航天电连接器分离拉力测试系统设计

针对航天电连接器在出厂前需进行分离测试的情况,以JF2-126TD航天电连接器为研究对象设计了一种航天电连接器分离拉力测试系统,并对测试系统中硬件及软件技术进行研究.系统主要利用拉力传感器和数据采集卡获得电连接器分离瞬间的拉力值,通过所测数据与标准值的比较来判断航天电连接器的分离是否合格.     

ANSYS在电连接器温升分析中的应用

对于玻璃封接电连接器,由于接触件材料的电阻率较大,在使用时大量发热而导致的温升,可能会引起电连接器电气性能的大幅下降,甚至可能导致电连接器的功能失效.所以能够准确地计算出电连接器的温升值,对提高电连接器的可靠性是至关重要的.使用相关的计算公式进行理论计算,无法获得准确的电连接器的温升值.通过有限元分析软件ANSYS对电连接器进行有限元分析计算,将更为准确地计算出电连接器的温升,增加设计的可靠性.     

基于改进支持向量机的电动车辆故障自动检测方法

为提高电动车辆故障自动检测的准确性,设计了一个基于改进支持向量机的电动车辆故障自动检测方法.首先对电动车辆诊断信号采集,然后采用支持向量机理论对电动车辆故障信息低维时域特征提取,并识别特征空间的有效样本,同时对有效性样本聚类结果进行了二次划分,最后采用支持向量机与遗传算法结合的方式对车辆故障检测,以此实现基于改进支持向...     

视音频自动检测报警系统的设计与实现

本文主要介绍视音频自动检测报警系统的结构，原理，实验方法以及最终实现功能，它不仅适用于模拟视音频，也可用于数字视音频，对改善播出质量，增强技术监控自动化提供了辅助手段。     

基于改进Yolo v3的电连接器缺陷检测

针对电连接器缺陷检测目前存在自动化程度低、检测精度低、检测速度慢以及鲁棒性较差等问题,提出了一种改进的Yolo v3算法来检测电连接器的缺陷。首先采用K-means聚类算法对本文数据集进行聚类分析得到3种宽高比的候选框,针对本文缺陷对象提高检测精度;对主干网络第三个残差块输出的8倍降采样特征图进行4倍上采样,将得到的特征图与第二个残差块输出的2倍降采样特征图进行拼接得到融合特征检测层;将目标检测层之前经过的6个DBL单元改为2个DBL单元加上2个残差单元,以提高特征的复用与获取;另外本文选择单尺度特征图进行目标检测,而不是原网络的多尺度预测,既节省了计算量,又一定程度上避免误检。通过定性与定量的实验结果表明,本文改进后的Yolo v3算法对电连接器缺陷检测有着更好的性能以及速度,准确率为93.5%,相较于Faster R-CNN更加准确,原Yolo v3更加快速,基本上满足了工业现场对电连接器检测的要求。     

卫星供配电测试设备电连接器的检测方法

卫星供配电测试设备上有许多外观完全相同的电连接器,为了防止仅靠人为主观识别而导致电连接器插错,文章提出一种全新的、客观的检测方法;通过使用电连接器上未使用的悬空接点,将其与电源、指示灯和开关等元器件连接,形成闭合检测电路;当供配电测试电缆连接正确时,相应状态指示灯亮;否则,指示灯状态不正确;检测电路可避免电连接器错插、漏插和插接不到位的问题,提高卫星综合测试的安全性和可靠性;该设计已成功应用于多套地面供配电测试设备,并经过多颗卫星综合测试和发射任务的检验.     

基于AD7884的分离脱落电连接器机械分离力测试台的设计

基于分级型模数转换器AD7884对分离脱落电连接器的分离力进行测量,采用8位单片机W77E58与之接口,进行数据处理并通过485串口传输到上位机。实现了对分离脱落电连接器的分离力进行测量,系统运行稳定,且与上位机数据交互简单、可靠。     

宇航环境电连接器的失效机理及应用研究

电连接器作为基础电子元器件,在航天器中应用数量多,其可靠性对航天器至关重要.选取宇航级38999电连接器为代表,分析电连接器在宇航环境中的失效机理,提出了电连接器耐宇航环境在设计、选材及相关工艺要求,并对辐照、热真空释气等相关试验项目进行了验证.     

基于自适应滑模观测器的航空电连接器间歇性失效检测

针对航空电连接器系统建立数学模型,提出基于自适应滑模观测器的故障重构方法实现间歇性失效检测.针对乘性故障上界未知的情况,设计自适应律在线修正滑模观测器增益.采用Lyapunov函数作为稳定观测器的判别条件,保证跟踪状态的收敛性.引入线性变换矩阵进一步求取实现滑模运动的滑模观测器增益常数项,并验证滑模运动将在有限时间内发生.应用等价输出误差介入原理获取故障信息,实现乘性故障的检测和重构.对重构出的特征参数进行分析可以判断电连接器是否发生失效.用SIMULINK进行仿真,结果验证该方法有效.     

基于机器视觉的液晶屏裂痕自动检测方法研究

随着液晶的普及,对液晶屏生产过程中质量控制提出更高的要求,液晶屏裂痕自动检测系统应运而生,它能真正实现高效率、高稳定性的实时检测。针对液晶屏裂痕缺陷中的"线缺陷"、"点缺陷"进行深入研究,把机器视觉、数字图像处理技术运用到液晶屏裂痕自动检测系统中,并以HALCON和VC++联合编程完成了裂痕自动检测系统的设计。在数字图像处理部分,根据指定尺寸对图像进行傅里叶变换、高斯滤波、迭代处理等一系列操作,为了得到更清晰的图像,突出裂痕区域,对图像进行灰度化、频域图像卷积、滤波去噪、形态学处理。选择出适合在线测量的各种算法,进行了大量实验测试和实时自动检测,结果表明,该方法在识别液晶屏裂痕的几何特征上效果和精度较好,识别速度达到在线要求。     

基于机器视觉的多铆钉自动检测算法研究

为了克服传统人工铆钉检测工效低、精度不易控制等弊端,提出了一种基于机器视觉的多铆钉非接触式自动检测算法。采用改进的OTSU算法对采集到的铆钉图像进行分割,有效地减少了污点区域的误划分。为解决铆钉方位的随机性对检测过程造成的影响,采用最小外接矩形法定位铆钉轮廓主轴,克服了复杂工业环境中的不确定因素。通过计算铆钉轮廓各点在两侧支撑区间内曲率的方法识别轮廓特征点,有效减少了噪声在曲率计算中的权重,并提高了识别精度。实验表明:该系统检测精度高,且误检率低,能满足铆钉生产在线检测的要求。     

基于多维状态参量和时间序列对电机的异常检测

针对传统对电机的异常检测常常出现误判或滞后的情况,采用基于时间序列对电机单一状态参量用AR拟合,同时利用SOM神经网络无监督的方式量化电机数据。然后,利用得到的量化序列结合AR曲线得到序列的转移概率,及早发现某种状态参量的异常变化;之后,DBSCAN算法挖掘多维参数之间特征关系来确定电机是否出现异常。最后结合实例说明该方法的检测过程,并对比验证了该方法的优越性。     

Sensitivity improvement of automatic pulmonary nodules detection in chest X-ray CT images

In this article, we develop an automatic detection method for non-isolated pulmonary nodules as part of a computer-aided diagnosis (CAD) system for lung cancers in chest X-ray computed tomography (CT) images. An essential core of the method is to separate non-isolated nodules from connecting structures such as the chest wall and blood vessels. The isolated nodules can be detected more easily by the CAD systems developed previously. To this end, we propose a preprocessing technique for nodule candidate detection by using double-threshold binarization. We evaluate the performance using the receiver operating characteristic (ROC) analysis in clinical chest CT images. The results suggest that the detection rate for non-isolated nodules by the proposed method is superior to that by the conventional preprocessing methods.     

无纸化考试系统自动组卷策略分析及改进

介绍了自动组卷的数学模型和几种常用的自动组卷策略,探讨了基于传统遗传算法的智能组卷策略,并在此基础上,重点研究了改进的型遗传算法组卷策略.     

An automatic aperture detection system for LED cup based on machine vision

In order to improve the effectiveness of aperture detection and enhance the competitiveness of enterprise, an automatic inspection system for detecting the aperture of Led cup is developed in the paper. The proposed system can achieve detecting the aperture and separating the unqualified Led cups robustly. Specifically, efficient approaches based on three-point circle fitting and convolutional neural network (CNN) are proposed to achieve automatic aperture detection. Then, a novel control unit is designed to separate the unqualified Led cups using the gas claw and air cylinder. Experimental results demonstrate that the detecting accuracy of the developed system can well meet the requirements of manufacturing enterprise. Moreover, the proposed system can greatly save time and labor costs for enterprises. In addition, with this system we can efficiently construct a vision big data of LED cups. Using such a vision big data, problems of the production line can be timely discovered, and the production quality will be greatly improved.     

基于机器视觉的荧光磁粉自动检测系统设计

现有荧光缺陷检测技术主要采用人眼视觉判定与半自动化等方式,针对目前存在的检测效率低、对人体辐射损伤大等问题,提出一种基于机器视觉的荧光磁粉自动检测流水线系统。该系统具备自动磁化、缺陷检测及智能分拣等功能,实现检测过程的全自动;采用基于梯度聚类算法的磁痕缺陷识别方法,可根据缺陷特征进行检测模式分类,以提高缺陷检测的准确性。实验结果表明:该系统实现工件缺陷的全自动化检测,平均识别正确率高达98. 53%,检测效果较好,具有较高推广价值。     

Supervisory control of automatic pouring machine

This paper presents supervisory control of a total molten-metal pouring system to improve the productivity of the factory, the safety of workers, and the quality of the product. Through the pouring processes model, a forward tilting control input was calculated by an adaptive feedforward control system to hold the liquid in the sprue cup at a constant level considering the change effected by the accumulating slag in the ladle. A backward tilting input was obtained by means of the hybrid shape approach applied to suppress the slosh. The supervisory control system reasonably switches from the forward tilting motion to the backward tilting motion by using model predictive control to achieve the accurate poured quantity. The validity of the proposed total control system was demonstrated through experiments.     

Multiple-fault detection and identification scheme based on hierarchical self-organizing maps applied to an electric machine

Strategies of condition monitoring applied to electric motors play an important role in the competitiveness of multiple industrial sectors. However, the risk of faults coexistence in an electric motor and the overlapping of their effects in the considered physical magnitudes represent, currently, a critical limitation to provide reliable diagnosis outcomes. In this regard, additional investigation efforts are required towards high-dimensional data fusion schemes, particularly over the features calculation and features reduction, which represent two decisive stages in such data-driven approaches. In this study, a novel multiple-fault detection and identification methodology supported by a feature-level fusion strategy and a Self-Organizing Maps (SOM) hierarchical structure is proposed. The condition diagnosis as well as the corresponding estimated probability are obtained. Moreover, the proposed method allows the visualization of the results while preserving the underlying physical phenomenon of the system under monitoring. The proposed scheme is performed sequentially; first, a set of statistical-time based features is estimated from different physical magnitudes. Second, a hybrid feature reduction method is proposed, composed by an initial soft feature reduction, based on sequential floating forward selection to remove the less informative features, and followed by a hierarchical SOM structure which reveals directly the diagnosis and probability assessment. The effectiveness of the proposed detection and identification scheme is validated with a complete set of experimental data including healthy and five faulty conditions. The accuracy’s results are compared with classical condition monitoring approaches in order to validate the competency of the proposed method.     

微矩形弯式焊印制板电连接器打弯夹具的结构设计

介绍了微矩形弯式焊印制板电连接器打弯夹具的结构设计及打弯的过程。为解决早期打弯存在的问题而设计了一种能实现快速、高效打弯的打弯夹具，详细阐述了引脚整体打弯央具的结构设计方法、工作原理以及应用范围。