基于电信号特征分析的电机故障诊断技术

介绍了电机故障诊断技术平台的组成,分析了电机常见故障下电信号的特征。利用宜昌和景洪工厂两台电机进行了实际对比测试,宜昌工厂电机定子电流特征频率在49.2Hz时表现出峰值-36.08dB,在50.8Hz时表现峰值则为-37.23dB,表明电机存在转子断条故障;景洪工厂电机在转子特征频率为113.51Hz时,出现峰值-58.47dB,表明电机存在静态偏心故障。经电机现场抽芯检查,验证了电机故障快速诊断平台给出的电机健康状态评估结果,证实了基于电信号特征分析的电机故障诊断技术的准确性。     

模具设计与制造专业群虚拟仿真实训基地建设路径研究

针对模具设计与制造专业群实训教学开展过程中存在的问题,开展专业群虚拟仿真实训基地的建设,通过精密模具智能制造生产线仿真实训工厂、模具数字化设计及智能成型单元综合应用平台、开放共享课程资源等3个方面内容的建设,引入行业新技术、新工艺、新标准,确保虚拟仿真教学资源与学生职业能力培养相一致。基地建设依托智能制造新技术,以培养高层次复合型技术技能人才为主线,满足实训教学为核心,多方共享为目标,助力区域经济发展,服务"鲁班工坊"国际化建设,最终实现虚拟仿真实训基地区域示范性效果。     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).     

基于音频特征的工程车辆工况识别研究

高效率地使用工程车辆是工程项目管理中节约成本的有效方法，无人监管环境下工程车辆的工况识别，是实现工程车辆高效率使用的有效手段。目前以GPS等技术为核心的车辆智能管理系统未对工程车辆进行工况识别，提出一种基于GRU循环神经网络的工程车辆工况识别方法，通过对工程车辆在不同工况下产生的音频信号进行分析，从中提取Mel倒谱系数作为主要特征，构建GRU循环神经网络模型进行训练和识别。实验结果表明，该方法可以实现对工程车辆工况的有效识别。     

Nb2O5-doped NiZnCo ferrite ceramics with ultra-high magnetic quality factor and low coercivity for high-frequency electronic devices

This work investigates the influence of niobium pentoxide (Nb₂O₅) as dopant, on the structural, magnetic, and dielectric properties of NiZnCo ferrites. The results showed that Nb₂O₅ was an effective dopant, and the Nb⁵⁺ ions entered the B site to replace Fe³⁺ ions, which altered the electromagnetic properties of the NiZnCo ferrite. In particular, the coercivity (H_c) was 20～24 Oe, and the magnetic quality factor (Q), was more than 200 at x = 0 and x = 0.1 wt%, which is 4～5 times higher than that of NiZn and NiCuZn ferrites. Excellent electromagnetic properties were obtained for 0.1 wt% Nb₂O₅-doped NiZnCo ferrite, i.e., M_s = 88.3 emu/g, H_c =20.4 Oe, ρ = 2.4 × 10⁵ Ω m and Q = 202 @20 MHz. These excellent electromagnetic properties of Nb₂O₅-doped NiZnCo ferrites could be potentially applied to resonators and capacitors at high frequency.     

基于Matlab的量子激光雷达稳频通信模拟系统设计

传统通信模拟系统设计较为复杂,导致模拟过程消耗能量较大,不能准确模拟稳频通信质量。因此,提出基于Matlab的量子激光雷达稳频通信模拟系统。由于振荡器是雷达形成初始信号源的基础,通过分析振荡电路与相位噪声,获得相位噪声函数与通信频率存在的关系;为确保通信过程的稳定,将准确性与稳定性作为信号质量的评价指标,并采用锁频环稳频技术计算频率偏移程度,根据PID控制算法控制频率,量子激光雷达稳频通信;利用Matlab确定激光器、探测器等硬件组成结构,通过时序与数字阵列的设置完成模拟系统设计。仿真结果表明所提系统结构简便、性能稳定,能够真实模拟出稳频通信的信号质量。     

Secure image encryption scheme using 4D-Hyperchaotic systems based reconfigurable pseudo-random number generator and S-Box

This paper introduces the design of a hardware efficient reconfigurable pseudorandom number generator (PRNG) using two different feedback controllers based four-dimensional (4D) hyperchaotic systems i.e. Hyperchaotic-1 and -2 to provide confidentiality for digital images. The parameter's value of these two hyperchaotic systems is set to be a specific value to get the benefits i.e. all the multiplications (except a few multiplications) are performed using hardwired shifting operations rather than the binary multiplications, which doesn't utilize any hardware resource. The ordinary differential equations (ODEs) of these two systems have been exploited to build a generic architecture that fits in a single architecture. The proposed architecture provides an opportunity to switch between two different 4D hyperchaotic systems depending on the required behavior. To ensure the security strength, that can be also used in the encryption process in which encrypt the input data up to two times successively, each time using a different PRNG configuration. The proposed reconfigurable PRNG has been designed using Verilog HDL, synthesized on the Xilinx tool using the Virtex-5 (XC5VLX50T) and Zynq (XC7Z045) FPGA, its analysis has been done using Matlab tool. It has been found that the proposed architecture of PRNG has the best hardware performance and good statistical properties as it passes all fifteen NIST statistical benchmark tests while it can operate at 79.101-MHz or 1898.424-Mbps and utilize only 0.036 %, 0.23 %, and 1.77 % from the Zynq (XC7Z045) FPGA's slice registers, slice LUTs, and DSP blocks respectively. Utilizing these PRNGs, we design two 16 × 16 substitution boxes (S-boxes). The proposed S-boxes fulfill the following criteria: Bijective, Balanced, Non-linearity, Dynamic Distance, Strict Avalanche Criterion (SAC) and BIC non-linearity criterion. To demonstrate these PRNGs and S-boxes, a new three different scheme of image encryption algorithms have been developed: a) Encryption using S-box-1, b) Encryption using S-box-2 and, c) Two times encryption using S-box-1 and S-box-2. To demonstrate that the proposed cryptosystem is highly secure, we perform the security analysis (in terms of the correlation coefficient, key space, NPCR, UACI, information entropy and image encryption quantitatively in terms of (MSE, PSNR and SSIM)).     

改进的CAGAN在虚拟试衣中的应用

针对CAGAN（Conditional Analogy GAN）换衣后效果模糊，在目标衣服与原始衣服长短不一致时效果一般，相对目标衣服保留过少的细节等问题做了相关研究并对CAGAN进行了改进，提出了新的虚拟试衣方式。经过改进的CAGAN生成一个粗糙的结果，由该结果得到目标衣服穿在模特身上改变形状后的mask，接下来利用mask对目标衣服进行变形，综合变形的衣服和第一步的结果便得到最终的试衣图像。实验结果表明，该方法解决了前面存在的问题，而且取得了非常好的效果。     

激光在线测厚振动分析与精度优化

激光测厚具有安全可靠、测量精度高、测量范围大等优点,广泛应用于纸张、电池极片等薄膜类材料厚度的在线测量。带材宽幅方向扫描测厚时由于扫描架往复运动会产生机械振动,影响在线测厚精度。针对该问题,以锂离子电池极片厚度测量为例,使用双激光差动式测厚平台对电池极片和铜箔分别进行厚度测量,然后对测厚数据进行频谱分析,探究其振动规律的相似性,并基于频谱分析结果采用滑动带阻滤波方式对测厚数据进行处理,滤波后极片和铜箔的厚度极差分别降低了33.4%和73.8%,有效过滤了机械振动导致的测量误差,可满足极片和铜箔厚度测量的精度要求。     

Cognitive and affective processes for learning science in immersive virtual reality

As immersive virtual reality (IVR) systems proliferate in classrooms, it is important to understand how they affect learning outcomes and the underlying affective and cognitive processes that may cause these outcomes. Proponents argue that IVR could improve learning by increasing positive affective and cognitive processing, thereby supporting improved performance on tests of learning outcome, whereas opponents of IVR contend that it could hurt learning by increasing distraction, thereby disrupting cognitive learning processes and leading to poorer learning outcomes. In a media comparison study, students viewed a biology lesson either as an interactive animated journey in IVR or as a slideshow on a desktop monitor. Those who viewed the IVR lesson performed significantly worse on transfer tests, reported higher emotional arousal, reported more extraneous cognitive load and showed less engagement based on EEG measures than those who viewed the slideshow lesson, with or without practice questions added to the lessons. Mediational analyses showed that the lower retention scores for the IVR lesson were related to an increase in self-reported extraneous cognitive load and emotional arousal. These results support the notion that immersive environments create high affective and cognitive distraction, which leads to poorer learning outcomes than desktop environments.