用于骨科手术机器人的电磁定位方法

针对计算机辅助骨科手术,提出了基于磁偶极子模型的电磁定位方法.该方法以交流线圈为发射源,由电磁定律,接收线圈会产生感应电动势.由磁偶极子模型计算出磁场的空间分布,推导出包含目标位置和方向信息的方程组,利用非线性算法来解方程,从而得到一个稳定的、实时的定位方法.通过仿真验证该模型所需的方程数,实验结果表明该方法是有效的,...     

舰艇磁场磁偶极子阵列数学模型研究

为提高舰艇磁性防护能力,准确反映其磁场特性,舰艇测磁需要使用先进的测磁技术,这就可以用磁偶极子阵列模拟舰艇磁场源;文中根据舰艇测量面上的磁场数据建立了舰艇磁场换算的数学模型,给出一种运用实例评述测磁技术在舰艇磁性防护中的应用;实例结合点阵式大平面测磁法和磁荷模拟算法建立了测磁后舰艇磁场换算的数学模型,简单论述了该模型的数学原理、磁场函数计算方法及具体应用中有关参数的确定方法等,并对计算精度作了分析,仿真结果表明模型精度较高;测磁技术的应用在磁性防护中具有重要的实用价值。     

电磁定位系统中发射线圈半径优化设计

电磁定位系统中通常以多匝线圈来作为发射装置,以磁偶极子定位模型为基础来实现电磁定位技术.然而传统计算电磁定位的方式,只是将多匝线圈的半径简单归一化为一常数r,而忽视了线圈与线圈之间的差异性.对多匝发射线圈建立起多磁偶板子模型,并利用该模型来修正传统计算公式中多匝发射线圈的半径.仿真实验计算多匝线圈的磁感应强度表明,在环数一定的情况下,随着层数的增加,优化后的效果越明显,对计算接收线圈的感应电动势更为准确.     

胶囊内窥镜磁定位算法改进及实验研究

针对胶囊内窥镜磁定位磁场计算模型复杂和实时性较差的问题,提出了一种逆推定位算法.在胶囊内窥镜磁偶极子模型基础上,建立了磁定位系统数学模型,采用一种快速的定位求解算法,以最小二乘法构建磁定位目标函数,根据阵列磁阻传感器的输出电压,通过线性算法计算出胶囊内窥镜中永磁体位置和方向的一个初值,使用非线性算法进行迭代,求解胶囊内窥镜永磁体位姿最优解,简化了定位算法的复杂度,实时性得到大大提高.同时搭建胶囊内窥镜磁定位系统,实验结果表明该设计是可行和有效的.     

一种新的运动磁目标定位算法

给出了一种简单实用的运动磁目标定位算法.基于目标磁偶极子模型下的磁场表达式,推导出了目标相对于传感器的方位角的通用解析表达式,将求解目标方位角的问题转化为求解目标磁场的方向角和两者的偏差角的问题,从而实现利用单个静止的平面四轴磁通门传感器实现目标定位.实验结果表明该方法是切实有效的,而且实时性和可靠性好,估计的方位角的...     

基于低频电磁波的管道机器人定位技术

针对浅海海底泥面下管道维护要求及管道对普通电磁波的屏蔽特点,给出了基于磁偶极子模型的超低频电磁波磁场分布,提出了基于超低频电磁波的多传感器管道机器人示踪定位模型.根据超低频电磁波磁场对称分布的特点,给出了求解低频电磁波发射源位置参数的DLM离散非线性最小二乘迭代算法,及迭代算法的初值计算方法.实验表明,用该迭代初值进行DLM迭代,能够收敛到期望的局部最小值,能够计算超低频波发射源的位置,实现管道机器人的示踪定位问题.     

电磁跟踪系统大型三轴正交磁敏传感器设计

为了增加六自由度电磁跟踪系统定位距离,克服球形磁芯传感器大型化设计的制约因素,在验证方环线圈磁场分布规律满足磁偶极子定位原理的基础上,提出了一种大型三轴正交方环结构磁敏传感器的设计方案.综合考虑了磁芯材料、导线线径、匝数等影响因素,研制了一套大型三轴正交磁敏传感器,并进行了远距离跟踪定位实验,验证了所设计磁敏传感器的有效性和应用前景.     

磁偶极子源的被动测距与跟踪

基于电磁波在海水中的传播方程,分析了海水中磁偶极子辐射场的分布特性,建立了运动磁遇极子的测量坐示系并推导出被动测距方程,提出了基于磁偶极子源的三维被动测距方法及非线性最小二乘被动跟踪算法,通过对最小二乘算法的分析比较,利用离散型Levenberg-Marquardt算法对所建立的三维被动测距数学模型进行了仿真计算。结果表明,在水下有效测距离范围内,利用磁有子辐源进行被动测距与跟踪的方法是有效的,具有较高的测距精度。     

一种新的相干源波达方向估计算法

本文介绍了一种相干源渡达方向估计的新方法.由于相干源的对消而造成的数据协方差矩阵的秩缺损,经典的MUSIC不能分类相干源.只能生成等效源.我们的方法是首先用数据减去等效源,然后再递归使用该方法,依次找到相干源.模拟实验表明,相比方法,这种方法具有更优的定位性能.     

三磁偶极子磁体舰船磁场仿真

针对磁偶极子阵列对舰船磁场建模需要磁偶极子数量较多,排列复杂,在工程较难实现的问题,首次提出用三个磁偶极子对舰船磁场进行建模.建模过程首先选定磁偶极子位置,然后用最小二乘法计算磁矩,计算并仿真舰船磁场,最后分析仿真磁场与水雷动作参数之间关系,结果表明用三个磁偶极子建模得到的磁场在幅度上有一定的精度,而且磁场梯度较高,可以在低航速下模拟相对高速的舰船磁场通过特性.由于磁偶极子数较少,排列规则,在工程上有广阔的应用前景.     

漏磁检测传感器提离值的一种快速估计方法

在漏磁无损检测中,传感器的提离值是影响检测信号大小的一项重要因素.文章在使用ANSYS软件仿真得到漏磁场数据的基础上,结合磁偶极子模型和粒子群优化算法提出一种对霍尔传感器提离值的快速估计方法,并研究了磁化条件及缺陷大小对估计精度的影响.仿真结果表明:提离值的估计误差能达到5%,仿真时间仅2秒,为漏磁检测的实际应用提供了有效的分析方法.     

磁偶极子跟踪的渐进贝叶斯滤波方法

提出一种新的非线性滤波器应用于磁偶极子目标跟踪问题.建立了跟踪问题的状态空间模型, 在此基础上, 从高斯矩近似误差的角度分析了现有卡尔曼滤波更新在磁偶极子跟踪中的问题.对此, 将贝叶斯更新过程等效为求解连续时间上的渐进贝叶斯问题, 在线性高斯条件下推导了其解析解, 表明渐进贝叶斯更新可等效为定常系统的Kalman-Bucy滤波器; 进一步采用一阶Taylor展开得到非线性近似解表达式, 导出一种渐进贝叶斯滤波器, 从理论上分析了与现有方法的异同.仿真与实测磁目标跟踪试验结果表明, 渐进贝叶斯滤波器具有良好的精度和收敛性, 能够有效抑制磁目标跟踪中由于大初始误差导致的性能下降和滤波发散, 且计算效率与扩展卡尔曼滤波器相当, 适于实际应用.     

Localization of current dipole within a sphere by magnetic measurements

The principal objective of this study is the development of computer programs to determine the location and strength of neural electric activity within the brain from noninvasive magnetic field measurements at the surface of the head. This report presents theoretical calculations and computer programs derived from the method described by Williamson and Kaufman to determine the depth and strength of a current dipole in a sphere. From the location of the magnetic field radial component extremes, Br maximum and Br minimum, the orientation and location of the current dipole can be determined. The accuracy of the solution is dependent on precise location of of the magnetic field extremes as measured from the surface of a sphere, e.g. the head. To validate the program for locating the dipole, theoretical calculations and computer programs related to the total magnetic field vector resulting from a hypothetical current source within a homogeneous sphere were generated. The errors in calculations of the current dipole depth and strength are presented.     

Accuracy of two dipolar inverse algorithms applying reciprocity for forward calculation.

Two inverse algorithms were applied for solving the EEG inverse problem assuming a single dipole as a source model. For increasing the efficiency of the forward computations the lead field approach based on the reciprocity theorem was applied. This method provides a procedure to calculate the computationally heavy forward problem by a single solution for each EEG lead. A realistically shaped volume conductor model with five major tissue compartments was employed to obtain the lead fields of the standard 10-20 EEG electrode system and the scalp potentials generated by simulated dipole sources. A least-squares method and a probability-based method were compared in their performance to reproduce the dipole source based on the reciprocal forward solution. The dipole localization errors were 0 to 9 mm and 2 to 22 mm without and with added noise in the simulated data, respectively. The two different inverse algorithms operated mainly very similarly. The lead field method appeared applicable for the solution of the inverse problem and especially useful when a number of sources, e.g., multiple EEG time instances, must be solved.     

基于双十字形测量结构的磁信标定位方法

为解决地磁场对磁信标定位影响较大的问题,首先提出了一种两点式磁梯度张量解算运动载体位置的定位算法,然后通过对定位算法进行分析,设计出测量两点磁梯度张量的双十字形测量结构,最后建立关于以位置坐标为参数的非线性方程,利用粒子群算法得出目标位置的最优解。仿真结果表明磁信标与运动载体在单一坐标轴上的距离大于25 m时,磁传感器精度和信标磁矩对定位误差影响较大,在环境磁噪声影响下,当信噪比低于80 dB时,定位误差显著增大,基于双十字形测量结构的磁信标定位方法可有效消除地磁场和其他恒定磁场的影响。     

Real-time magnetic dipole detection with single particle optimization

In recent years, the use of magnetic field measurements has become relevant in several applications ranging from non-invasive structural fault detection to tracking of micro-capsules within living organisms. Magnetic measurements are, however, affected by a high noise due to a number of causes, such as interference from external objects and the Earth magnetic field. Furthermore, in many situations the magnetic fields under analysis are time-variant, for example because generated by moving objects, power lines, antennas, etc. For these reasons, a general approach for accurate real-time magnetic dipole detection is unfeasible, but specific techniques should be devised. In this paper we explore the possibility of using multiple 3-axis magnetic field sensors to estimate the position and orientation of a magnetic dipole moving within the detection area of the sensors. We propose a real-time Computational Intelligence approach, based on an innovative single particle optimization algorithm, for solving, with an average period of 2.5 ms, the inverse problem of magnetic dipole detection. Finally, we validate the proposed approach by means of an experimental setup consisting of 3 sensors and a custom graphical application showing in real-time the estimated position and orientation of the magnetic dipole. Experimental results show that the proposed approach is superior, in terms of detection error and computational time, to several state-of-the-art real-parameter optimization algorithms.