24m~2烧结机自动化改造方案

介绍烧结机不停产自动化改造的方法,阐述构成工艺过程控制的DCS系统组合以及变频调速技术改造电磁滑差调速成功的选型方法。     

基于数字PID算法的台达运动控制器在音叉多线切割机上的应用

在连续一时间控制系统中,PID控制器在各类自动化系统中应用得非常广泛。其设计技术成熟,长期以来形成了典型的结构,参数整定方便,结构变化灵活,能满足一般的控制要求。数字PID控制比连续PID控制更为优越,因为计算机程序的灵活性,很容易克服连续PID控制中存在的问题,经修正可得到更为完善的数字PID算法。     

基于激光多普勒测速法的2×106m/s2高冲击校准技术

在高冲击传感器动态性能校准中,实现高量程、宽脉冲激励是目前高冲击校准急需解决的问题。采用速度改变法校准原理,以气炮为激励源,利用激光多普勒测速方法测量砧体运动速度,建立高冲击校准系统。分析碰撞系统的作用原理,提出调整和控制激励脉宽的方法;分析测速误差,提出双光束差动侧向测速方法。实验结果表明:高冲击校准系统校准量程为2×106m/s2,激励脉宽在2×106m/s2时大于100μs,校准冲击灵敏度的扩展不确定度小于5%(k=2)。     

支持状态机建模的工作流引擎研究

为了能清晰地描述存在较多审批环节和步骤跳转的业务流程,提出利用状态机为流程建模的方法。通过改进传统的关系结构工作流引擎,给出一个支持状态机建模的关系结构工作流引擎的设计方案,详细介绍该引擎的设计原理和实现柔性方法。最后通过一个示例,演示支持状态机建模的工作流引擎的工作机制和实例迁移的过程。原型已经应用到高校学费管理系统中。实践证明,该引擎可以有效地支持状态机建模,并缩短关键业务的开发周期。     

虚拟环境平台上的Linux裁剪分析

分析在虚拟环境平台上（虚拟机上）,采用原有的和新的方法来裁减Linux系统,得到的效果和意义。     

基于极限学习机的堤防工程多元风险指标评价方法

为提高堤防工程风险评价的准确性,提出了基于极限学习机的堤防工程多元风险指标评价方法。首先,综合考虑影响堤防风险的28个评价指标,利用层次分析法从预警系统、堤防工程系统、环境系统和社会经济系统这4个方面建立了堤防工程多元风险评价指标体系。接着,基于极限学习机算法对28个指标进行标准化处理及分级标准构建,以风险指标作为输入量,分级隶属度作为输出量,划分风险等级,量化评价指标,估计多元风险评价指标值和判断风险的严重程度。最后,依托鄱阳湖重点堤防——康山大堤,构建多元风险评价指标体系,运用极限学习机算法计算多元风险评价指标值。评价结果表明:康山大堤目前处于基本安全水平,符合康山大堤经过两次加固后的工程实际情况,并与其他方法进行对比,验证了提出方法的可靠性和有效性。该方法可拓展应用到其他重要水工结构工程风险评估中。     

Digital Twin-driven machining process for thin-walled part manufacturing

Thin-walled parts are widely used in the aerospace, shipbuilding, and automotive industry, but due to its unique structure and high accuracy requirements, which leads to an increase in scrapped parts, high cost in production, and a more extended period in the trial machining process. However, to adapt to fast production cycles and increase the efficiency of thin-walled parts machining, this paper presents a Digital Twin-driven thin-walled part manufacturing framework to allow the machine operator to manage the product changes, make the start-up phases faster and more accurate. The framework has three parts: preparation, machining, and measurement, driven by Digital Twin technologies in detail. By establishing and updating the workpiece Digital Twin under a different status, various manufacturing information and data can be integrated and available to machine operators and other Digital Twins. It can serve as a guideline for establishing the machine tool and workpiece Digital Twin and integrating them into the machining process. It provides the machine operator opportunities to interact with both the physical manufacturing process and its digital data in real-time. The digital representation of the physical process can support them to manage the trial machining from different aspects. In addition, a demonstrative case study is presented to explain the implementation of this framework in a real manufacturing environment.     

ACS运动控制器运动实时暂停功能的实现方法

提出了一种ACS运动控制器运动实时暂停功能的实现方法。该方法通过将大的程序段按时间细分成细小段轨迹运动程序,然后在各细小段轨迹运动程序之间加入条件控制语句,使各细小轨迹运动程序段逐条载入到运动命令队列中,从而有效控制整个程序的运行,实现运动实时暂停功能。该方法已在基于ACS运动控制器的卷簧机数控系统中得到应用,取得了理想的运动实时暂停效果,且未出现明显的累积误差。     

基于CPLD的系统硬件看门狗设计

基于以DSP芯片TMS320F2812为核心的数字伺服控制器,以国微电子公司的SM1032国产CPLD(兼容Lattice公司的ispLSI 1032)为载体,设计了专用的系统硬件看门狗模块,具备识别DSP软件初始化时序、自由定制看门狗时序等功能。通过对伺服控制器上电及工作运行时序的分析、仿真和实验验证,确定了硬件看门狗功能模块的设计方案,并给出了实验结果。     

Soft computing approach to fault diagnosis of centrifugal pump

Fault detection and isolation in rotating machinery is very important from an industrial viewpoint as it can help in maintenance activities and significantly reduce the down-time of the machine, resulting in major cost savings. Traditional methods have been found to be not very accurate. Soft computing based methods are now being increasingly employed for the purpose. The proposed method is based on a genetic programming technique which is known as gene expression programming (GEP). GEP is somewhat a new member of the genetic programming family. The main objective of this paper is to compare the classification accuracy of the proposed evolutionary computing based method with other pattern classification approaches such as support vector machine (SVM), Wavelet-GEP, and proximal support vector machine (PSVM). For this purpose, six states viz., normal, bearing fault, impeller fault, seal fault, impeller and bearing fault together, cavitation are simulated on centrifugal pump. Decision tree algorithm is used to select the features. The results obtained using GEP is compared with the performance of Wavelet-GEP, support vector machine (SVM) and proximal support vector machine (PSVM) based classifiers. It is observed that both GEP and SVM equally outperform the other two classifiers (PSVM and Wavelet-GEP) considered in the present study.