A Fusion Kalman Filter and UFIR Estimator Using the Influence Function Method

In this paper, the Kalman filter(KF) and the unbiased finite impulse response(UFIR) filter are fused in the discrete-time state-space to improve robustness against uncertainties. To avoid the problem where fusion filters may give up some advantages of UFIR filters by fusing based on noise statistics, we attempt to find a way to fuse without using noise statistics. The fusion filtering algorithm is derived using the influence function that provides a quantified measure for disturbances on the res...     

Robust fault detection for discrete-time Markovian jump systems with mode-dependent time-delays

This paper investigates a fault detection problem for a class of discrete-time Markovian jump systems with norm-bounded uncertainties and mode-dependent time-delays. Attention is focused on constructing the residual generator based on the filter of which its parameters matrices are dependent on the system mode, that is, the fault detection filter is a Markovian jump system as well. The design of fault detection filter is reduced to H-infinity filtering problem by using H-infinity control theory, which can guarantee the difference between the residual and the fault (or, more generally weighted fault) as small as possible in the context of enhancing the robustness of residual to modeling errors, control inputs and unknown inputs. Sufficient condition for the existence of the above filters is established by means of linear matrix inequalities, which can be readily solved by using standard numerical software. A numerical example is given to illustrate the feasibility of the proposed method.     

Fault detection for a class of impulsive switched systems

The problem of fault detection for a class of nonlinear impulsive switched systems is investigated in this paper. Fault detection filters are designed such that the augmented systems are stable, and the residual error signal generated by the filters guarantees the H∞ performance for disturbances and faults. Sufficient conditions for the design of fault detection(FD) filters are presented by linear matrix inequalities. Moreover, the filter gains are characterized according to a solution of a convex optimization. Finally, an example derived from a pulse-width-modulation-driven boost converter is given to illustrate the effectiveness of the FD design approach.     

Consistent Kalman filters for nonlinear uncertain systems over sensor networks

In this paper, we study how to design filters for nonlinear uncertain systems over sensor networks. We introduce two Kalman-type nonlinear filters in centralized and distributed frameworks. Moreover, the tuning method for the parameters of the filters is established to ensure the consistency, i.e., the mean square error is upper bounded by a known parameter matrix at each time. We apply the consistent filters to the track-to-track association analysis of multi-targets with uncertain dynamics. A novel track-to-track association algorithm is proposed to identify whether two tracks are from the same target. It is proven that the resulting probability of mis-association is lower than the desired threshold. Numerical simulations on track-to-track association are given to show the effectiveness of the methods.     

Short text classification based on strong feature thesaurus

Data sparseness, the evident characteristic of short text, has always been regarded as the main cause of the low accuracy in the classification of short texts using statistical methods. Intensive research has been conducted in this area during the past decade. However, most researchers failed to notice that ignoring the semantic importance of certain feature terms might also contribute to low classification accuracy. In this paper we present a new method to tackle the problem by building a strong feature thesaurus (SFT) based on latent Dirichlet allocation (LDA) and information gain (IG) models. By giving larger weights to feature terms in SFT, the classification accuracy can be improved. Specifically, our method appeared to be more effective with more detailed classification. Experiments in two short text datasets demonstrate that our approach achieved improvement compared with the state-of-the-art methods including support vector machine (SVM) and Nave Bayes Multinomial.     

Intelligence evolution for service robot: An ADRC perspective

The strategy of active disturbance rejection control (ADRC) and its applications in intelligence evolution for service robot are summarized. It is also shown that the philosophy of ADRC is consistent with the essential characteristics of intelligence evolution. Most importantly, we concentrate on five core issues which will be encountered when applying ADRC to deal with intelligence evolution for service robot, that is, how to eliminate the impact of unknown composite disturbances, how to handle the nonholonomic constraints in uncalibrated visual servoing, how to realize eye hand torque coordination, how to deal with the disturbance in simultaneous localization and mapping (SLAM), and how to reject the imperfections induced by network in human robot interaction. The main purpose of this paper is to clarify the challenges encountered on intelligence evolution for service robot when one applies ADRC to, hoping that more and more researchers can give some suggestions or work together to deal with these problems, and flourishing results of ADRC from both theory and applications.     

机器人定位中的自适应粒子滤波算法

The research of robot localization aims at accuracy, simplicity and robustness. This article improves the performance of particle filters in robot localization via the utilization of novel adaptive technique. The proposed algorithm introduces probability retracing to initialize particle sets, uses consecutive window filtering to update particle sets, and refreshes the size of particle set according to the estimation state. Extensive simulations show that the proposed algorithm is much more effective than the traditional particle filters. The proposed algorithm successfully solves the nonlinear, non-Gaussian state estimation problem of robot localization.     

Automatic target detection by optimal morphological filters

It is widely accepted that the design of morphological filters,which are optimal in some sense,is a difficult task.In this paper a novel method for optimal learning of morphological filtering parameters(Genetic training algorithm for morphological filters,GTAMF)is presented.GTAMF adopts new crossover and mutation operators called the curved cylinder crossover and master-slave mutaition to achieve optimal filtering parameters in a global searching,Experimental results show that this method is practical,easy to extend,and markedly improves the performances of morphoological filters.The operation of a morphological filter can be divided into two basic problems including morphological operation and structuring element (SE)Selection.The rules for morphological operations are predefined so that the filter‘s properties depend merely on the selection of SE.By means of adaptive optimization training,structureing elements possess the shape and structural characteristics of image targets,and give specific information to SE.Morphological filters formed in this way become certainly intelligent and can provide good filtering results and robust adaptability to image targets with clutter background.     

Edit Propagation via Edge-Aware Filtering

This paper presents a novel framework for efficiently propagating the stroke-based user edits to the regions with similar colors and locations in high resolution images and videos.Our framework is based on the key observation that the edit propagation intrinsically can also be achieved by utilizing recently proposed edge-preserving filters.Therefore,instead of adopting the traditional global optimization which may involve a time-consuming solution,our algorithm propagates edits with the aid of the edge-preserve filters.Such a propagation scheme has low computational complexity and supports multiple kinds of strokes for more flexible user interactions.Further,our method can be easily and efficiently implemented in GPU.The experimental results demonstrate the efficiency and user-friendliness of our approach.     

Scratch-concerned yield modeling for IC manufacturing involved with a chemical mechanical polishing process

In existing integrated circuit (IC) fabrication methods,the yield is typically limited by defects generated in the manufacturing process.In fact,the yield often shows a good correlation with the type and density of the defect.As a result,an accurate defect limited yield model is essential for accurate correlation analysis and yield prediction.Since real defects exhibit a great variety of shapes,to ensure the accuracy of yield prediction,it is necessary to select the most appropriate defect model and to extract the critical area based on the defect model.Considering the realistic outline of scratches introduced by the chemical mechanical polishing (CMP) process,we propose a novel scratch-concerned yield model.A linear model is introduced to model scratches.Based on the linear model,the related critical area extraction algorithm and defect density distribution are discussed.Owing to higher correspondence with the realistic outline of scratches,the linear defect model enables a more accurate yield prediction caused by scratches and results in a more accurate total product yield prediction as compared to the traditional circular model.     

声表面波器件的反射特性及性能

为了准确分析反射型声表面波器件参数对其性能的影响,基于耦合模理论和P矩阵方法建立了器件的耦合模模型,分析得到器件的电反射特性即反射系数S11曲线,并在128°Y-X LiNbO3压电基片试制了频率为90 MHz的多种参数的器件,分析与测试结果表明:单个叉指换能器器件的S11中心频率为91.26 MHz,幅值为-20.58 dB,与理论分析结果91.44 MHz和-19.21 dB相近;带有反射栅的器件比单个叉指换能器件在中心频率处S11幅值增大约8.5 dB,谐振峰增多,时域曲线有明显的反射峰信号,验证了反射栅的反射特性;叉指换能器叉指对数减小使器件中心频率处的S11幅值减小,时域中的回波信号更尖锐,信噪比明显增大,表明对数较多的IDT具有较强的反射特性,对回波信号干扰较大,过小的叉指对数对器件声电转换效率影响很大,会使器件性能下降;较大的反射栅指条数对回波信号影响不大,但过小的指条数会降低反射栅反射系数,使得回波信号信噪比减小,纹波增多.     

Development of SAW based gyroscope with high shock and thermal stability

A novel surface acoustic wave (SAW)-based gyroscope with an 80 MHz central frequency was developed on a 128° YX LiNbO₃ piezoelectric substrate. The developed sensor was composed of a SAW resonator, metallic dots, and two SAW delay lines. A SAW resonator was employed to generate a stable standing wave with a large amplitude, metallic dots were used to induce a Coriolis force and to form a secondary SAW, and two delay lines were formed to extract the Coriolis effect by comparing the resonance frequencies between these two delay lines. Coupling of modes (COM) modeling was conducted to determine the optimal device parameters prior to fabrication. According to the simulation results, the device was fabricated and then measured on a rate table. When the device was subjected to an angular rotation, resonant frequency differences between the two oscillators were observed because of the secondary wave, generated by the Coriolis force, perturbed the propagation of the SAW in the sense element. Depending on the angular velocity, the difference of the resonance frequency was linearly modulated. The obtained sensitivity was approximately 172 Hz deg^?1 s^?1 at an angular rate range of 0–500 deg/s. Device performances depending on different mass weights and temperatures were also characterized. Good thermal and shock stabilities were observed during the evaluation process.     

Development of temperature-control system for liquid droplet using surface Acoustic wave devices

In this paper, we present a liquid-droplet-heating system using a surface acoustic wave (SAW) device. When liquid is placed on a Rayleigh-SAW-propagating surface, a longitudinal wave is radiated into the liquid. If the SAW amplitude increases, the liquid shows non-linear dynamics, such as vibrating, streaming, small droplet flying, and atomizing. This phenomenon is well known as SAW streaming. The liquid temperature is measured during the longitudinal wave radiation and found to increase. First, the mechanism of the liquid-heating effect is discussed on the basis of experimental results. The surface electrical condition is changed to investigate the effect of dielectric heating. The obtained results indicate that the radiated longitudinal wave causes liquid heating and the dielectric heating effect does not. Second, the fundamental properties of the liquid temperature are measured by varying the applied voltage, duty factor, and liquid viscosity. The liquid temperature is found to be proportional to the duty factor and the square of the applied voltage. Therefore, the liquid temperature can be controlled by these applied signals. Also, by using highly viscous solutions, the liquid temperature is increased to more than 100 °C. Moreover, for chemical applications, the possibility of periodic temperature control is tested by varying the duty factor. The obtained results strongly suggest that an efficient thermal cycler is realized. A novel application of the SAW device is proposed on the basis of SAW streaming.     

Solvation,transduction and independent component analysis for pattern recognition in SAW electronic nose

This paper revisits the fundamental basis for signal generation in polymer coated SAW vapor sensors and applies the independent component analysis (ICA) for feature extraction from the SAW sensor array data to explore whether the independent components could represent analyte-specific solvation parameters and whether they could form the feature vector for reliable pattern classification. Thermodynamic partitioning of analytes between vapor and polymer phases is treated as independent contributions from different solvation mechanisms, each associated with characteristic ‘environment swap’ energy. The overall equilibrium partition coefficient of an analyte is modeled as product of partial partition coefficients associated with different solvation mechanisms. The polymer films on SAW devices are treated to be acoustically thin. The theory of signal generation accounts for effects from both the mass as well as the viscoelastic loadings. It explains the signal amplification factor due to viscoelastic effects, and models the sensor signal to be proportional to the equilibrium partition coefficient. Thus, the logarithmic signal becomes a linear combination of the partial free energies associated with various solvation mechanisms. A linear-solvation-energy relationship (LSER) like factorization is assumed for the partial free energies where the latter are expressed as product of analyte and complimentary polymer associated solvation parameters. The problem of sensor array signal analysis is then treated as a blind source separation problem with the analyte solvation parameters being the independent sources, the polymer solvation parameters being the mixing weights and the log(signals) being the measured variables. The FastICA algorithm with Gram-Schmidt orthogonalization is applied to determine independent components. The principal component analysis (PCA) is done as pre-processing step for ICA. An experimental SAW sensor array data available in the literature [Rose-Pehrsson et al., Anal. Chem. 60 (1988) 2801–2811] is used to seek validation for our approach, and to examine the role of ICA in SAW sensor array signal processing. In brief, the paper establishes a direct relationship between the independent components and the analyte solvation parameters, and presents ICA as an effective method for feature extraction for pattern recognition in SAW electronic noses.     

基于WIFI的无线声表面波传感器信号采集系统

将声表面波传感器与信号无线保真(WIFI)技术相结合,提出了一种基于WIFI的无线声表面波传感器信号采集系统.该系统由声表面波传感器、信号调理电路、处理器、WIFI模块和无线接收终端组成.声表面波传感器混频后的信号经过信号调理电路后,转换为处理器可计频的低频方波信号,并通过WIFI模块将采集到的信号无线发送到接收终端.通过一个输出信号范围在100 kHz~350 kHz声表面波传感器信号采集系统的实现,对该系统的结构、性能进行了验证和测试.实验结果表明,该系统可以实现测试范围内信号的采集、发送和无线接收,系统输入信号与无线接收终端接收信号之间的平均绝对误差为0.843 kHz,最大相对误差为0.51%,无障碍环境有效采集范围约为100 m,有障碍环境有效采集范围约为50 m.     

基于P矩阵模型的声表面波胎压微传感器研究

轮胎压力监视系统是一种当轮胎气压与温度超出正常标准时,能及时提醒驾驶者的系统。研究的目的在于对该系统一款新型无源无线声表面波微传感器的设计进行理论分析和参数优化。为此,根据耦合模理论推出了P矩阵模型新的表示形式并验证了该表示形式在分析双向对称一致IDT和反射器方面的适用性和精确性。应用P矩阵方法分析IDT的输入导纳和该SAW器件的插损,结果显示该传感器设计具有优良的插损性能。     

基于SAW器件的微间隙压力监测传感器

声表面波SAW(Surface Acoustic Wave)器件能进行无源无线通信,为微间隙等特殊环境下物理量的测量提供了新的解决思路.研究设计了一种基于声表面波延迟线的接触应力传感器.围绕微间隙环境,研究了声表面波器件的结构类型,并确定压力监测的技术方案;根据设计原理,设计一种新型声表面波传感器,并利用有限元分析法对压电基片进行应力仿真;将设计出的传感器进行实验测试并提出温度补偿.通过对声表面波传感器设计的探究,验证了利用声表面波传感器实现微间隙压力监测的可行性.     

Coupling coefficient determination based on simulation and experiment for ST-Cut quartz saw delay-line response

This paper used the theoretical calculation to simulate the response of surface acoustic wave (SAW) delay-line on quartz substrate and then compared to the experimental results. The coupling coefficients affected by operation frequency as well as aperture length were built up by experimental data analysis. Based on the experimental values of these two parameters, the device-coupling coefficient was defined. This method is new and we has not found in other document. In addition, it improves the simulation results and helps the analysis process more comprehensive. This study developed ST-cut quartz SAW delay-lines with gold inter-digital transducer (IDT) operating at 39.5 and 78.9 MHz corresponding to 80 and 40 μm of the wavelength. The differences of aperture length in IDT designs were investigated to help understand the effects of this parameter on SAW sensor response. The maximum error of operating frequency is 1%; of insertion loss is 4.25 and 3.13% for bandwidth. The larger of the insertion loss error is expected owing to the result of mathematical approximation and the quality of quartz substrate. The simulation results agree with the experimental results shows that the simulation method can apply to quartz-based SAW delay-line as well as for other material based SAW delay-line applications. The results help understand more about the parameters which effect the insertion loss, operating frequency and bandwidth. It should be very useful for IDT design in specific, SAW sensor and SAW filter design in general.     

SAW传感器对神经性毒剂及模拟剂的检测进展

基于压电效应和化学特异选择性的有机敏感材料的声表面波(SAW)传感器,因其具有体积小、响应时间快、选择性好、可集成度高等优点而成为对气体实时、在线检测的重要手段之一。介绍了SAW传感器在神经性毒剂及其模拟剂检测中的应用,重点从SAW传感器测试电路、敏感膜材料、成膜方法及信号处理等方面介绍此领域的研究现状,并对发展趋势进行了展望。     

声表面波NO_2传感器敏感膜研究进展

由于工业检测、环境监测、医学监测等领域的需求,高性能NO2传感器得到了广泛的研究。声表面波传感器技术的发展为研发高灵敏度、高稳定性、响应快速、小型化的NO2传感器提供了极大的潜能。总结了近30年来声表面波NO2传感器敏感膜的研究现状,并根据现有的研究和传感器的应用需求,深入探讨了声表面波NO2传感器敏感膜面临的挑战和发展趋势。