Search results

The purpose of this article is to suggest that Fraby‐Perot optic sensor is a practical measurement gage to monitor the strain of great structures such as railway bridges.

A remote strain monitoring system based on F‐P optic fiber and virtual instrument is designed to monitor the strains of a railway bridge.

The application results show that the Fraby‐Perot optical fiber sensors can accurately measure strain and they are suitable for the long‐term and automatic monitoring. In addition, the system has several advantages over conventional structural instruments including fast response, ability of both static and dynamic monitoring, absolute measurement, immunity to interferences such as lightning strikes, electromagnetic noise and radio frequency, low attenuation of light signals in long fiber optic cables.

Health monitoring of structures is getting more and more recognition all over the world because it can minimize the cost of reparation and maintenance and ensure the safety of structures. A strain monitoring system based on F‐P optic fiber sensor was developed according to the health monitoring requirements of Wuhu Yangtze River Railway Bridge, which is the first cable‐stayed bridge with a maximum span of 312 m carrying both railway and highway traffic in China. It has run stably in the monitoring field more than two years and fulfilled the monitoring requirement very well. Now the system has been transplanted successfully to the Zhengzhou Yellow Railway Bridge for strain monitoring. So the work can be referenced by other similar health monitoring projects.

Long‐term, real‐time monitoring of strain using FP fiber optic sensors in railway bridge is an innovation. A remote strain data acquisition and real‐time processing are another character of the system. The work studied can be referenced by other structures monitoring, such as tunnel, concrete bridges, concrete and earth dams.

This study aims to analyze the dynamic monitoring of deformation damage of steel structure buildings in long-term use. Although the steel structure building has the advantage of high structural strength, it will be deformed after being affected by factors such as corrosion and impact during long-term use, and which will affect building safety, especially the public building facilities. The dynamic monitoring of its security is an indispensable means.

This paper briefly introduced the principle of building information modeling (BIM)-based steel structure building information monitoring and the dynamic information monitoring system based on this principle. Then the monitoring system was used to analyze an operational steel structure suspension bridge in Xinxiang City, Henan Province, China, and compared it with the monitoring system based on back propagation (BP) neural network.

The results showed that the fitting degree of the dynamic deformation displacement data processed by BIM-based monitoring system was higher than that processed by BP-based monitoring system. Based on the comprehensive comparison of the dynamic data of all monitoring points, the BIM-based monitoring system had higher accuracy of deformation displacement monitoring and reliability of structural safety evaluation.

In summary, the BIM-based steel structure building monitoring system can effectively monitor the dynamic information of steel structure information.

The purpose of the paper is to propose a novel approach, based on grey clustering decision, to fill in an omission of quantitative monitoring parameter selection methods.

The basic monitoring parameter selection criteria and the corresponding calculation methods are presented. Then, the grey clustering decision model for monitoring parameter optimization selection is constructed, and an integrated weight determination method based on analytic hierarchy process (AHP) and information entropy is provided.

Basic principle for monitoring parameter selection is proposed and quantitative description is carried out for selection principle in engineering application. Grey clustering decision‐making model for monitoring parameter optimization selection is established. Comprehensive weight ascertainment method based on AHP and information entropy is provided to make the index weight more scientific.

At system design stage, it is of significance to carry out selection and optimization of monitoring parameters. After the optimization of monitoring parameters is confirmed, measurability analysis and design in parallel are carried out for convenience of timely information feedback and system design revision. Therefore, the system integration efficiency is improved and the cost of research and manufacturing is reduced.

Monitoring parameter optimization selection process based on grey clustering decision‐making model is described and the analysis result shows that the proposed method has certain degree of effectiveness, rationality and universality.

Human skin temperature data can provide reference advice for diagnosing many diseases, but current wearable skin temperature monitoring systems have few points and may miss temperature information in critical areas. This paper aims to develop a wearable system that can be used for local temperature monitoring and restore better the actual state of local human temperature by exploring ways to extend more temperature measurement points. This will provide better assistance in developing medical targeting and intelligent clothing.

The temperature measurement system contains modules for temperature monitoring, digital-to-analog conversion and regulated power supply, enabling fast reading of 12 channels of monitoring data. The microprocessor unit is the STM32F407. The instructions and control modes are written in C. The waist area was chosen as the monitoring area because it is susceptible to temperature, and many diseases are associated with skin temperature. Twelve points, including temperature-related acupuncture points and heat-sensitive points, were selected for testing and the data results agreed well with the infrared imaging results.

The waist is selected as the monitoring object, and an easy-to-wear waist temperature monitoring belt is designed to verify the application value of the system. The development of the system provides reference suggestions for the exploration of multi-point temperature monitoring systems and the integration capabilities of temperature measurement modules in wearable multifunctional systems.

In addition to waist temperature monitoring, the wearable temperature measurement system developed in this study can also be applied to other body parts. In addition, the system can be efficiently and effectively combined with various garments, making it a useful tool for researching human skin temperature.

The wearable temperature monitoring system designed in this paper extends the number of temperature test points to 12. The number of test points covers as many localized body areas as possible to indeed reproduce the temperature distribution of the human body. In addition, the selection of test points combines medically relevant body points with physiologically relevant heat-sensitive areas, which makes the temperature measurement data more valuable.

The purpose of this paper is to introduce the continuous auditing system based on continuous monitoring and its implementation methodology; also to present a systematic case study of actual continuous auditing systems implemented in the financial industry and the manufacturing industry.

The paper examines the method of implementing the continuous auditing system in the enterprise resource planning (ERP) environment, and suggests how the continuous auditing system can take firm root by looking at the successful introduction of the continuous auditing system in the financial industry and the manufacturing industry.

The proposed method of implementing the continuous auditing system has the 2stage approaches which can be applied to various kinds of companies in the ERP‐based environment. In addition, the proposed cases have the important practical implications acquired in the process of implementing the continuous auditing system in the financial industry and the manufacturing industry.

This study will help many corporations facing various types of corruption or circumvention of internal control, with their internal auditing, by showing them how to use the continuous auditing system to reinforce internal control. Also, it will make the independent auditor understand audited company's continuous monitoring system and lead to use the infrastructure for efficient and effective external auditing.

The proposed method and cases of implementing the continuous auditing system offer an innovative approach to auditing in the ERP‐based environment because it facilitates both internal auditor and external auditor to achieve the audit objectives efficiently and effectively.

The purpose of this paper is to design a low-power human physiological parameters monitoring system which can monitor six vital parameters simultaneously based on wearable body sensor network.

This paper presents a low-power multiple physiological parameters monitoring system (MPMS) which comprises four subsystems. These are: electrocardiogram (ECG)/respiration (RESP) parameters monitoring subsystem with embedded algorithms; blood oxygen (SpO₂)/pulse rate (PR)/body temperature (BT)/blood pressure (BP) parameters monitoring subsystem with embedded algorithms; main control subsystem which is in charge of system-level power management, communication and interaction design; and upper computer software subsystem which manipulates system function and analyzes data.

Results have successfully demonstrated monitoring human ECG, RESP, PR, SpO₂, BP and BT simultaneously using the MPMS device. In addition, the power reduction technique developed in this work at the physical/hardware level is effective. Reliability of algorithms developed for monitoring these parameters is assessed by Fluke Prosim8 Vital Signs Simulators (produced by Fluke Corp. USA).

The MPMS device provides long-term health monitoring without interference from normal personal activities, which potentially allows applications in real-time daily healthcare monitoring, chronic diseases monitoring, elderly monitoring, human emotions recognization and so on.

First, a power reduction technique at the physical/hardware level is designed to realize low power consumption. Second, the proposed MPMS device enables simultaneously monitoring six key parameters. Third, unlike most monitoring systems in bulk size, the proposed system is much smaller (118 × 58 × 18.5 mm3, 140 g total weight). In addition, a comfortable smart shirt is fabricated to accommodate the portable device, offering reliable measurements.

The purpose of this paper is to describe the development of a novel mobile monitoring and control (MC) framework with active-push and plug-and-play capabilities. This proposed framework is particularly designed to addresses the shortcomings of the traditional factory MC systems in sharing information over the internet, protecting the system security, delivering warning messages, and deploying monitoring points.

By leveraging web service technology, mobile devices, and wireless communication, this paper describes the methodology and approach for designing a MC server, a wireless monitoring module (WMM), an intelligent v-Machine, two active-push mechanisms, a pocket PC application, and a smart phone application.

The designed WMM enables the monitoring points to be deployed in a mobile manner. The proposed mobile MC framework (MMCF) can timely detect abnormalities of appliances and equipment and turn off appliances in dangerous situations through WMM. It can also instantly deliver various warning contents to the mobile devices carried by the responsible persons. The v-Machine is built based on virtual metrology (VM) technology and can predict production precision of machined workpieces.

With the successful design and testing of the novel MMCF, this framework can obviously be used for many more applications and developments.

The authors' implement a factory MC system based on the proposed framework and conduct various integration tests on two electric appliances and a practical CNC machine tool in a factory. Testing results shows that the factory MC system works smoothly according the design goals and can overcome the shortcomings of traditional factory MC systems. The MC system also presents good performances, instantly delivering warning contents with a size ranging from 1K bytes to 10M bytes to the users within few seconds.

The proposed MMCF exploits various automation technologies to detect equipment's abnormalities, reduce the rate of product defects caused by human errors, reinforce security, prevent accidents, and ensure the safety of operations.

The proposed MMCF can effectively promote existing factory MC systems to achieve the merits of mobile MC, which is a unique contribution of this work, compared to previous studies. The results of this study can be applied to a variety of industrial automation applications, including factory automation and assembly automation.

The purpose of this paper is to examine the relationship between hybrid HR systems in call centers and their effect on workers' performance.

Drawing on a sample of 337 call center operator-supervisor dyads, the authors analyzed how the joint perceptions of monitoring and high-performance work systems (HPWS) are associated with workers' authenticity to explain performance, rated by supervisors.

The authors found that when monitoring is perceived as low, HPWS is not associated with authenticity, suggesting that it requires the joint effect of monitoring and HPWS to communicate HR management priorities in call centers. In addition, the authors found that high ratings of monitoring combined with low perceptions of HPWS were associated with the lowest levels of authenticity, whereas the highest levels of authenticity at work were found when high monitoring was combined with high HPWS. The results supported a conditional indirect effect through authenticity to explain when and how hybrid HR systems are associated with better supervisor-rated performance.

This is the first study to test the interaction effects between HPWS and monitoring practices to explain authenticity as a key strategic component of performance in call centers.

This paper aims to present disaster information and a monitoring system in order to utilize earth observation data in the operative process of early warning, mitigation and management of natural disasters. The system is aimed at integrating earth observation data analysis with modern ICTs including GIS, grid, mobile communication and web technology to support disaster monitoring and to share disaster information during a crisis.

The system development concerned outlining an operative disaster monitoring and management process. The process was derived from actual practices, suggestions and needs of different user groups involved in disaster management. After investigating state‐of‐the‐art ICTs and reviewing the existing tools and databases, a suitable system architecture was designed and a prototype system was implemented, adapting to a proven software development process.

The prototype system implementation demonstrated how satellite‐based data can be used to support disaster management processes. Disaster monitoring requires information system infrastructure that would enable communication and integrate various distributed information sources and services.

The result gives ideas for establishing an operative disaster management process involving local authorities, disaster analysts and the public. The process integrates earth observation data analysis with modern ICTs and improves the methods of early warning. The developed concept can be used as the basis for future development of automated real‐time disaster monitoring.