首先对自动化标记语言Automation ML技术以及国内外发展情况进展作了介绍,介绍了什么是健壮性,对自动化标记语言健壮性的分析及验证方法进行了描述,并给出了验证方案.

在CPS的背景下,笔者对数字孪生的概念和特性进行了说明,介绍了工程数据交换格式Automation ML的架构,并创建了使用Automation ML对数字孪生进行建模的方法.基于此,提出了建模步骤,对实例中物理实体的物理属性进行分析并设置,并将需要的物理属性交换数据置于中间件中,使得其他系统可有效访问这些属性.实例采用了Automation ML对物理实体建模,从而得出采用Automation ML可对在系统间交换数据的结论.

介绍了针对冷库温度的测量方法,结合数据简要分析了冷库温度变化的各主要指标.基于测量数据,文章着重从冷库的冷量流失和冷库控温等方面考虑,介绍并分析了一些重要的影响因素.

介绍了一套针对钢卷尺测量台的系统性校准方法,以及标准钢卷尺、读数显微镜、砝码等测量台主要部件的功能.结合测量不确定度分析,验证了对相关部件进行校准的必要性,提出了与之相对应的校准项目和方法.

讨论了机动车风洞试验中有关风速和流场品质的检测方法,介绍了测试手段的原理和特性.结合风洞实验室中流场的几种主要技术参数,分析并介绍了与之相适应的测试方法,为相应领域的实际应用提供参考.

本文首先概括了智能制造的特征,对我国与主要发达国家智能制造战略作了横向比较.在此基础之上,引入自动化标识语言Automation Markup Language这一适用于智能制造领域的数据交换格式,对语言架构,如:拓扑信息、几何与运动、逻辑、引用关系等均作了描述,并对Automation ML技术以及国内外发展情况进展作了介绍.最后根据Automation ML的特点,对其应用于智能制造领域的前景作了预测.

The intelligent characteristics are the important features to be used to distinguish intelligent sensor and general industrial sensor;intellectualization is an important developing direction of sensors.The core part of IoT,i.e.,intelligent sensors are investigated and researched;their general characteristics are introduced in brief,and the intelligent characteristics of multiple processes for signal acquisition,data processing,information interaction,and logic judgement,as well as the IoT characteristics in practical applications are analyzed and interpreted in further.Combining with the current industrial status and applicational situation,based on the traditional classifications in accordance with the materials and manufacturing processes of sensors,the multi-angle and multi-faceted classification of intelligent sensors is conducted.In addition,the basis of intellectualization classification,including the composition,integration and the types of signal processor of sensor module;security mechanism of network,and networking application,etc.,are put forward.Due to the unified consensus for systematic classification of sensors has not yet formed in industries today,related research provides reference and guidance for practical applications in corresponding fields,especially for the standardization of intelligent sensors.