a high-resolution webcam, the NFCV sensor device collected near-field images of the jet trajectory. Preprocessing of collected images was carried out, which included squint image correction, noise elimination, and jet trajectory extraction. The features of the jet trajectory in the processed image were extracted, including: start-point slope (SPS), end-point slope (EPS), and overall trajectory slope (OTS) based on the proposed mean position method. A multiple regression jet trajectory range prediction model was established based on these trajectory characteristics and the reliability of the model was verified. The results show that the accuracy of the prediction model is not less than 94% and the processing time is less than 0.88 s, which satisfy the requirements of real-time online jet trajectory monitoring.
机译：开发了一种新的近场计算机视觉方法（NFCV）来监视喷射过程中的喷射轨迹，该方法用于精确预测喷射轨迹的下降点位置。通过高分辨率的网络摄像头，NFCV传感器设备收集了射流轨迹的近场图像。对收集的图像进行了预处理，包括斜视图像校正，噪声消除和喷射轨迹提取。在提出的平均位置方法的基础上，提取了处理后的图像中喷射轨迹的特征，包括：起点斜率（SPS），终点斜率（EPS）和总轨迹斜率（OTS）。基于这些轨迹特征建立了多元回归射流轨迹范围预测模型，并验证了该模型的可靠性。结果表明，该预测模型的准确度不小于94％，处理时间小于0.88 s，满足了实时在线射流轨迹监测的要求。

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