MEMS惯性测量单元的精确定标技术

在工程实际应用中,MEMS惯性测量单元的误差来源很多,噪声波动范围很大,温度特性和非线性严重;通过高低温实验,首先,分析系统的误差,建立系统的误差模型,在-30℃~+60℃范围内,进行全温度补偿;然后,分析噪声,根据实际要求,设计数字低通滤波器,对补偿后的数据进行滤波;结果显示,在满足工程实时性与动态特性要求的前提下,陀螺仪的零位补偿精度可以达到±0.03°以内,噪声波动范围可以控制在0.05°以内,加速度计的零位补偿精度达到±0.001g,满足工程实际要求,具有实用性!     

基于故障重构的故障识别

针对基于主元分析(Principal Component Analysis,PCA)的统计过程性能监测法,尽管不依赖于精确的数学模型,然而却限制了其在故障诊断方面的能力问题,在故障重构技术的基础上,研究了基于统计量的故障诊断问题,获得了主元子空间中故障可重构性的理论条件,提出了故障识别指标和诊断算法.通过对双效蒸发过程...     

非线性系统的多模型DMC解耦设计

针对工业生产过程大多为多输入多输出非线性系统,干扰因素多,耦合作用强,常规控制方法难以获得满意控制效果的特.提出一种基于动态矩阵控制(DMC)的多模型控制方法,采用误差指标切换函数作为切换准则,根据其最小值来选择与实际最接近模型,并将基于此模型的控制器切换为当前控制器.结合目标函数解耦方法,在模型中考虑其他通道输入对当...     

一阶常微分方程组加速算法及数值仿真

针对一阶常微分方程组提出了一种数值加速算法,给出了该算法的误差分析,并将该加速算法应用于求解太阳帆航天器轨道运动方程组。该算法实现简单,计算量小,计算精度较高。     

An eigenstructure-based 2D DOA estimation method using dual-size spatial invariance array

A sparse planar array vertically placed in y-z plane is proposed to improve the angle estimation accuracy of sources in low angle region with reflection multipath.With two sizes of spatial invariances along both dimensions,the array estimates the azimuth and elevation angles using unitary ESPRIT(estimation of signal parameters via rotational invariance techniques).The first spatial invariance with a displacement of half-wavelength yields unambiguous coarse estimates of high-variance,while the second spatial...     

基于继电保护测试仪的数据存储设计

为解决便携式继电保护测试仪在数据处理及存储方面的相关问题,提出基于USB芯片CH375的解决方案。通过分析CH375的命令集和工作时序,编写了MSP430处理器与U盘的数据通信应用程序。使用结果表明,由此构建的USB接口能够与各种U盘进行数据高速传输和存储。     

多中继通信系统中量化误差补偿的MMSE中继预编码方案

为了补偿量化误差造成的系统性能的降级,文中提出将Grassmannian码本量化误差的统计特性引入多中继系统有限反馈中继预编码的设计,首先在QoS要求下的完全反馈中继预编码与接收均衡MMSE两步优化算法的基础上,给出了有限反馈下量化误差补偿的中继预编码与接收均衡MMSE两步优化方案,进而文中在中继和功率约束下,提出了一种有限反馈下量化误差补偿的中继预编码与接收均衡MMSE联合优化方案,并给出了中继预编码矩阵设计的闭合表达式.计算机仿真表明,文中提出的中继和功率约束下量化误差补偿的MMSE联合优化方案的系统性能优于QoS要求下量化误差补偿的MMSE两步优化方案,而且相比没有采用量化误差补偿的MMSE联合优化方案可以获得更低的误码率性能.     

Reconstruction of intersecting curved solids from 2D orthographic views

This paper presents a new approach to reconstruct curved solids composed of elementary volumes intersecting with one another from three-view engineering drawings. Intersection curves arising from two intersecting curved surfaces are mostly higher order spatial curves, which cannot be described exactly by 2D orthographic projections and normally represented as smooth curves passing through several key points or even simplified as arcs or lines. Approximated sketches of higher order intersection curves in 2D views result in the invalidation of existing methods that need the exact projection information as input. Based on some heuristic hints, our method is able to recover the complete and correct half-profiles of the intersecting elementary volumes using the least traces left by them, which ensure the correctness of solution solids constructed finally. Several examples are provided to show the validation of the described method.     

Spectral element spatial discretization error in solving highly anisotropic heat conduction equation

This paper describes a study of the effects of the overall spatial resolution, polynomial degree and computational grid directionality on the accuracy of numerical solutions of a highly anisotropic thermal diffusion equation using the spectral element spatial discretization method. The high-order spectral element macroscopic modeling code SEL/HiFi has been used to explore the parameter space. It is shown that for a given number of spatial degrees of freedom, increasing polynomial degree while reducing the number of elements results in exponential reduction of the numerical error. The alignment of the grid with the direction of anisotropy is shown to further improve the accuracy of the solution. These effects are qualitatively explained and numerically quantified in 2- and 3-dimensional calculations with straight and curved anisotropy.     

An improved method for voice pathology detection by means of a HMM-based feature space transformation

This paper presents new a feature transformation technique applied to improve the screening accuracy for the automatic detection of pathological voices. The statistical transformation is based on Hidden Markov Models, obtaining a transformation and classification stage simultaneously and adjusting the parameters of the model with a criterion that minimizes the classification error. The original feature vectors are built up using classic short-term noise parameters and mel-frequency cepstral coefficients. With respect to conventional approaches found in the literature of automatic detection of pathological voices, the proposed feature space transformation technique demonstrates a significant improvement of the performance with no addition of new features to the original input space. In view of the results, it is expected that this technique could provide good results in other areas such as speaker verification and/or identification.