Correlating microstructural features with wear resistance of dual phase steel

In order to explore the tribological potential of the dual phase (DP) steel as a wear resistant material, the wear characteristics of the dual phase (DP) steel have been investigated with varying amounts of martensite from 43 to 81 vol pct, developed by varying holding time at the intercritical annealing temperature of 780 °C. Dry sliding wear tests have been conducted on DP steels using a pin-on-disk machine under different normal loads of 61.3, 68.5, 75.7 and 82.6 N and at a constant sliding speed of 1.20 m/s. At these loads, the mechanism of wear is mainly delamination, which has been confirmed by SEM micrographs of the subsurface and wear debris of the samples. Wear and friction properties have been found to be improved with increasing martensite volume fraction in dual phase steels.     

基于混合特征的人体动作识别改进算法

运动特征的选择直接影响人体动作识别方法的识别效果.单一特征往往受到人体外观、环境、摄像机设置等因素的影响不同,其适用范围不同,识别效果也是有限的.在研究人体动作的表征与识别的基础上,充分考虑不同特征的优缺点,提出一种结合全局的剪影特征和局部的光流特征的混合特征,并用于人体动作识别.实验结果表明,该算法得到了理想的识别结果,对于Weizmann数据库中的动作可以达到100％的正确识别率.     

方管冲孔工艺分析与模具设计

通过对密集架传统加工工艺的分析,提出了采用方管冲孔的加工工艺,并对各种加工方案进行论证,采取只有凸模的无凹模冲孔方式,介绍了方管冲孔模的结构和设计要点。通过试验确定了合理的凸模刃口形状,冲出的零件毛刺极小,产品断面平整光滑。     

一种基于H_∞观测器的电池荷电状态估计方法

文中提出一种基于H∞观测器电池荷电状态SOC估计方法.在传统电池SOC估计方法中,常常把电池开路电压OCV与SOC之间的关系看作是静态线性关系.实际上,电池OCV与SOC之间是随着电池周围环境变化而变化,是一种动态关系;因而如果将电池OCV与SOC之间看作是静态关系,可能导致较大SOC估计误差.根据电池OCV与SOC之间动态关系,将电池系统建模成一种非线性系统,随后设计一种H∞观测器估计电池SOC.在高压输电线路巡检机器人样机中进行了实验研究,实验结果验证了所提方法的有效性.     

AR-based deep learning for real-time inspection of cable brackets in aircraft

In the process of aircraft assembly, there exist numerous and ubiquitous cable brackets that shall be installed on frames and subsequently need to be manually verified with CAD models. Such a task is usually performed by special operators, hence is time-consuming, labor-intensive, and error-prone. In order to save the inspection time and increase the reliability of results, many researchers attempt to develop intelligent inspection systems using robotic, AR, or AI technologies. However, there is no comprehensive method to achieve enough portability, intelligence, efficiency, and accuracy while providing intuitive task assistance for inspectors in real time. In this paper, a combined AR+AI system is introduced to assist brackets inspection in a more intelligent yet efficient manner. Especially, AR-based Mask R-CNN is proposed by skillfully integrating markerless AR into deep learning-based instance segmentation to generate more accurate and fewer region proposals, and thus alleviates the computation load of the deep learning program. Based on this, brackets segmentation can be performed robustly and efficiently on mobile devices such as smartphones or tablets. By using the proposed system, CAD model checking can be automatically performed between the segmented physical brackets and the corresponding virtual brackets rendered by AR in real time. Furthermore, the inspection results can be directly projected on the corresponding physical brackets for the convenience of maintenance. To verify the feasibility of the proposed method, experiments are carried out on a full-scale mock-up of C919 aircraft main landing gear cabin. The experimental results indicate that the inspection accuracy is up to 97.1%. Finally, the system has been deployed in the real C919 aircraft final-assembly workshop. The preliminary evaluation reveals that the proposed real-time AR-assisted intelligent inspection approach is effective and promising for large-scale industrial applications.     

A new force-depth model for robotic abrasive belt grinding and confirmation by grinding of the Inconel 718 alloy

Robotic abrasive belt grinding has been successfully applied to the grinding and polishing of aerospace parts. However, due to the flexible characteristics of robotic abrasive belt grinding and the time-varying characteristics of the polishing contact force, as well as the plastic and difficult-to-machine material properties of Inconel 718 alloy, it is very difficult to control the actual removal depth and force of the polished surface, which brings great challenges to robot automatic polishing. Therefore, the relationship between the grinding force and the grinding depth in the robotic abrasive belt grinding is analyzed in detail, the robot machining pose error model considering the deformation of the grinding head is established, and the Inconel 718 alloy machining experiment of the robotic abrasive belt grinding is designed. The mapping relationship between the grinding force and the grinding depth is obtained, and the grinding force ratio in the downgrinding and upgrinding mode is discussed. The experimental and theoretical comparisons results show that with the increase of the grinding depress depth, both the grinding depth and the grinding force show an irregular increasing trend, and the increasing trend of the grinding force (increases by about 344.44%–445.45%) is obviously greater than that of the grinding depth (increases by about 52.94%). When the grinding depress depth is large (greater than 3 mm), the feed direction force and the normal force appear obvious secondary pressure peaks at the beginning and end of grinding, which has not been seen in previous studies. In addition, regardless of whether it is downgrinding or upgrinding, the grinding force ratio decreases with the increase of the depress depth, and the grinding force ratio of downgrinding (average 0.668) is smaller than that of upgrinding (average 0.724). This study provides a reference for robotic abrasive belt grinding, and the surface quality of Inconel 718 alloy of robotic abrasive belt grinding can be further improved through the optimization of force and depth.     

Digital twin-driven manufacturing equipment development

Currently, expectations of shorter time-to-market and improved product performance are placing greater demands on manufacturing companies. However, the optimization and redesign work between the design stage and the prototype design and manufacturing stage in the traditional product development process lengthens the required product development cycle time (which lasts up to several years in extreme cases). The manufacturing phase for the physical prototype of the product is especially time-consuming and costly. The above reasons make the common product development process increasingly unable to meet the demands of market needs. Motivated by this need, the digital twin (DT)-driven manufacturing equipment (ME) development method is studied in this paper. This method contains three main core elements of the design method based on axiomatic design (AD) theory, the construction of DT models related to ME development, and DT-based validation analysis. The advantage of this method is that it can incorporate the physical prototype manufacturing stage into the digital space with the high-fidelity model provided by the DT technology, which ensures the confidentiality of the design scheme validation while freeing it from the physical prototype stage. This avoids the cost of physical prototyping, shortens the product development cycle, and improves the efficiency of new ME development. At the end of this paper, a case study of the development of a virtual machining dynamic performance test bench (VM-TB) is carried out to show the implementation flow of this proposed method, and its operability and effectiveness are verified.     

Differential geometry modeling and application of roller pose and trajectory of robot roller hemming for complex curved surface-curved edge panels

Roller hemming is a relatively new process used to achieve high-precision assembly of auto-body enclosure panels. During the process of roller hemming, accuracy of the roller pose and trajectory affects the hemming quality of the product. The traditional passive method based on robot teaching to determine the pose of the roller is inefficient and time-consuming. In these studies, we proposed an active method for solving roller pose and trajectory based on differential geometry for curved surface-curved edge geometric characteristics of auto-body enclosure panels and multi-pass reciprocating motions of the roller. Firstly, the local coordinate system of the die was constructed based on the Frenet Frame according to the normal vector of the surface of die and the tangent vector of the curved die edge. Secondly, the coordinate system of the die, diameter of the roller, TCP-RTP value, and inclination of the roller were combined to form the roller pose based on a homogeneous transformation matrix. Based on the obtained trajectory curve of the roller reference point, the equal chord deviation error method was used to analyze the roller trajectory. Finally, a roller pose and trajectory solving algorithm was developed based and implemented using PYTHON to obtain the positions and poses of the roller at several discrete reference points. ABAQUS software was subsequently utilized to complete modeling of the roller pose and trajectory. This research supports the multi-field mechanical simulation of robot roller hemming for curved surface-curved edge panels and provides support for determining roller pose and kinematic trajectory of industrial robot roller hemming for curved surface-curved edge panels.     

融合改进 Padim 建模和 ResNet 网络的 喷涂质量检测算法

为了满足喷涂机器人对于喷涂质量检测的需求,采用迁移学习对改进 Padim 建模和 ResNet 网络进行融合,构建自主喷 涂机器人喷涂质量检测一体化模型。 该模型提取一次图像特征可同时用于缺陷定位和分类。 在缺陷定位端,通过改进 Padim 模型以减少特征冗余所造成网络的计算消耗,首先将 ResNet-18 网络获取的 patch 嵌入向量语义层由原先前 3 层改为单 2 层,然 后特征表达由 100 维降维至 20 维,最后训练正样本得到正态分布模型与测试图像进行缺陷定位。 在缺陷分类端,对预训练 ResNet-18 网络进行负样本二次训练,得到 ResNet-18 分类模型对测试图像进行缺陷分类。 经过实验,将一体化模型移植在 jetson nano 移动端中,参数量仅为 11. 69 M,定位精度 94. 5%,分类准确率高达 99. 6%,在机器人位移速度 0. 02 m/ s 下检测时间 为 0. 730 s,不会出现缺帧漏检情况,满足实时检测的要求。     

Minimum variance prediction and control for adaptive optics

Adaptive Optics (AO) systems enable to compensate the adverse effects of atmospheric turbulence on ground-based telescopes’ images in real time, using a deformable mirror (DM) inserted in the telescope’s optical path, and measurements provided by a wavefront sensor (WFS). This paper revisits minimum-variance (MV) control design for astronomical AO systems in a state-space framework. It presents a survey of the modeling and control issues arising in this multi-variable disturbance rejection problem. In a linear time-invariant framework, and under some mild assumptions, the optimal solution to MV control for AO systems is shown to be a discrete-time LQG controller. This result holds for a DM with instantaneous response, and for a fairly general class of DM’s dynamics. The state-space approach is extended to Wide-field Adaptive Optics (WfAO) configurations involving several DMs and/or WFSs. Integral-action control used in existing AO systems is compared with the LQG controller. Experimental WfAO results obtained on a laboratory test bench are presented, showing significant improvement in performance. Finally, open issues and perspectives of applicative and/or theoretical interests are discussed.