机载塔康设备综合检查仪设计

使用市场上成熟的模块和技术研制机载塔康设备综合检查仪,以降低成本和提高设备的可靠性;根据设备的测试需求,选用嵌入式工业平板电脑、USB-ARINC429通讯卡、USB-数字IO卡、串行接口数字表和自研的塔康信号模拟器等构成检查仪硬件,使用CVI9.0编写了测试程序;应用表明:检查仪集成度高,使用方便,能够完成对塔康设备的自动及手动测试。     

Blind estimation of the PN sequence in lower SNR DS-SS signals with residual carrier

This paper presents a method of singular value decomposition (SVD) plus digital phase lock loop (DPLL) to solve the difficult problem of blind pseudo-noise (PN) sequence estimation in low signal to noise ratios (SNR) direct sequence spread spectrum (DS-SS, DS) signals with residual carrier. Of course, the method needs to know the parameters of DS signal, such as the period and code rate of PN sequence. Firstly, the received signal is sampled and divided into non-overlapping signal vectors according to a temporal window, whose duration is two periods of PN sequence. Then, an autocorrelation matrix is computed and accumulated by the signal vectors one by one. The PN sequence with residual carrier can be estimated by the principal eigenvector of this autocorrelation matrix. Furthermore, a DPLL is used to deal with the estimated PN sequence with residual carrier, it estimates and tracks the residual carrier, removes the residual carrier in the end. Theory analysis and computer simulation results show that this method can effectively realize the PN sequence estimation from the input DS signals with residual carrier in lower SNR.     

CLP(ℜ) and some electrical engineering problems

The Constraint Logic Programming Scheme defines a class of languages designed for programming with constraints using a logic programming approach. These languages are soundly based on a unified framework of formal semantics. In particular, as an instance of this scheme with real arithmetic constraints, the CLP() language facilitates and encourages a concise and declarative style of programming for problems involving a mix of numeric and non-numeric computation.In this paper we illustrate the practical applicability of CLP() with examples of programs to solve electrical engineering problems. This field is particularly rich in problems that are complex and largely numeric, enabling us to demonstrate a number of the unique features of CLP(). A detailed look at some of the more important programming techniques highlights the ability of CLP() to support well-known, powerful techniques from constraint programming. Our thesis is that CLP() is an embodiment of these techniques in a language that is more general, elegant and versatile than the earlier languages, and yet is practical.An earlier version of this paper appeared in the proceedings of the 4th International Conference on Logic Programming, Melbourne, May 1987. Much of this work was carried out while the authors were at Monash University, Melbourne, Australia.     

基于DSP嵌入式技术的无刷直流电动机智能控制系统的研究

本文以TI公司的数字信号处理器TMS320F2812作为核心控制芯片,设计出了一款低成本具有足够功能的无刷直流电动机的调速控制系统实验平台。详细介绍了该控制系统的软硬件结构及控制策略。通过对该控制系统实验结果的分析,表明该系统的动态性能和稳态性能好,抗干扰能力强的特点,且在该实验平台上可进行一些先进控制算法的研究。     

基于DSP芯片的斜齿轮插齿数控加工技术研究

国内斜齿轮加工一般采用滚齿机或者进口插齿机,由于产品体积过大和机床价格昂贵而受到限制.文章对采用DSP芯片的数控插齿加工技术进行了研究,提出了虚拟轴插补技术以及用软件实现电子齿轮差动技术,利用DSP芯片的高速处理能力进行跟踪插补,经初步试验证明该方法理论上可行,实际中可以运用.     

Bayesian decision-based pattern recognition on spectrum signal of metal transfer modes

A software system of pattern recognition on spectrum signal of metal transfer mode has been developed using Visual Basic under Windows environment. On the basis of the coincidence relation between the spectrum signal and metal transfer mode, according to the geometrical pattern feature of the spectrum signal, several key characteristic parameters are extracted. The correspondent recognition function and a minimum distance classifier have been constructed based on Bayesian decision theory. The results show that using this system, the metal transfer mode of MIG, MAG, CO2 welding can be recognized automatically which provides the basis for automatically controlling of the metal gas arc welding metal transfer.     

Epileptic seizure classification in EEG signals using second-order difference plot of intrinsic mode functions

Epilepsy is a neurological disorder which is characterized by transient and unexpected electrical disturbance of the brain. The electroencephalogram (EEG) is a commonly used signal for detection of epileptic seizures. This paper presents a new method for classification of ictal and seizure-free EEG signals. The proposed method is based on the empirical mode decomposition (EMD) and the second-order difference plot (SODP). The EMD method decomposes an EEG signal into a set of symmetric and band-limited signals termed as intrinsic mode functions (IMFs). The SODP of IMFs provides elliptical structure. The 95% confidence ellipse area measured from the SODP of IMFs has been used as a feature in order to discriminate seizure-free EEG signals from the epileptic seizure EEG signals. The feature space obtained from the ellipse area parameters of two IMFs has been used for classification of ictal and seizure-free EEG signals using the artificial neural network (ANN) classifier. It has been shown that the feature space formed using ellipse area parameters of first and second IMFs has given good classification performance. Experimental results on EEG database available by the University of Bonn, Germany, are included to illustrate the effectiveness of the proposed method.     

Feature extraction of the first difference of EMG time series for EMG pattern recognition

This paper demonstrates the utility of a differencing technique to transform surface EMG signals measured during both static and dynamic contractions such that they become more stationary. The technique was evaluated by three stationarity tests consisting of the variation of two statistical properties, i.e., mean and standard deviation, and the reverse arrangements test. As a result of the proposed technique, the first difference of EMG time series became more stationary compared to the original measured signal. Based on this finding, the performance of time-domain features extracted from raw and transformed EMG was investigated via an EMG classification problem (i.e., eight dynamic motions and four EMG channels) on data from 18 subjects. The results show that the classification accuracies of all features extracted from the transformed signals were higher than features extracted from the original signals for six different classifiers including quadratic discriminant analysis. On average, the proposed differencing technique improved classification accuracies by 2–8%.     

Chemical properties of femoral gland secretions in the desert iguana,Dipsosaurus dorsalis

This study investigates the chemistry of femoral gland secretions in the desert iguana,Dipsosaurus dorsalis (Lacertilia: Iguanidae), and discusses their possible functional significance. Electrophoretic and proton NMR studies indicated that the secretions are composed of approximately 80 % protein and 20% lipid material. Individual differences in polyacrylamide gel banding patterns of femoral gland proteins were found. Reflectance spectroscopy revealed that the secretions strongly absorb longwave ultraviolet light, a feature that may be important in the localization of secretion deposits in the environment.     

城市污水处理厂污泥中温两相厌氧消化的研究

采用中温两相厌氧消化处理西安市污水处理厂污泥,结果表明,污泥可在较短的停留时间(296 h,产酸相30 h,产甲烷相266 h),较高的有机负荷(约2.65 kg VS/m3.d)下稳定运行,系统VS去除率38.87%,pH≈7.5,产气速率6.33 L/L.d,单位VS产气率3.00 L/g。与单相厌氧消化处理结果对比,两相厌氧消化系统的停留时间可减少一半,而污泥有机负荷提高2倍,且有机物的去除率大,处理效果好,稳定性高,抗冲击负荷能力强,产气性良好。