Automatic classification of defects on the product surface in grinding and polishing

Grinding and polishing are standard operations in material processing. It is important to inspect and classify the potential defects existing on the product surfaces after grinding and polishing in order to obtain high quality in both functionality and aesthetics. Post-processing handling can be carried out after the defects have been correctly classified. A vision system already exists to detect and classify defects based on captured grayscale images automatically. The system is able to find and locate the defects precisely, but is incapable of placing those defects into the right predefined classes. The old system classifies the defects 30% of the time into the 15 predefined classes based on shape features. In this paper, a new classification strategy has been introduced using diverse extracted features. In addition to shape features, some other feature extraction methods were tried, e.g. Laws filter bank, DCT (Discrete Cosine Transformation) filter bank, Gabor filter bank, and statistical features based on co-occurrence matrix. The Support Vector Machine (SVM) was used as a multi-class classifier with input of the extracted features. By combining the Gabor filter features and the statistical features, the classification rate of the system can reach 82% overall right rate, which is applicable practically.     

民主德国的堆焊工艺及其现代化设备

本文介绍了民主德国关于堆焊工艺的一些最新研究成果以及为提高焊接自动化程度对设备的研究和发展。哈雷中央焊接研究所研制的堆焊-裁荷-填充材料-工艺系统(“A—B—Z—V”),作为选择工艺及填充材料的依据,从构件分析出发,生产了用于旋转件的特种程序的机器人ZIS12—63.孔堆焊设备ZIS12—96,轨道堆焊机ZIS13—43,轻便堆焊机ZIS15—40.以及用于侧板堆焊的机器人和煤球模型堆焊机器人。     

An efficient method for solving the Signorini problem in the simulation of free-form surfaces produced by belt grinding

Industrial robots are recently introduced to the belt grinding of free-form surfaces to obtain high productive efficiency and constant surface quality. The simulation of belt grinding process can facilitate planning grinding paths and writing robotic programs before manufacturing. In simulation, it is crucial to get the force distribution in the contact area between the workpiece and the elastic contact wheel because the uneven distributed local forces are the main reason to the unequal local removals on the grated surface. The traditional way is to simplify this contact problem as a Signorini contact problem and use the finite element method (FEM) to calculate the force distribution. However, the FEM model is too computationally expensive to meet the real-time requirement. A new model based on support vector regression (SVR) technique is developed in this paper to calculate the force distribution instead of the FEM model. The new model approximates the FEM model with an error smaller than 5%, but executes much faster (1 s vs 15 min by FEM). With this new model, the real-time simulation and even the on-line robot control of grinding processes can be further conducted.     

SleepExplorer: a visualization tool to make sense of correlations between personal sleep data and contextual factors

Getting enough quality sleep is a key part of a healthy lifestyle. Many people are tracking their sleep through mobile and wearable technology, together with contextual information that may influence sleep quality, like exercise, diet, and stress. However, there is limited support to help people make sense of this wealth of data, i.e., to explore the relationship between sleep data and contextual data. We strive to bridge this gap between sleep-tracking and sense-making through the design of SleepExplorer, a web-based tool that helps individuals understand sleep quality through multi-dimensional sleep structure and explore correlations between sleep data and contextual information. Based on a two-week field study with 12 participants, this paper offers a rich understanding on how technology can support sense-making on personal sleep data: SleepExplorer organizes a flux of sleep data into sleep structure, guides sleep-tracking activities, highlights connections between sleep and contributing factors, and supports individuals in taking actions. We discuss challenges and opportunities to inform the work of researchers and designers creating data-driven health and well-being applications.     

A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem

Meta-heuristics are frequently used to tackle NP-hard combinatorial optimization problems. With this paper we contribute to the understanding of the success of 2-opt based local search algorithms for solving the traveling salesperson problem (TSP). Although 2-opt is widely used in practice, it is hard to understand its success from a theoretical perspective. We take a statistical approach and examine the features of TSP instances that make the problem either hard or easy to solve. As a measure of problem difficulty for 2-opt we use the approximation ratio that it achieves on a given instance. Our investigations point out important features that make TSP instances hard or easy to be approximated by 2-opt.     

SEMPA – Ein Ansatz des Semantischen Prozessmanagements zur Planung von Prozessmodellen

Currently process modeling is mostly done manually. Therefore, the initial design of process models as well as changes to process models which are frequently necessary to react to new market developments or new regulations are time-consuming tasks. In this paper we introduce SEMPA, an approach for the partly automatic planning of process models. Using ontologies to semantically describe actions – as envisioned in Semantic Business Process Management –, a process model for a specified problem setting can be created automatically. In comparison to existing planning algorithms our approach creates process models including control structures and is able to cope with complex and numerical input and output parameters of actions. The prototypical implementation as well as an example taken from the financial services domain illustrate the practical benefit of our approach.     

Directed model checking with distance-preserving abstractions

In directed model checking, the traversal of the state space is guided by an estimate of the distance from the current state to the nearest error state. This paper presents a distance-preserving abstraction for concurrent systems that allows one to compute an interesting estimate of the error distance without hitting the state explosion problem. Our experiments show a dramatic reduction both in the number of states explored by the model checker and in the total runtime.