共查询到18条相似文献,搜索用时 125 毫秒
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提出一种控制氧化铝下料间隔来跟踪和适应电解槽槽况变化的方法,将槽电阻控制在较理想状态以保证槽况与氧化铝浓度的匹配。这种方法利用氧化铝加料量与槽电阻之间的关系建立特征模型,采用仿人智能控制算法与模糊控制算法相结合控制氧化铝下料间隔以适应当前槽况,实现铝电解槽的优化生产。 相似文献
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在焊缝跟踪过程中存在多种噪声干扰,严重影响焊缝位置信息的准确提取。以碳钢平板对接焊为试验对象,通过提取脉冲涡流检测信号波形的峰值和过零时间实现对焊缝位置参数的检测。为避免噪声特性的不确定性对卡尔曼滤波焊缝跟踪的影响,使用径向基(RBF)神经网络优化卡尔曼滤波算法,以卡尔曼滤波状态参量作为网络输入,滤波误差作为网络输出,建立RBF神经网络训练过程。利用训练好的RBF神经网络输出修正的卡尔曼滤波值,补偿焊缝中心滤波误差。试验结果表明,采用RBF神经网络优化的卡尔曼(Kalman)滤波焊缝修正方法能够减小噪声对测量数据的影响。通过修正脉冲涡流测量数据,获得更为精确的焊缝中心位置,提高了焊缝跟踪精度。 相似文献
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针对紧密对接微间隙焊缝,分析基于磁光成像的神经网络补偿卡尔曼滤波(kalman filtering compensated by neural network,NN-KF)跟踪算法,建立焊缝位置测量模型并运用卡尔曼滤波对焊缝位置偏差进行最优预测.卡尔曼滤波进行最优估计需建立准确的系统模型和观测模型,而在焊缝跟踪过程中,系统噪声具有非先验性.对于针对测量模型误差、过程噪声和测量噪声对卡尔曼滤波结果的影响,运用反向传播(back propagation,BP)神经网络对卡尔曼滤波结果进行修正,补偿模型误差及噪声统计不确定性造成的滤波误差.结果表明,BP神经网络补偿卡尔曼滤波算法能有效抑制滤波发散,减小噪声干扰影响,提高焊缝跟踪精度. 相似文献
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《焊接学报》2017,(1)
针对紧密对接微间隙焊缝,分析基于磁光成像的神经网络补偿卡尔曼滤波(kalman filtering compensated by neural network,NN-KF)跟踪算法,建立焊缝位置测量模型并运用卡尔曼滤波对焊缝位置偏差进行最优预测.卡尔曼滤波进行最优估计需建立准确的系统模型和观测模型,而在焊缝跟踪过程中,系统噪声具有非先验性.对于针对测量模型误差、过程噪声和测量噪声对卡尔曼滤波结果的影响,运用反向传播(back propagation,BP)神经网络对卡尔曼滤波结果进行修正,补偿模型误差及噪声统计不确定性造成的滤波误差.结果表明,BP神经网络补偿卡尔曼滤波算法能有效抑制滤波发散,减小噪声干扰影响,提高焊缝跟踪精度. 相似文献
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针对轮式移动机器人在实际的轨迹跟踪任务中存在传感器测量误差且测量噪声统计信息获取困难的情况,文章首先基于自适应扩展卡尔曼滤波算法(EKF)融合惯性传感器、地磁传感器与编码器的数据。在不需要传感器测量噪声协方差先验知识的情况下获取位姿数据的同时抑制了传感器测量噪声不稳定变化对位姿数据精度的影响;其次在机器人运动学模型的基础上,构造了具有全局稳定的双环轨迹跟踪控制器。仿真与实验表明,数据滤波与全局稳定轨迹跟踪控制器结合的控制器效果良好。 相似文献
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基于卡尔曼滤波的焊缝偏差实时最优估计 总被引:1,自引:1,他引:0
建立了基于卡尔曼滤波的焊缝偏差实时最优估计算法.以焊缝中心位置为特征矢量,建立焊缝位置检测的状态方程和测量方程,并依据最小均方差原则建立了卡尔曼滤波最优估计的递推算法.测量噪声协方差由传感器测量误差的统计值得到,假定过程噪声是由于加速度变化引入,通过两点法确定焊缝中心位置的初值.在焊接过程中,应用卡尔曼滤波消除噪声干扰,实现焊缝位置的实时精确预测.计算机仿真和试验结果表明,焊缝偏差信号经过卡尔曼滤波处理后,消除了偶然因素和随机噪声的影响,提高了跟踪精度以及系统工作的稳定性,适合实际工程应用.Abstract: The optimal estimation algorithm for real-time welding deviation based on Kalman filtering is presented. The state equation and measurement equation for detecting the weld position is established, and the optimal estimation of the Kalman filtering recursive algorithm also is established according to the principle of minimum mean square error. Measurement noise covariance is obtained from the statistical value of measurement error, and after the process noise is supposed to derive from the changes in acceleration, the initial values of the welding center position are determined by the twopoint method. During the welding process, the welding position is accurately predicted while the noise interference is eliminated by Kalman filtering. The computer simulation and experiment results show that the weld deviation signal processed by the Kalman filtering can eliminate the disturbance of causal factors and random noise,improve the tracking precision and the stability of system, and be suitable for the practical engineering applications. 相似文献
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An application of a recursive Kalman filtering algorithm in rotating machinery fault diagnosis 总被引:3,自引:1,他引:3
In this paper, an application of adaptive order tracking fault diagnosis technique based on recursive Kalman filtering algorithm is presented. Order tracking fault diagnosis technique is one of the important tools for fault diagnosis of rotating machinery. Conventional methods of order tracking are primarily based on Fourier analysis with reference to shaft speed. In this study, a high-resolution order tracking method with adaptive Kalman filter is used to diagnose the fault in a gear set and damaged engine turbocharger wheel blades. The adaptive Kalman filtering algorithm can overcome the problems encountered in conventional methods. The problem is treated as the tracking of frequency-varying bandpass signals. Ordered amplitudes can be calculated with high resolution after experimental implementation. Experiments are also carried out to evaluate the proposed system in gear-set defect diagnosis and engine turbocharger wheel blades damaged under various conditions. The experimental results indicate that the proposed algorithm is effective in fault diagnosis of both cases. 相似文献
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为了使机器人视觉伺服控制系统的目标跟踪精度得到进一步提高,构建一种基于开关卡尔曼滤波器的视觉伺服控制系统。研究视觉伺服的目标跟踪原理,推导相关的数学模型,并分析跟踪误差产生的原因;针对图像采集和处理引入的延时问题,通过卡尔曼滤波估计得到目标运动的速度信息,以此作为前馈量输入视觉伺服控制器,补偿由于目标运动和延时造成的跟踪误差;为了解决卡尔曼滤波器由于目标运动的突然变化而降低估计性能的问题,引入运动监视器以在目标运动突然变化时发出开关信号并重置卡尔曼滤波器;最后对该算法进行实验与仿真。结果表明:基于卡尔曼滤波器的视觉伺服控制器能把跟踪误差控制在1 mm以内,而开关卡尔曼滤波器能有效地减少因目标运动状态突然变化而产生的跟踪误差。 相似文献
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针对间隙小于0.05 mm的低碳钢对接焊缝,用磁光传感方法获取焊缝位置信息,研究多新息理论优化卡尔曼滤波在焊缝识别及跟踪中的应用.在获取磁光图像及提取焊缝位置的过程中存在较多干扰,而传统卡尔曼滤波受噪声的影响较大,难以对焊缝偏差进行最优估计.为此,结合多新息理论,提出一种焊缝位置检测的卡尔曼滤波改进算法,在对当前时刻进行预测时,充分考虑之前多个时刻的运动状态,综合历史数据估计出焊缝位置信息,对不同新息值进行试验比较并考虑计算量和滤波精度,发现选用两个新息值优化卡尔曼滤波算法可得到较好的效果.结果表明,多信息理论优化卡尔曼滤波算法可有效提高焊缝位置检测精度. 相似文献
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《Science & Technology of Welding & Joining》2013,18(1):103-109
AbstractA seam tracking method is presented based on the estimation of weld position during the gas tungsten arc welding process. Kalman filtering of the weld pool images from a visual sensor is applied to compute recursively the solution to the weld position equations which are established based on an estimation of the centroid position of the weld pool images. This centroid, the position of which corresponds with the weld position, is extracted as the measurement eigenvector. The evolution of the weld position data from the weld pool images can be described through an appropriate process model, so that the weld position can be detected by applying a Kalman filter. This allows adjustment of the welding torch position in real time, which may significantly reduce processing time and promote seam tracking accuracy. Simulations and actual welding experiments have demonstrated the effectiveness of the proposed algorithm in the presence of weld pool image noise and have demonstrated the robustness of weld position detection for seam tracking. 相似文献
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结合均值滤波器和中值滤波器各自在图像去噪中的优点,借助阈值图像分割思想,提出一种阈值开关空域滤波器设计新思想.在该滤波器设计中,先求解模块中未被噪声污染的像素点占模板总像素数的比值,然后设置一个阈值并用该阈值将比值划分为不同的分段,最后对每个分段采用不同空域滤波算法.将本设计方法与标准中值滤波、算术均值滤波以及修正的阿尔法均值滤波器进行仿真分析.实验结果表明,这种设计方法在图像去噪与保留细节方面都有很好的效果,即使是高密度的噪声,采用较小窗口滤波,也能取得较好的除噪效果. 相似文献