Research on An Improved PMF-FFT Fast PN Code Acquisition Algorithm

To solve the problem of the large Doppler frequency offset in the LEO communication system, this paper studies a rapid PN code acquisition method based on the PMF-FFT architecture, which searches the phase and frequency offset and at the same time reduces the acquisition time. It presents an improved method equivalent to windowing function and uses windowing process to overcome the attenuation of related peak envelope caused by partial matched filters.

Decoupling Algorithms for the Gravitational Wave Spacecraft

The gravitational wave spacecraft is a complex multi-input multi-output dynamic system.The gravitational wave detection mission requires the spacecraft to achieve single spacecraft with two laser links and high-precision control.Establishing one spacecraftwith two laser links,compared to one spacecraft with a single laser link,requires an upgraded decoupling algorithmfor the link establishment.The decoupling algorithmwe designed reassigns the degrees of freedomand forces in the control loop to ensure sufficient degrees of freedomfor optical axis control.In addressing the distinct dynamic characteristics of different degrees of freedom,a transfer function compensation method is used in the decoupling process to further minimize motion coupling.The open-loop frequency response of the systemis obtained through simulation.The upgraded decoupling algorithms effectively reduce the open-loop frequency response by 30 dB.The transfer function compensation method efficiently suppresses the coupling of low-frequency noise.

Research on Genetic Algorithm Based Knowledge Auto－Acquisition for Fault Diagnosi

In this paper, a genetic algorithm based knowledge auto acquisition approach for fault diagnosis is proposed. Under the circumstances that diagnostic examples are available but no empirical knowledge can be obtained, knowledge for fault diagnosis can be

Automatic Data Acquisition System and Reconstruction Algorithm for Computerized Ionospheric Tomography

The design and operation features of the automatic data acquisition system for the low latitude ionospheric tomography along the 120°E meridian are presented. The system automatically collects the differential Doppler phase data,and GPS satellite beacon signal is simultaneously collected to achieve time synchronization of all receivers in whole station chain. An improved reconstruction algorithm of computerized ionospheric tomography is also proposed, in which calculating of the integral phase constant and choosing of the initial guess are integrated in the procedure of reconstruction and evaluated by the reconstructed image. Both numerical simulation examples and reconstructed results from observed data show that the new algorithm works reasonably and effectively with ionospheric CT problems.

Direct P-code acquisition algorithm based on bidirectional overlap technique

According to the signal-to-noise ratio （SNR） loss of average algorithms in direct P-code acquisition method, this paper analyzes the SNR performance of the overlap average algorithm quantitatively, and derives the relationship of SNR loss with overlap shift value and initial average phase difference in the overlap average algorithm. On this basis, the bidirectional overlap average algorithm based on optimal correlation SNR is proposed. The algorithm maintains SNR consistent in the entire initial average phase difference space, and has a better SNR performance than the overlap average algorithm. The effectiveness of the algorithm is verified by both theoretical analysis and simulation results. The SNR performance of the bidirectional overlap average algorithm is 5 dB better than that of the direct average algorithm, and 2 dB better than that of the overlap average algorithm, which provides the support for direct P-code acquisition in low SNR.

Improved direct P code acquisition technique

P code direct acquisition is an important technology in satellite navigation system. As the P code has a long period, it is hard to directly acquire. The traditional average method can process multiple code phases in a time to shorten the acquisition time. But with the increase of average phase error of the input signal and the local code, the correlation signal-to-noise ratio （SNR） loss increases. To reduce the SNR loss, an improved average method is introduced. A new sequence is generated with a summation of phase shifting sequences to decrease correlation peak loss. Simulation results show that compared with direct average method, the improved average method effectively increases correlation SNR.

The development of data acquisition and processing application system for RF ion source

As the key ion source component of nuclear fusion auxiliary heating devices, the radio frequency （RF） ion source is developed and applied gradually to offer a source plasma with the advantages of ease of control and high reliability. In addition, it easily achieves long-pulse steady-state operation. During the process of the development and testing of the RF ion source, a lot of original experimental data will be generated. Therefore, it is necessary to develop a stable and reliable computer data acquisition and processing application system for realizing the functions of data acquisition, storage, access, and real-time monitoring. In this paper, the development of a data acquisition and processing application system for the RF ion source is presented. The hardware platform is based on the PXI system and the software is programmed on the LabVIEW development environment. The key technologies that are used for the implementation of this software programming mainly include the long-pulse data acquisition technology, multi- threading processing technology, transmission control communication protocol, and the Lempel-Ziv-Oberhumer data compression algorithm. Now, this design has been tested and applied on the RF ion source. The test results show that it can work reliably and steadily. With the help of this design, the stable plasma discharge data of the RF ion source are collected, stored, accessed, and monitored in real-time. It is shown that it has a very practical application significance for the RF experiments.

Development of a Data Acquisition Control System for the First NBI on EAST

Neutral beam injection （NBI） heating is one of the most efficient auxiliary plasma heating methods for fusion devices. The data acquisition control system （DACS） with PXI （pe- ripheral component interconnect extensions for instrumentation） data acquisition card for the first NBI system in the experimental advanced superconducting tokamak （EAST） is presented in this paper. As an important sub-system, DACS is designed to obtain physical measurement signals in the EAST NBI system and to deal and store these data with the Lempel-Ziv-Oberhumer （LZO） lossless data compression algorithm, as well as offer convenient data call-back and access inter- faces to the user for examining and analyzing the data. Experimental results show that accurate data will ensure that researchers correctly analyze it and then properly adjust the experimental parameters or operation, so DACS should take a large step in improving experimental efficiency. Tile hardware and software sections are briefly presented in this paper, and now this system has been tested to be able to work reliably and steadily.

Study of Visual Information Acquisition Technology based on AGV Robot

Visual information acquisition is an important component of the AGV robot. The system adopts STM32F4 embedded application of the ARM Cortex-M4 kernel as the main control module,using shift algorithm to finish on a specific color piece of target tracking. For multi-sensor fusion of three methods,quaternion method is used to correct the attitude,the stability of AGV robot visual information acquisition and image clarity are improved.

Configuration information acquisition and matching in self-reconfiguring process of modular self-reconfigurable robots

Configuration information acquisition and matching are two important steps in the self-reconfiguringprocess of self-reconfigurable robots.The process of configuration information acquisition was introduced,and a self-reconfiguring configuration matching strategy based on graded optimization mechanism was pro-posed.The first-grade optimization was to search common connection between matching scheme and goalconfiguration.The second-grade optimization,whose object function was constructed in terms of configu-ration connectivity,was to search common topology according to the results of the first-grade optimization.The entire process of configuration information acquisition and matching was verified by an experiment andgenetic algorithm (GA).The result shows the accuracy of the configuration information acquisition andthe effectiveness of the configuration matching method.

An Efficient Task Scheduling Method for the Unified Interface Platform of the Electric Information Acquisition System

Due to the large and frequent static data interaction between the Electric Information Acquisition System and the external business systems,researching on using limited server sources to do an efficient task scheduling is becoming one of the key technologies of the unified interface platform.The information interaction structure of the unified interface platform is introduced.Task scheduling has been decomposed into two stages,task decomposition and task combination,based on the features(various types and dispersed)of large static data.The principle of the minimum variance of the subtasks data quantity is used to do the target task resolving in the decomposition stage.The thought of the Greedy Algorithm is used in the task combination.Breaking the target task with large static data into serval composed tasks with roughly same data quantity is effectively realized.Meanwhile,to avoid the situation of the GA falling into the local optimal solution,an improved combination method has been put forward.Moreover,the new method creates more average composed tasks and making the task scheduling more effective.Ultimately,the effectiveness of the proposed method is verified by the experimental data.

肌电信号控制的智能小车实验平台设计

肌电信号是人体肌群在运动时产生的一种微弱信号,该信号蕴藏着与运动相关的控制信息源。提出了一种基于肌电信号的智能小车控制系统。该系统由肌电信号采集模块、无线传输模块、小车控制模块和显示模块等组成。整个系统分为主从两部分。主机采用STM32F103ZET6微处理器对肌电信号进行多通道采集,提取所采集信号的特征值。将特征值分为测试集和训练集,并对不同手势信号贴上对应的标签,使用K最近邻(KNN)算法对测试集进行准确度分析以实现对不同手势的识别。识别结果通过无线传输模块发送给从机小车,小车接收到主机发送的内容后进行相应的动作。测试结果表明,所提出的方法在不同时间段信号采集的平均准确率可达91.14%以上,系统具有很好的鲁棒性。

飞行器参数动态采集降噪技术研究

针对飞行器测试过程中动态数据采集存在大量噪声干扰,设计了硬件与软件相结合的噪声优化解决方案。通过分析π型滤波电路原理,设计相关参数,搭建π型CRC无源滤波电路,从硬件层面解决了信号受纹波干扰导致的失真问题;通过在FPGA中进行理论仿真,设计递推平均滤波器,从软件层面解决了信号受尖峰脉冲噪声干扰导致的信号可靠性降低的问题。经过实验验证,该噪声优化方案可以大幅降低噪声峰峰值。经过优化后的采编器完成了多次高低温和振动试验,性能稳定可靠,目前已经应用在某飞行器大型地面试验中。

基于ARM处理器的温室大棚智能监控系统设计

为了实现温室大棚的智能监测与控制,设计基于ARM处理器的温室大棚智能监控系统。系统分为三个部分:数据采集及设备控制终端、智能网关终端、Android手机客户端,数据采集及设备控制终端以ARM微处理为核心,通过传感器、算法、Wi-Fi等技术,实现温室大棚数据采集、数据处理、数据传输及执行设备的智能控制,智能网关终端实现多个温室大棚数据从内网发送至公网,Android手机客户端实现数据的接收与发送。经测试验证,系统能够实现温室大棚的智能监控。

基于PMF-FFT的北斗B2a信号捕获算法研究

为了对北斗三号B2a信号进行快速且准确地捕获,提出了一种基于PMF-FFT的捕获算法。首先,通过建立数学模型,分析了PMF-FFT算法的特性;然后,对PMF分段长度、FFT运算点数、相关积分时间、非相干积分次数和判决门限等参数的选取进行了详细地分析;最后,利用Matlab工具对PMF-FFT捕获算法性能进行了仿真与分析,验证了算法的有效性,为算法的实现解决了首要问题。

正交通道中码分干扰对载波捕获的影响分析及研究

在多功能数字基带的信号处理过程中,由于正交通道的码分干扰较大,传统的FFT算法无法进行载波捕获。文中从理论上分析了正交通道中扩频码对FFT算法的影响,并进行了仿真分析,最后提出双向搜索捕获算法和增加平方算法两种方法在消除码分干扰中的应用。双向搜索捕获算法在完成码捕获的同时能获得多普勒频率;增加平方算法能有效消除码分多址的影响,精确计算多普勒频率,简单实用。实验结果表明,两种消除码分干扰的算法各有优点,在实际工程应用中可根据需要选择使用。

智能跑步机跟随速度自适应控制方法研究

当前跑步机都是外部速度跟随机器完成控制,在变速过程中智能化程度较低,导致变频调速精度和稳定性控制过程很被动,影响了整体的智能化效果。为此,提出智能跑步机跟随速度自适应控制方法。通过设备完成人体静止及运动状态实时数据采集,利用卡尔曼滤波算法结合采集的数据,实现用户加速度预测,根据预测结合用户在跑步机上的受力情况,带入跑步机速度控制器,实现其跟随速度的自适应控制。实验结果表明:所提方法在接近0.2s时达到理想速度,变频调速精度高于95%,证明该方法的稳定性好、响应速度快且调节精度高,整体控制效果好,更能满足用户对于智能跑步机的自适应变速要求。

基于MIWOA优化SCN的变压器故障诊断研究

针对变压器故障诊断精确度低的问题,本文提出了一种多策略改进的鲸鱼优化算法(MIWOA)优化随机配置网络(SCN)的变压器故障诊断模型。首先,对变压器冗杂繁多的原始故障数据进行核主成分分析(KPCA)降维处理,降低无效特征的影响;其次,利用Tent混沌映射、动态自适应权重和初级知识获取共享算法对鲸鱼算法(WOA)进行改进,提高其优化能力;然后,在SCN中引入L2范数惩罚项进行正则化处理,并使用改进后的MIWOA算法对SCN惩罚项系数C进行寻优求解,提高SCN分类精度和泛化能力;最后,将降维的数据输入到MIWOA-SCN故障诊断模型中,提高模型收敛速度。结果表明,本文所提出的模型诊断精度为93.1%,与WOA-SCN、GWO-SCN和PSO-SCN诊断模型相比,分别提高了6.89%、9.48%、14.65%,证明MIWOA-SCN诊断模型在变压器故障诊断上具有良好的诊断效果。

电力变压器异常故障智能声纹监测与诊断系统研究及应用

如何提高电力变压器运行潜伏性异常故障监测,并且变压器运行不受干扰,是目前电力行业亟待解决的重要问题之一。提出电力变压器异常故障智能声纹监测与诊断系统的研究与应用,通过对电力变压器各种故障声音发声机理分析、混合声音采集与分离、声音信号特征提取和故障类型识别的研究,结合独立分量分析算法、小波包能量分布向量和梅尔对数频谱、BP神经网络算法等人工智能技术的运用,在不影响变压器正常运行下对其进行监测,实现对变压器运行健康状态展示与告警,及时发现变压器异常故障,消除变压器隐患,保障变压器安全稳定运行,减少经济损失,对电力系统发展具有重要意义。

一种基于DSM和DOM的地理信息数据采集方法

针对航摄影像立体采集和人工外业测绘等方式的人员投入大、数据采集效率不高问题,本文通过数字正射影像图(DOM)数据、数字表面模型(DSM)数据及DOM数据生产过程中产生的辅助数据进行再利用,探索推扫式数据中高大地物的倒伏特点,解决数据生产过程中产生的投影差问题,形成了一种新的数据采集技术,并通过生产验证。试验结果表明这种方法打破了传统采集方式的束缚,不受软硬件和人员技能的约束,不仅能够实现基本比例尺地形图测绘功能、新型基础测绘地理实体采编功能,还可以实现建模数据采编功能。