高职高专数控技术应用专业人才培养规划

数控专业的人才是国家级紧缺人才，数控专业人才的培养是各院校面临的共性问题，本文讨论了数控专业的人才培养目标，并在课程设置、师资队伍建设、实验室和实训基地建设方面做一定的论述。     

基于虚拟仪器的切削力监控技术研究

研制了一种基于虚拟仪器界面、供现场使用的高精度、高效率的金属切削过程监控系统。研究中采用回归分析、叠加原理及抛物线插值的方法建立切削力模型 ,并基于该模型进行参数估计来提取切削状态特征 ,进而监控整个切削过程     

数据库开放对象的数学模型

本文根据系统论提出了开放对象的概念,认为客观世界是由开放对象构成的。它本身是一个递归定义的层次结构,同时具有目的性和适应环境、改造环境的能力即具有自我进化的能力。每个开放对象与其外界的通讯只能通过信息来完成,而且允许它们对同一个消息具有完全不同的理解。开放对象实质是面向对象+人工智能+数据库的一个模型。同时本文还给出它的形式定义。     

弹簧杆校正原理及其在力矩控制系统中的应用

 为了掌握自动飞行器的工作特性,在它飞上空中之前,工程技术人员要在地面进行各种仿真试验。研制力矩控制系统的目的在于模拟随高度、速度变化且连续作用在飞行器翼面上的气动铰链力矩。这种装置广泛应用于各种型号舵机。 我们研制的力矩控制系统力案如图1所示。     

Rotating machinery fault diagnosis based on convolutional neural network and infrared thermal imaging

Rotating machinery is widely applied in industrial applications. Fault diagnosis of rotating machinery is vital in manufacturing system, which can prevent catastrophic failure and reduce financial losses. Recently, Deep Learning (DL)-based fault diagnosis method becomes a hot topic. Convolutional Neural Network (CNN) is an effective DL method to extract the features of raw data automatically. This paper develops a fault diagnosis method using CNN for InfRared Thermal (IRT) image. First, IRT technique is utilized to capture the IRT images of rotating machinery. Second, the CNN is applied to extract fault features from the IRT images. In the end, the obtained features are fed into the Softmax Regression (SR) classifier for fault pattern identification. The effectiveness of the proposed method is validated using two different experimental data. Results show that the proposed method has a superior performance in identification various faults on rotor and bearings comparing with other deep learning models and traditional vibration-based method.     

Spatial transformation of general sampling-aliasing frequency region for rotating-blade parameter identification with emphasis on single-probe blade tip-timing measurement

Blade-health monitoring is intensely required for turbomachinery because of the high failure risk of rotating blades. Blade-Tip Timing (BTT) is considered as the most promising technique for operational blade-vibration monitoring, which obtains the parameters that characterize the blade condition from recorded signals. However, its application is hindered by severe undersampling and stringent probe layouts. An inappropriate probe layout can make most of the existing methods invalid or inaccurate. Additionally, a general conflict arises between the allowed and required layouts because of arrangement restrictions. For the sake of economy and safety, parameter identification based on fewer probes has been preferred by users. In this work, a spatial-transformation-based method for parameter identification is proposed based on a single-probe BTT measurement. To present the general Sampling-Aliasing Frequency (SAFE) map definition, the traditional time–frequency analysis methods are extended to a time-sampling frequency. Then, a SAFE map is projected onto a parameter space using spatial transformation to extract the slope and intercept parameters, which can be physically interpreted as an engine order and a natural frequency using coordinate transformation. Finally, the effectiveness and robustness of the proposed method are verified by simulations and experiments under uniformly and nonuniformly variable speed conditions.     

单幅图像的三维重构视觉系统特征点提取算法的研究与实现

实现基于单幅二维图像不标定欧氏重构三维场景的关键技术之一是有效提取彩色伪随机编码图像特征角点。为给图像特征点匹配提供更多的样本信息,采用定位于彩色图像Harris算子探测特征角点,并动态给出角点响应的自适应阈值条件。特征点提取实验及三维欧氏重构结果证实了该方法的适用性和有效性。     

空间目标快速轮廓特征提取与跟踪技术

为满足空间目标交会对接任务中高精度、快速的测量要求,提出了一种空间目标快速轮廓特征提取与跟踪技术。该算法首先从初始帧图像中分割定位目标所在局部区域,作为目标连续跟踪的初始值;其次基于初始帧目标局部区域完成对初始帧目标边缘特征的检测及细化处理;最后采用Hough变换完成对初始帧目标边缘的检测及细化后的局部图像轮廓直线的提取,分别选取目标轮廓四方向最优的直线参数作为最终目标轮廓直线获取的效果,并采用梯度最大法则实现两两求交获取的轮廓特征的优化提取。在目标逼近过程中,结合相邻帧图像间目标尺度动态变化的关联性,根据初始帧提取目标轮廓特征的先验信息,确定目标在第二帧图像中的轮廓位置,并依次根据上一帧图像的轮廓位置信息定位目标在当前帧所在的区域,通过局部处理实现序列图像轮廓区域特征的连续跟踪。该算法无需遍历整个图像,所需处理的目标区域大幅减小,能够有效克服由目标图像较多边缘干扰导致的轮廓提取效果差及处理速度慢的缺点,具有速度快、准确性强、稳定性高等优点。     

Inertial parameter estimation and control of non-cooperative target with unilateral contact constraint

In this paper, the relative sliding motion between the target and the manipulator’s end-effector is considered and characterized as a unilateral contact constraint. A new possible solution is presented to estimate the inertial parameters of a non-cooperative target while the relative sliding motion exists. First, the detailed analysis of the dynamical model is presented, and a parameter-explicit linear time-varying model is obtained. Then, an extended state observer is constructed based on the new model, which can effectively estimate the unknown inertial parameters of the target when relative sliding motion exists. As the modified reactionless controller requires the knowledge of inertial parameters, a hybrid post-capture control scheme is also established based on the switch law between different controllers. The correctness and efficiency of the proposed algorithm are validated by numerical simulation, which proves a potential framework for the non-cooperative target post-capture operation.     

NNW-TopViz流场可视分析系统

流场可视化技术采用图形图像直观地表现CFD数值模拟的计算结果,使用户能够方便地对这些数据进行分析、比较和研究。然而,CFD数值模拟的流动复杂,其产生的流场数据规模巨大、数据类型复杂、特征提取困难,传统的串行可视化软件效率低、交互手段单一,难以满足数据分析的需求。国家数值风洞（NNW）工程研制了一套流场数据处理可视化软件系统（NNW-TopViz,简称TopViz）,具有对流场数据处理与特征提取、几何图形绘制等可视化与交互功能。根据可视分析效率需求,TopViz实现了线程并行,在多核计算环境下有效提高了可视化计算和交互效率;针对流场特征提取困难、常规方法效率低的问题,TopViz实现了基于卷积神经网络的流场旋涡特征提取方法,提升了特征提取准确率和效率;为提高软件交互效率并提供便捷的交互方式和体验,基于头戴式显示设备和体感控制器构建沉浸式虚拟显示与交互平台,TopViz实现了手势和眼球凝视2种交互方法,提供沉浸式环境下多视图、多角度流场探测方式。