A generalized method for the inherent energy performance modeling of machine tools

Machine tools (MTs), as the key equipment of manufacturing systems, have enormous quantities and consume a great amount of energy. However, the diversity of both machines and their energy consumption properties make it difficult to transfer the energy-saving knowledge and services among different MT. To facilitate the initialization configuration of energy-saving services, the inherent energy performance (IEP) is investigated to describe the differences in energy consumption among MTs, and a generalized method for modeling the IEP of MT and its electrical subsystems is proposed. Three key enablers, including generalized experimental design rules, automatic coding, and data processing algorithms, are presented and integrated into a supporting system to reduce the modeling efforts and knowledge requirements. Case studies of an offline manufacturing scenario and an Internet of Things (IoT)-enabled manufacturing scenario were carried out to verify the effectiveness and convenience of the proposed method. The results show that the proposed method can provide essential modeling support for large-scale energy-saving service configurations and energy-efficient MT development.     

Spatial hybrid/parallel force control of a hexapod machine tool using structure-integrated force sensors and a commercial numerical control

Structure-integrated force measurement in hexapod structures or kinematics offers great potential for spatial process force control in six degrees of freedom. Although force control has been studied for many years, research questions remain unanswered, especially when regarding parallel kinematic machine tools with numerical control and integrated sensors. This contribution summarizes the technology of structure-integrated force sensing in hexapod machine tools and develops two approaches to use the measured signals for direct hybrid/parallel force control. For different use-cases, such as teach-in or synchronous force/position control with variable task frame, different approaches of set-point specification and injection of manipulated values are studied from a practical point of view. As a result of the work, the feasibility of the force control with structure-integrated sensors on a commercial CNC can be confirmed through appropriate experiments. Furthermore, the realized G-Code integration represents a practical solution for programming force-controlled machine tools in an easy and concise way from the NC programme.     

Beyond Alternative Text and tables: Comparative Analysis of Visualization Tools and Accessibility Methods

Modern visualization software and programming libraries have made data visualization construction easier for everyone. However, the extent of accessibility design they support for blind and low-vision people is relatively unknown. It is also unclear how they can improve chart content accessibility beyond conventional alternative text and data tables. To address these issues, we examined the current accessibility features in popular visualization tools, revealing limited support for the standard accessibility methods and scarce support for chart content exploration. Next, we investigate two promising accessibility approaches that provide off-the-shelf solutions for chart content accessibility: structured navigation and conversational interaction. We present a comparative evaluation study and discuss what to consider when incorporating them into visualization tools.     

ParaDime: A Framework for Parametric Dimensionality Reduction

ParaDime is a framework for parametric dimensionality reduction (DR). In parametric DR, neural networks are trained to embed high-dimensional data items in a low-dimensional space while minimizing an objective function. ParaDime builds on the idea that the objective functions of several modern DR techniques result from transformed inter-item relationships. It provides a common interface for specifying these relations and transformations and for defining how they are used within the losses that govern the training process. Through this interface, ParaDime unifies parametric versions of DR techniques such as metric MDS, t-SNE, and UMAP. It allows users to fully customize all aspects of the DR process. We show how this ease of customization makes ParaDime suitable for experimenting with interesting techniques such as hybrid classification/embedding models and supervised DR. This way, ParaDime opens up new possibilities for visualizing high-dimensional data.     

Evaluating View Management for Situated Visualization in Web-based Handheld AR

As visualization makes the leap to mobile and situated settings, where data is increasingly integrated with the physical world using mixed reality, there is a corresponding need for effectively managing the immersed user's view of situated visualizations. In this paper we present an analysis of view management techniques for situated 3D visualizations in handheld augmented reality: a shadowbox, a world-in-miniature metaphor, and an interactive tour. We validate these view management solutions through a concrete implementation of all techniques within a situated visualization framework built using a web-based augmented reality visualization toolkit, and present results from a user study in augmented reality accessed using handheld mobile devices.     

xOpat: eXplainable Open Pathology Analysis Tool

Histopathology research quickly evolves thanks to advances in whole slide imaging (WSI) and artificial intelligence (AI). However, existing WSI viewers are tailored either for clinical or research environments, but none suits both. This hinders the adoption of new methods and communication between the researchers and clinicians. The paper presents xOpat, an open-source, browser-based WSI viewer that addresses these problems. xOpat supports various data sources, such as tissue images, pathologists' annotations, or additional data produced by AI models. Furthermore, it provides efficient rendering of multiple data layers, their visual representations, and tools for annotating and presenting findings. Thanks to its modular, protocol-agnostic, and extensible architecture, xOpat can be easily integrated into different environments and thus helps to bridge the gap between research and clinical practice. To demonstrate the utility of xOpat, we present three case studies, one conducted with a developer of AI algorithms for image segmentation and two with a research pathologist.     

面向目标用户的深度学习模型可视化综述

深度学习模型在某些场景的实际应用中要求其具备一定的可解释性, 而视觉是人类认识周围世界的基本工具, 可视化技术能够将模型训练过程从不可见的黑盒状态转换为可交互分析的视觉过程, 从而有效提高模型的可信性和可解释度. 目前, 国内外相关领域缺少有关深度学习模型可视化工具的综述, 也缺乏对不同用户实际需求的研究和使用体验的评估. 因此, 本文通过调研近年来学术界模型可解释性和可视化相关文献, 总结可视化工具在不同领域的应用现状, 提出面向目标用户的可视化工具分类方法及依据, 对每一类工具从可视化内容、计算成本等方面进行介绍和对比, 以便不同用户选取与部署合适的工具. 最后在此基础上讨论可视化领域存在的问题并加以展望.     

凸缘断面型钢多工位在线尺寸测量

研制了一种凸缘断面型钢的多工位轧件尺寸在线测量系统 ,测量精度可达 0 .0 1mm。该系统用于型钢轧制的闭环尺寸控制 ,借助于带人工智能的控制软件 ,可以明显提高型钢轧制的尺寸精度。用于轧制 H2 0 0mm× 10 0 mm铅质模拟轧件时 ,轧件的腰部厚度尺寸偏差可以从标准要求的± 1.0 mm提高至± 0 .1mm之内。用于 60 kg/m重轨的冷定径精轧 ,轨高的尺寸偏差可从± 0 .5 mm提高至± 0 .1mm     

弹丸转动惯量测试系统及其误差分析

介绍了一种用于测量弹丸转动惯量的高精度测量仪器,该仪器利用双悬丝扭摆机构、光电计时系统提取摆动周期信息,由MCS-51系列单片机组成的测量系统进行数据处理,并由LED显示器测量结果。文中阐述了仪器的工作原理, 推导了所需的计算公式,分析了产生测量误差的因素,进行了定量精度分析,给出了实验结果与测量精度。     

蠕变试验装置的微机巡检系统

研制了微机巡检系统，巡回监测蠕变试验的温度和形变信号，介绍系统组成及其软件功能