Robust Isolation Of Sensor Failures

Sensor self‐validity check is a critical step in system control and fault diagnostics. In this paper, a robust approach to isolate sensor failures is proposed. First, a residual model for a given system is built off‐line and directly based on input‐output measurement data. The residual model outputs are called “primary residuals” and are zero when there is no fault. Most conventional approaches to residual model generation are indirect, as they first require the determination of state‐space or other models using standard system identification algorithms. Second, a new max‐min design of structured residuals, which can maximize the sensitivity of structured residuals with respect to sensor failures, is proposed. Based on the structured residuals, one can then isolate the sensor failures. This design can also be done in an off‐line manner. It is an optimization procedure that avoids local optimal solutions. Simulation and experimental results demonstrated the effectiveness of the proposed method.     

Visual Analysis of Confocal Raman Spectroscopy Data using Cascaded Transfer Function Design

2D Confocal Raman Microscopy (CRM) data consist of high dimensional per‐pixel spectral data of 1000 bands and allows for complex spectral and spatial‐spectral analysis tasks, i.e., in material discrimination, material thickness, and spatial material distributions. Currently, simple integral methods are commonly applied as visual analysis solutions to CRM data which exhibit restricted discrimination power in various regards. In this paper we present a novel approach for the visual analysis of 2D multispectral CRM data using multi‐variate visualization techniques. Due to the large amount of data and the demand of an explorative approach without a‐priori restriction, our system allows for arbitrary interactive (de)selection of varaibles w/o limitation and an unrestricted online definition/construction of new, combined properties. Our approach integrates CRM specific quantitative measures and handles material‐related features for mixed materials in a quantitative manner. Technically, we realize the online definition/construction of new, combined properties as semi‐automatic, cascaded, 1D and 2D multidimensional transfer functions (MD‐TFs). By interactively incorporating new (raw or derived) properties, the dimensionality of the MD‐TF space grows during the exploration procedure and is virtually unlimited. The final visualization is achieved by an enhanced color mixing step which improves saturation and contrast.     

Development of the curtain wall installation robot: Performance and efficiency tests at a construction site

The development of automation in construction has been restricted by the variety of construction materials used, variable circumstances, and difficulties in the quantitative management of the construction process. Curtain wall, however, can be considered a relatively standard material compared to other construction materials. In this study, we analyze the current process of curtain wall installation and investigate the potential of an automated system combining a commercial excavator and a 3-DOF manipulator. This automated system has the adaptations necessary to work with any type of commercialized excavator. Therefore, workers need to transfer only the 3-DOF manipulator portion of the system when they move to other construction sites. This paper investigates experimental trials involving the proposed system at construction sites to determine its performance, working time, and efficiency. Results from this study were analyzed and further research options outlined.     

Real‐Time Subspace Integration for Example‐Based Elastic Material

Example‐based material allows simulating complex material behaviors in an art‐directed way. This paper presents a method for fast subspace integration for example‐based elastic material, which is suitable for real‐time simulation in computer graphics. At the core of the method is the formulation of a new potential using example‐based Green strain tensors. By using this potential, the deformation can be attracted towards the example‐based deformation feature space, the example weights can be explicitly obtained and the internal force can be decomposed into the conventional one and an additional one induced by the examples. The real‐time subspace integration is then developed with subspace integration costs independent of geometric complexity, and both the reduced conventional internal force and additional one being cubic polynomials in reduced coordinates. Experiments demonstrate that our method can achieve real‐time simulation while providing comparable quality with the prior art.     

Multi‐style paper pop‐up designs from 3D models

Paper pop‐ups are interesting three‐dimensional books that fascinate people of all ages. The design and construction of these pop‐up books however are done manually and require a lot of time and effort. This has led to computer‐assisted or automated tools for designing paper pop‐ups. This paper proposes an approach for automatically converting a 3D model into a multi‐style paper pop‐up. Previous automated approaches have only focused on single‐style pop‐ups, where each is made of a single type of pop‐up mechanisms. In our work, we combine multiple styles in a pop‐up, which is more representative of actual artist's creations. Our method abstracts a 3D model using suitable primitive shapes that both facilitate the formation of the considered pop‐up mechanisms and closely approximate the input model. Each shape is then abstracted using a set of 2D patches that combine to form a valid pop‐up. We define geometric conditions that ensure the validity of the combined pop‐up structures. In addition, our method also employs an image‐based approach for producing the patches to preserve the textures, finer details and important contours of the input model. Finally, our system produces a printable design layout and decides an assembly order for the construction instructions. The feasibility of our results is verified by constructing the actual paper pop‐ups from the designs generated by our system.     

Sensor Location for Diagnosis in Linear Systems: A Structural Analysis

We consider here the fault detection and isolation (FDI) problem for linear systems. We are interested in designing a set of observer-based residuals, in such a way that the transfer from the faults to the residuals is diagonal and the transfer from the disturbances to the residuals is zero. We deal with this problem when the system under consideration is structured, that is, the entries of the system matrices are either fixed zeros or free parameters. This problem can be solved in terms of the graph that can be associated in a natural way with a structured system. When the FDI solvability conditions are not satisfied, we assume that internal variables can be measured at a cost and look into the question of wether the problem is solvable with these new measurements. We give solvability conditions for a solution with a minimal number of additional sensors and among such solutions provide a minimal cost solution for the sensor location problem under consideration. We pay particular attention to the internal analysis of the system, and we propose a structural decomposition of the system associated graph based on some particular separators. This analysis leads to the definition of a reduced system. We prove that some potential additional sensors are inefficient for solving our FDI problem and that the FDI problem can be solved using only measurements on the reduced system     

Automated hazardous material information retrieval system for fire departments

This article discusses the design of a computer based information system oriented towards retrieval of data concerning hazardous materials located at or near the site of a fire call. The article presents the data structure and coding method selected along with the computer and language utilized during the construction phase of the system. Because of the desire to make the resulting system feasible for smaller communities, the system was developed around a microprocessor.     

Invariant‐set‐based fault diagnosis in Lure systems

In this paper, we present an invariant‐set‐based method for actuator and sensor fault detection and isolation in Lure systems. The Lure plant is controlled by an observer‐based feedback tracking controller, designed for the nominal (fault‐free) system. Suitable residual signals are constructed from measurable system outputs and estimates associated with the nominal observer. Faults are diagnosed by online contrasting the residual signal trajectories against sets of values that the residuals are shown to attain under healthy or faulty operation. These values are obtained via set‐invariance analysis of the system closed‐loop trajectories. Copyright © 2013 John Wiley & Sons, Ltd.     

Acquisition, Synthesis, and Rendering of Bidirectional Texture Functions

One of the main challenges in computer graphics is still the realistic rendering of complex materials such as fabric or skin. The difficulty arises from the complex meso structure and reflectance behavior defining the unique look‐and‐feel of a material. A wide class of such realistic materials can be described as 2D‐texture under varying light‐ and view direction, namely, the Bidirectional Texture Function (BTF). Since an easy and general method for modeling BTFs is not available, current research concentrates on image‐based methods, which rely on measured BTFs (acquired real‐world data) in combination with appropriate synthesis methods. Recent results have shown that this approach greatly improves the visual quality of rendered surfaces and therefore the quality of applications such as virtual prototyping. This state‐of‐the‐art report (STAR) will present the techniques for the main tasks involved in producing photo‐realistic renderings using measured BTFs in details.     

Product-cost modelling approach for the development of a decision support system for optimal roofing material selection

Selection of optimal roofing materials is very important but it is a complex and onerous task as varieties of materials are available for housing roof construction. In order to select suitable materials, an extensive range of criteria would need to be considered. This paper presents the framework and the development of a knowledge-based decision support system for material selection implemented in roofing material selection domain, called ‘Knowledge-based Decision Support system for roofing Material Selection and cost estimating’ (KDSMS). It was developed to facilitate the selection of optimal materials for different roof sub elements. The system consists of a database and knowledge base that is equipped with an inference engine. The former is used to store different types of roofing materials with assigned attribute values. The later is used to hold qualitative and quantitative knowledge which were collected from domain experts and other technical literatures such as building regulations, price guide book and product catalogues. The proposed system employs the TOPSIS (Technique of ranking Preferences by Similarity to the Ideal Solution) multiple criteria decision making method to solve materials selection and optimisation problem. This study utilised the available roofing materials in the UK housing market in developing the system reported. The main contribution of the developed system is that it provides a tool for the architects, quantity surveyors or self house builder to select optimal materials from a wide array of possibilities for different roof sub elements and also to estimate the conceptual cost for the roof element in the early stage of building design.     

Fault detection and isolation in robotic manipulators via neural networks: A comparison among three architectures for residual analysis

In this article we discuss artificial neural networks‐based fault detection and isolation (FDI) applications for robotic manipulators. The artificial neural networks (ANNs) are used for both residual generation and residual analysis. A multilayer perceptron (MLP) is employed to reproduce the dynamics of the robotic manipulator. Its outputs are compared with actual position and velocity measurements, generating the so‐called residual vector. The residuals, when properly analyzed, provides an indication of the status of the robot (normal or faulty operation). Three ANNs architectures are employed in the residual analysis. The first is a radial basis function network (RBFN) which uses the residuals of position and velocity to perform fault identification. The second is again an RBFN, except that it uses only the velocity residuals. The third is an MLP which also performs fault identification utilizing only the velocity residuals. The MLP is trained with the classical back‐propagation algorithm and the RBFN is trained with a Kohonen self‐organizing map (KSOM). We validate the concepts discussed in a thorough simulation study of a Puma 560 and with experimental results with a 3‐joint planar manipulator. © 2001 John Wiley & Sons, Inc.     

Classification of major construction materials in construction environments using ensemble classifiers

The automatic detection of construction materials in images acquired on a construction site has been regarded as a critical topic. Recently, several data mining techniques have been used as a way to solve the problem of detecting construction materials. These studies have applied single classifiers to detect construction materials—and distinguish them from the background—by using color as a feature. Recent studies suggest that combining multiple classifiers (into what is called a heterogeneous ensemble classifier) would show better performance than using a single classifier. However, the performance of ensemble classifiers in construction material detection is not fully understood. In this study, we investigated the performance of six single classifiers and potential ensemble classifiers on three data sets: one each for concrete, steel, and wood. A heterogeneous voting-based ensemble classifier was created by selecting base classifiers which are diverse and accurate; their prediction probabilities for each target class were averaged to yield a final decision for that class. In comparison with the single classifiers, the ensemble classifiers performed better in the three data sets overall. This suggests that it is better to use an ensemble classifier to enhance the detection of construction materials in images acquired on a construction site.     

基于LEBERT的多模态领域知识图谱构建

多模态知识图谱(multi-modal knowledge graph, MMKG)是近几年新兴的人工智能领域研究热点.本文提供了一种多模态领域知识图谱的构建方法,以解决计算机学科领域知识体系庞大分散的问题.首先,通过爬取计算机学科的相关多模态数据,构建了一个系统化的多模态知识图谱.但构建多模态知识图谱需要耗费大量的人力物力,本文训练了基于LEBERT模型和关系抽取规则的实体-关系联合抽取模型,最终实现了一个能够自动抽取关系三元组的多模态计算机学科领域知识图谱.     

Inventing motivates and prepares student teachers for computer‐based learning

A brief, problem‐oriented phase such as an inventing activity is one potential instructional method for preparing learners not only cognitively but also motivationally for learning. Student teachers often need to overcome motivational barriers in order to use computer‐based learning opportunities. In a preliminary experiment, we found that student teachers who were given paper‐based course material spent more time on follow‐up coursework than teachers who were given a well‐developed computer‐based learning environment (CBLE), leading to higher learning outcomes. Thus, we tested inventing as an instructional method that may help overcome motivational barriers of teachers' use of computer‐supported tools or learning environments in our main experimental study (N = 44). As a computer‐based environment, we used the ‘Assessment of Learning strategies in Learning journals’. The inventing group produced ideas about criteria to evaluate learning strategies based on student cases prior to the learning phase. The control condition read a text containing possible answers to the inventing problem. The inventing activity enhanced motivation prior to the learning phase and assessment skills as assessed by transfer problems. Hence, the inventing activity prepared student teachers to learn from a CBLE in a motivational as well as cognitive way.     

Interactive thin elastic materials

Despite great strides in past years are being made to generate motions of elastic materials such as cloth and biological skin in virtual world, unfortunately, the computational cost of realistic high‐resolution simulations currently precludes their use in interactive applications. Thin elastic materials such as cloth and biological skin often exhibit complex nonlinear elastic behaviors. However, modeling elastic nonlinearity can be computationally expensive and numerically unstable, imposing significant challenges for their use in interactive applications. This paper presents a novel simulation framework for simulating realistic material behaviors with interactive frame rate. Central to the framework is the use of a constraint‐based multi‐resolution solver for efficient and robust modeling of the material nonlinearity. We extend a strain‐limiting method to work on deformation gradients of triangulated surface models in three‐dimensional space with a novel data structure. The simulation framework utilizes an iterative nonlinear Gauss–Seidel procedure and a multilevel hierarchy structure to achieve computational speedups. As material nonlinearity are generated by enforcing strain‐limiting constraints at a multilevel hierarchy, our simulation system can rapidly accelerate the convergence of the large constraint system with simultaneous enforcement of boundary conditions. The simplicity and efficiency of the framework makes simulations of highly realistic thin elastic materials substantially fast and is applicable of simulations for interactive applications. Copyright © 2015 John Wiley & Sons, Ltd.     

Texture rendering system for architectural design

Depicting construction materials in colour enhances the realism of synthetic images and provides the architect with a powerful design tool. A computer-aided system for creating textured renderings of architectural designs is presented. This enables the designer to organize libraries of texture samples and details extracted from digital images of colour photographs of actual materials. Furthermore, buildings can be interactively positioned on an optically scanned site background and the textures mapped to simulate any desired view of the building. The system was designed so that it could be used quickly and easily by architects with little computer experience.     

Information lifecycle management with RFID for material control on construction sites

Radio frequency identification (RFID) is an emerging technology in the building industry. Many researchers have demonstrated how to enhance material control or production management with RFID. However, there is a lack of integrated understanding of lifecycle management. This paper develops and demonstrates a framework to Information Lifecycle Management (ILM) with RFID for material control. The ILM framework includes key RFID checkpoints and material types to facilitate material control on construction sites. In addition, this paper presents a context-aware scenario to examine multiple on-site context and RFID parameters. From tagging nodes at the factory to reading nodes at each lifecycle stage, this paper demonstrates how to manage complex construction materials with RFID and how to construct integrated information flows at different lifecycle stages. To validate key material types and the scenario, the study reports on two on-site trials: read distance test and on-site simulation. Finally, the research provides discussion and recommended approaches to implementing ILM. The results show that the ILM framework has the potential for a variety of stakeholders to adopt RFID in the building industry. This paper provides the understanding about the effectiveness of ILM with RFID for material control, which can serve as a base for adopting other IT technologies in the building industry.     

AppFusion: Interactive Appearance Acquisition Using a Kinect Sensor

We present an interactive material acquisition system for average users to capture the spatially varying appearance of daily objects. While an object is being scanned, our system estimates its appearance on‐the‐fly and provides quick visual feedback. We build the system entirely on low‐end, off‐the‐shelf components: a Kinect sensor, a mirror ball and printed markers. We exploit the Kinect infra‐red emitter/receiver, originally designed for depth computation, as an active hand‐held reflectometer, to segment the object into clusters of similar specular materials and estimate the roughness parameters of BRDFs simultaneously. Next, the diffuse albedo and specular intensity of the spatially varying materials are rapidly computed in an inverse rendering framework, using data from the Kinect RGB camera. We demonstrate captured results of a range of materials, and physically validate our system.