立柱加固型框架大楼的爆破拆除

采用定向控制爆破技术拆除立柱加固型7层框架大楼。为了彻底炸毁加固立柱,确保大楼顺利定向倾倒,通过多次爆破试验确定了炸药单耗、布孔参数和装药结构。为了控制大楼塌落时的触地震动,采取了秒差分区爆破、空中解体、铺垫缓冲层和开挖减震沟等技术措施。爆破过程中进行了震动监测。此外还介绍了起爆顺序、安全防护措施及爆破结果。     

Structural health monitoring system based on multi-agent coordination and fusion for large structure

In practical applications of structural health monitoring technology, a large number of distributed sensors are usually adopted to monitor the big dimension structures and different kinds of damage. The monitored structures are usually divided into different sub-structures and monitored by different sensor sets. Under this situation, how to manage the distributed sensor set and fuse different methods to obtain a fast and accurate evaluation result is an important problem to be addressed deeply. In the paper, a multi-agent fusion and coordination system is presented to deal with the damage identification for the strain distribution and joint failure in the large structure. Firstly, the monitoring system is adopted to distributedly monitor two kinds of damages, and it self-judges whether the static load happens in the monitored sub-region, and focuses on the static load on the sub-region boundary to obtain the sensor network information with blackboard model. Then, the improved contract net protocol is used to dynamically distribute the damage evaluation module for monitoring two kinds of damage uninterruptedly. Lastly, a reliable assessment for the whole structure is given by combing various heterogeneous classifiers strengths with voting-based fusion. The proposed multi-agent system is illustrated through a large aerospace aluminum plate structure experiment. The result shows that the method can significantly improve the monitoring performance for the large-scale structure.     

基于熵权TOPSIS的工程咨询机构BIM技术应用能力评价

构建工程咨询机构BIM技术应用能力评价的指标体系,提出改进的熵权TOPSIS评价模型,以4个典型的工程咨询单位为例,进行BIM技术运用能力评价。研究表明,BIM行业的整体水平已经有了明显的提升,但是区域间的发展还存在一定差距。     

A hybrid homogeneously weighted moving average control chart for process monitoring

Several modifications and enhancements to control charts in increasing the performance of small and moderate process shifts have been introduced in the quality control charting techniques. In this paper, a new hybrid control chart for monitoring process location is proposed by combining two homogeneously weighted moving average (HWMA) control charts. The hybrid homogeneously weighted moving average (HHWMA) statistic is derived using two smoothing constants λ₁ and λ₂ . The average run length (ARL) and the standard deviation of the run length (SDRL) values of the HHWMA control chart are obtained and compared with some existing control charts for monitoring small and moderate shifts in the process location. The results of study show that the HHWMA control chart outperforms the existing control charts in many situations. The application of the HHWMA chart is demonstrated using a simulated data.     

A study on the monitoring model development for quality measurement of internet traffic

The recent trend of integration among new network services such as the long-term evolution (LTE) based on internet protocol (IP) needs reputable analyses and prediction information on the internet traffic. The IP along with increased internet traffics due to expanding new service platforms such as smartphones will reflect policies such as network QoS according to new services. The establishment of monitoring methods and analysis plans is thus required for the development of internet traffics that will analyze their status and predict their future. The paper with the speed of Internet traffic model is developed for monitoring the state of the experiment and verified. The problem is that the proposed service Internet service provider (ISP) to resolve the conflict between the occurrences can be considerably Internet traffic and that the state of data may be helpful in understanding. The paper advancement policy to reflect the network traffic volume of Internet services and users irradiation with increased traffic due to the development and management of the analysis was carried out experimental measurements.     

A model- and simulation-based approach for tolerancing and verifying the functional capability of micro/nano-structured workpieces

The evaluation of functional features of manufactured workpieces is based on GO- and NO-GO-test results, which are obtained by comparing measured geometric characteristics with nominal dimensions and tolerances specified by the designer. These geometrical specifications are based on a tolerancing system, which was originally defined for the function mating capability. Against the background of upcoming lots of other new functions (like reduction of flow resistance, light absorption, reduction of friction, diffraction of light, self-cleaning or mass transmission) are to be realized with our products – particularly by micro- and nano scaled features. If the verification process will deliver the prediction of the achievable degree of functionality, the usability of a part can be assessed more accurately and in consequence quality and economics can be improved. So, a new principle for tolerancing and verifying turns out to be necessary. In this paper the fundamental deficit of the actual tolerancing and specification systems GPS and ASME Y14.5 is derived and the path for enlarging the system by preposing a functional model is shown. To verify the functional capability of the workpieces an approach based on simulations done with the parameterized mathematical–physical model of the function is suggested. Advantages of this approach will be discussed and demonstrated by examples with microstructured inking rolls, crankshafts and injection valves.     

Knowledge-Based Virtual Modeling and Simulation of Manufacturing Processes for Industry 4.0

Abstract

Industry 4.0 aims at providing a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital models in inter-organizational production chains have not been identified yet in a systematic manner. In this paper, various Industry 4.0 research and technical challenges are addressed, and their present scenario is discussed. Moreover, in this article, the novel concept of developing experience-based virtual models of engineering entities, process, and the factory is presented. These models of production units, processes, and procedures are accomplished by virtual engineering object (VEO), virtual engineering process (VEP), and virtual engineering factory (VEF), using the knowledge representation technique of Decisional DNA. This blend of the virtual and physical domains permits monitoring of systems and analysis of data to foresee problems before they occur, develop new opportunities, prevent downtime, and even plan for the future by using simulations. Furthermore, the proposed virtual model concept not only has the capability of Query Processing and Data Integration for Industrial Data but also real-time visualization of data stream processing.     

Achieving Rich and Active Alkaline Hydrogen Evolution Heterostructures via Interface Engineering on 2D 1T‐MoS2 Quantum Sheets

Large‐scale production of hydrogen from water‐alkali electrolyzers is impeded by the sluggish kinetics of hydrogen evolution reaction (HER) electrocatalysts. The hybridization of an acid‐active HER catalyst with a cocatalyst at the nanoscale helps boost HER kinetics in alkaline media. Here, it is demonstrated that 1T–MoS₂ nanosheet edges (instead of basal planes) decorated by metal hydroxides form highly active ${\text{edge}}_{{\text{1T‐MoS}}_{\text{2}}}$/ ${\text{edge}}_{\text{Ni}{(\text{OH})}_{\text{2}}}$ heterostructures, which significantly enhance HER performance in alkaline media. Featured with rich ${\text{edge}}_{{\text{1T‐MoS}}_{\text{2}}}$/ ${\text{edge}}_{\text{Ni}{(\text{OH})}_{\text{2}}}$ sites, the fabricated 1T–MoS₂ QS/Ni(OH)₂ hybrid (quantum sized 1T–MoS₂ sheets decorated with Ni(OH)₂ via interface engineering) only requires overpotentials of 57 and 112 mV to drive HER current densities of 10 and 100 mA cm^?2, respectively, and has a low Tafel slope of 30 mV dec^?1 in 1 m KOH. So far, this is the best performance for MoS₂‐based electrocatalysts and the 1T–MoS₂ QS/Ni(OH)₂ hybrid is among the best‐performing non‐Pt alkaline HER electrocatalysts known. The HER process is durable for 100 h at current densities up to 500 mA cm^?2. This work not only provides an active, cost‐effective, and robust alkaline HER electrocatalyst, but also demonstrates a design strategy for preparing high‐performance catalysts based on edge‐rich 2D quantum sheets for other catalytic reactions.     

A review on ultrasonic spot welding of copper alloys

As a solid state joining process, ultrasonic spot welding has been proven to be a promising technique for joining copper alloys. However, challenges still remain in employing ultrasonic spot welding to join copper alloys. This article comprehensively reviews the current state of ultrasonic spot welding of copper alloys with a number of critical issues including materials flow, plastic deformation, temperature distribution, vibration, relative motion, vertical displacement, interface friction coefficient, online monitoring technique, coupled with the macrostructure and microstructure, the mechanical properties and electrical conductivity. In addition, the future trends in this field are provided.     

An automated patient monitoring using discrete‐time wireless sensor networks

In recent years, Internet of Things (IoT) devices are used for remote health monitoring. For remotely monitoring a patient, only the health information at different time points are not sufficient; predicted values of biomarkers (for some future time points) are also important. In this article, we propose a powerful statistical model for an efficient dynamic patient monitoring using wireless sensor nodes through Bayesian Learning (BL). We consider the setting where a set of correlated biomarkers are measured from a patient through wireless sensors, but the sensors only report the ordinal outcomes (say, good, fair, high, or very high) to the sink based on some prefixed thresholds. The challenge is to use the ordinal outcomes for monitoring and predicting the health status of the patient under consideration. We propose a linear mixed model where interbiomarker correlations and intrabiomarker dependence are modeled simultaneously. The estimated and the predicted values of the biomarkers are transferred over the internet so that health care providers and the family members of the patient can remotely monitor the patient. Extensive simulation studies are performed to assess practical usefulness of our proposed joint model, and the performance of the proposed joint model is compared to that of some other traditional models used in the literature.