围绕信号处理与传感系统的优化研究，本期精选发表在《仪器仪表学报》的5篇双语文章，欢迎阅读！
精选文章·Selected Articles
01
基于视觉感知的率失真优化算法
A rate-distortion optimization algorithm based on visual perception
【摘要】率失真优化在视频编码中起着关键作用，其目的是在压缩效率和视频质量失真之间取得平衡。现有的率失真算法主要针对视频中时间和空间冗余的消除，未充分考虑视频内容的主观感知冗余。本文提出了一种基于视觉感知的率失真优化算法，通过数据驱动的JND预测模型推导拉格朗日乘数因子，并使用显著性模型优化拉格朗日乘子权重系数，最终融合应用于率失真优化，并采用SW-SSIM评估视频质量，实现视频编码的感知优化。实验结果表明，与AVS3标准率失真算法相比，本文所提算法平均节省12.15%的码率，SW-SSIM提高了0.0043,有效降低了视频内容中的感知冗余，提高了视频感知质量和编码性能。
【Abstract】The rate-distortion optimization (RDO) plays a key role in video coding, which aims to achieve a tradeoff between compression efficiency and video quality distortion. The existing RDO algorithms mainly aim at eliminating temporal and spatial redundancies but ignore the subjective perception in video content, which results in a large number of perceptual redundancies in the video content. To address these issues, a rate-distortion optimization algorithm based on visual perception is proposed in this article. Firstly, the Lagrangian multiplier is obtained based on the data-driven just noticeable distortion prediction model, which is more in line with the perception of the human eye. Secondly, the Lagrangian multiplier weight coefficient is optimized based on the saliency model. Finally, the fusion of two models is applied to RDO, and the salience weighted-structural similarity index metric (SW-SSIM) is used to evaluate video quality and achieve the perceptual optimization of video coding. Compared with the third-generation audio and video coding standard algorithm, experimental results show that the proposed algorithm reduces the bit rate by 12.15% on average, and the SW-SSIM increases by 0.0043. Furthermore, the proposed algorithm reduces the perceptual redundancy in video content and improves the perceptual video quality and coding performance.
02
基于滑动聚类的多传感器异步信息融合方法
A sliding-clustering-based method for multi-sensor asynchronous information fusion
【摘要】传感器是智能检测和自动化装置中重要的部件组成，为了解决多传感器异步数据下的融合难题，提出了一种创新的基于滑动聚类的多传感器异步信息融合方法。首先引入了K-means聚类方法去容忍异步问题，主要利用曲线拟合给出一种简易的快速的判定法则以便实现实时聚类方法中的k值计算；其次设计了聚类滤波核从而在时空域上形成融合滑动管道，让数据的变化一直维持在一个能接受的误差之内，完整实现了实时多传感器信息融合方法。最后实验验证了设计的聚类融合方法的正确性以及合理性，实验证明了SC-MSIF方法是正确可行的，且在实时性方面具有较好的表现，相比较EKF和MEAN方法，SC-MSIF方法的RMSE误差减少了47.8%、36.3%,同时无人机中多传感器融合实际测试结果也较为优异。
【Abstract】Sensors are important components in intelligent detection and automation devices. To solve the problem of fusion under multi-sensor asynchronous data, an innovative sliding clustering-based multi-sensor asynchronous information fusion method is proposed. Firstly, a K-Means clustering method is introduced to tolerate the asynchronous problem, which mainly uses curve fitting to give a simple and fast rule of thumb for the calculation ofk-values in the real-time clustering method. Secondly, a clustering filtering kernel is designed to form a sliding pipeline for fusion in the spatial-temporal domain. In this way, the variation of data is always kept within an acceptable error, and the real-time multi-sensor information fusion method is fully implemented. Finally, the experiments validate the correctness and rationality of the designed clustering fusion method. The experiments show that the SC-MSIF method is correct and feasible and has a better performance in terms of real-time performance, and the RMSE error of the SC-MSIF method is reduced by 47.8% and 36.3% compared with the EKF and MEAN methods. The actual test results of multi-sensor fusion in UAVs are also better.
03
基于电磁力控制的非接触式二维力触觉再现系统
Non-contact two-dimensional haptic rendering system based on electromagnetic force control
【摘要】力触觉再现提供了操作者与虚拟物体间的双向信息和能量交互，有效提高了虚拟现实等应用系统的真实感、沉浸感和操作效率，成为人机交互的新兴技术和研究热点。本文实现了一种新型的基于电磁力控制的二维力触觉再现系统，该系统由二维背景电磁场产生和控制模块、指尖穿戴式永磁铁、人手位置检测模块和中央控制模块组成。基于ANSYS有限元分析，确定了系统中背景电磁铁线圈和指尖永磁铁的最优参数，获得指尖永磁铁所受电磁力与二维可控背景电磁铁驱动电流、指尖电磁铁位置的映射关系，形成离线仿真数据。提出了基于离线仿真数据实时插值的二维力触觉再现中电磁力控制方法。在实现系统原型的基础上，开展了作用力阈值感知基础实验和三维虚拟物体识别实验。实验结果表明，两种三维虚拟物体的识别实验成功率分别为85.7%和71.4%,有效验证了本文所设计力触觉再现方法的有效性。
【Abstract】Being a cutting-edge technique and hot topic in human-computer interaction, the haptic rendering provides bidirectional information and energy communication between human operators and the virtual environment (VE), which effectively enhances the level of reality and immersion and operating efficiency of virtual reality applications. This article proposes a novel two-dimensional (2 D) haptic interface through electromagnetic force control, which consists of the two-dimensional background electromagnetic field generation and control module, fingertip-mounted permanent magnet, position tracking module, and central control module. The optimized parameter configuration for the electromagnetic coils and fingertip magnet is obtained with the ANSYS-based finite element analysis, which further reveals the relationship between the electromagnetic force, the driving currents for the 2 D background magnetic field, and the position of the fingertip magnet. With the offline data for this relationship, a real-time interpolation-based force generation method is proposed for this 2 D haptic rendering. Based on the proposed haptic interface prototype system, several experiments are carried out, including the force perception threshold experiment, and virtual object recognition experiment. Experimental results verify the efficacy of the proposed 2 D haptic interface with the success rates for the two virtual object recognition experiments being 85.7% and 71.4%, respectively.
04
结构光检测点云精简与重构参数自动调节方法
Point cloud simplification and reconstruction parameters’ automatic adjustment method of structured light detection
【摘要】针对薄壁叶片的点云扫描采样会产生特征消失、三角重构会产生孔洞现象的问题，提出一种改进的点云精简以及重构的方法。首先，根据法向量夹角阈值和欧氏距离提取叶片外轮廓；其次，计算点云的平均曲率和高斯曲率，设定阈值对点云划分子集，采用索引空间法对点云数据进行精简；然后，采用贪婪算法针对距离阈值系数和三角形参数对叶片点云进行实验分析，得出没有孔洞的贪婪三角参数经验值；最后对距离阈值系数和点云平均间距拟合出关系式，实现贪婪重构的参数自动调节。实验结果表明，在总体精简率为90%左右时，相较于另外两种方法，标准偏差分别下降了26.45%和19.92%,外轮廓尺寸平均偏差分别下降了79.81%和47.97%。按照提出的方法设置重构参数，重构质量良好，对薄壁叶片实现在机智能加工检测具有良好的应用参考。
【Abstract】An improved point cloud simplification and reconstruction method is proposed to solve the problems of feature disappearance and hole phenomenon in point cloud scanning and sampling of thin-walled blades. Firstly, the outer contour of the blade is extracted according to the angle threshold of the normal vector and the Euclidean distance. Secondly, the average curvature and Gaussian curvature of the point cloud are calculated, the threshold is set to divide the point cloud into molecular sets, and the index space method is used to simplify the point cloud data. Then, the greedy algorithm is used to analyze the blade point cloud for the distance threshold coefficient and triangle parameters, and the empirical value of greedy triangle parameters without holes is obtained. The relationship between the distance threshold coefficient and the average distance of point cloud is fitted to realize the automatic adjustment of greedy reconstruction parameters. Compared with the other two methods, experimental results show that, when the overall reduction rate is about 90%, the standard deviation is reduced by 26.45% and 19.92%, and the average deviation of the outer contour dimension is reduced by 79.81% and 47.97%, respectively. The reconstruction parameters are set according to the proposed method, and the reconstruction quality is good, which has a good application reference for the realization of intelligent machining detection of thin-walled blades.
05
齿轮三维测量中线激光传感器位姿标定方法
A position and attitude calibration method for the linear laser sensor in gear 3D measurement
【摘要】在齿轮三维测量中，传感器位姿标定的结果直接影响测量结果的准确性。本文提出了一种基于特征标准件的线激光传感器位姿标定方法，并设计了一款具有一定几何特征的标准件。该方法解耦了传感器与仪器之间的位姿关系，通过运动过程中传感器与标准件的几何关系计算传感器的三个姿态角并调整至标定零位，然后通过多次偏置求等区域均值的方法依次计算传感器3个位置量的偏置距离。在齿轮测量中心上进行验证实验，多次标定后被测齿轮的齿廓偏差动态测量重复性为3.94μm,评价标准差小于0.3μm,且评价结果与传统接触式测量结果的趋势一致。结果表明，基于特征标准件的线激光传感器位姿标定方法使得齿轮三维测量具有较好的测量重复性与准确性。
【Abstract】In the 3D gear measurement, the position and attitude calibration of sensors directly affects the accuracy of measurement results. In this article, a position and attitude calibration method of the linear laser sensors is proposed, which is based on feature standard parts. And a standard part with certain geometric features is designed. This method decouples the position and attitude relationship between the sensor and the instrument. Through the geometric relationship between the sensor and the standard part during the movement, the three attitude angles of the sensor are calculated and adjusted to the calibrated zero position. Then, the offset distances of the three positions of the sensor are calculated through calculating equal region mean by multiple offsets. The verification experiment is implemented on the gear measuring center. After multiple calibrations, the dynamic measurement repeatability of the tooth profile deviation of the measured gear is 3.94 μm. The evaluation standard deviation is less than 0.3 μm. The evaluation results are consistent with the traditional contact measurement results, which show that the position and attitude calibration method of linear laser sensors based on feature standard parts has good repeatability and accuracy for the 3D gear measurement.
期刊推荐·Recommend Journal
《仪器仪表学报》(中文刊)创刊于1980年，由中国科学技术协会主管、中国仪器仪表学会主办，是中国仪器仪表领域的学术刊物，主要报道仪器仪表领域及其交叉学科具有创新性的基础理论研究、工程技术应用的优秀科研成果。
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