• Smart Structures and Systems
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• v.4 no.4
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• pp.465-492
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• 2008

Proper pretest planning is a vital component of any successful vibration test on engineering structures. The most important issue in dynamic testing of many engineering structures is arriving at the number and optimal placement of sensors. The sensors must be placed on the structure in such a way that all the important dynamic behaviour of a structural system is captured during the course of the test with sufficient accuracy so that the information can be effectively utilised for structural parameter identification or health monitoring. Several optimal sensor placement (OSP) techniques are proposed in the literature and each of these methods have been evaluated with respect to a specific problem encountered in various engineering disciplines like aerospace, civil, mechanical engineering, etc. In the present work, we propose to perform a detailed characteristic evaluation of some selective popular OSP techniques with respect to their application to practical civil engineering problems. Numerical experiments carried out in the paper on various practical civil engineering structures indicate that effective independence (EFI) method is more consistent when compared to all other sensor placement techniques.

• Nuclear Engineering and Technology
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• v.37 no.2
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• pp.177-184
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• 2005

The Multivariate State Estimation Technique (MSET) is being used in Nuclear Power Plants for sensor and equipment condition monitoring. This paper presents the use of regularization methods for optimizing MSET's predictive performance. The techniques are applied to a simulated data set and a data set obtained from a nuclear power plant currently implementing empirical, on-line, equipment condition monitoring techniques. The results show that regularization greatly enhances the predictive performance. Additionally, the selection of prototype vectors is investigated and a local modeling method is presented that can be applied when computational speed is desired.

• Applied Science and Convergence Technology
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• v.26 no.6
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• pp.157-163
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• 2017

Immobilized enzymes have become the subject of considerable interest due to their excellent functional properties such as reusability, cost-effectiveness, and optimality during the past decades. Enzyme immobilization technology is not only used in industrial processes, but also a component technology of products for medical diagnostics, therapy, food industry, bio energy, and biomaterial detection. In this review, new methods for enzyme immobilization are introduced, and the advantages and disadvantages of a variety of techniques in enzyme immobilization will be also discussed.

• Smart Structures and Systems
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• v.5 no.4
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• pp.381-395
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• 2009

The paper presents a case study in which the structural condition assessment of the East Bay bridge in Gibsonton, Florida is evaluated with the help of remote health monitoring techniques. The bridge is a four-span, continuous, deck-type reinforced concrete structure supported on prestressed pile bents, and is instrumented with smart Fiber Optic Sensors. The sensors used for remote health monitoring are the newly emerged Fabry-Perot (FP), and are both surface-mounted and embedded in the deck. The sensing system can be accessed remotely through fast Digital Subscriber Lines (DSL), which permits the evaluation of the bridge behavior under live traffic loads. The bridge was open to traffic since March 2005, and the collected structural data have been continuously analyzed since. The data revealed an increase in strain readings, which suggests a progression in damage. Recent visual observations also indicated the presence of longitudinal cracks along the bridge length. After the formation of these cracks, the sensors readings were analyzed and used to extrapolate the values of the maximum stresses at the crack location. The data obtained were also compared to initial design values of the bridge under factored gravity and live loads. The study showed that the proposed structural health monitoring technique proved to provide an efficient mean for condition assessment of bridge structures providing it is implemented and analyzed with care.

• Smart Structures and Systems
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• v.6 no.3
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• pp.197-209
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• 2010

The structural state of a bridge is currently examined by visual inspection or by wired sensor techniques, which are relatively expensive, vulnerable to inclement conditions, and time consuming to undertake. In contrast, wireless sensor networks are easy to deploy and flexible in application so that the network can adjust to the individual structure. Different sensing techniques have been used with such networks, but the acoustic emission technique has rarely been utilized. With the use of acoustic emission (AE) techniques it is possible to detect internal structural damage, from cracks propagating during the routine use of a structure, e.g. breakage of prestressing wires. To date, AE data analysis techniques are not appropriate for the requirements of a wireless network due to the very exact time synchronization needed between multiple sensors, and power consumption issues. To unleash the power of the acoustic emission technique on large, extended structures, recording and local analysis techniques need better algorithms to handle and reduce the immense amount of data generated. Preliminary results from utilizing a new concept called Acoustic Emission Array Processing to locally reduce data to information are presented. Results show that the azimuthal location of a seismic source can be successfully identified, using an array of six to eight poor-quality AE sensors arranged in a circular array approximately 200 mm in diameter. AE beamforming only requires very fine time synchronization of the sensors within a single array, relative timing between sensors of $1{\mu}s$ can easily be performed by a single Mote servicing the array. The method concentrates the essence of six to eight extended waveforms into a single value to be sent through the wireless network, resulting in power savings by avoiding extended radio transmission.

• Nuclear Engineering and Technology
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• v.46 no.6
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• pp.737-752
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• 2014

As condition-based maintenance (CBM) has risen as a new trend, there has been an active movement to apply information technology for effective implementation of CBM in power plants. This motivation is widespread in operations and maintenance, including monitoring, diagnosis, prognosis, and decision-making on asset management. Thermal efficiency analysis in nuclear power plants (NPPs) is a longstanding concern being updated with new methodologies in an advanced IT environment. It is also a prominent way to differentiate competitiveness in terms of operations and maintenance costs. Although thermal performance tests implemented using industrial codes and standards can provide officially trustworthy results, they are essentially resource-consuming and maybe even a hind-sighted technique rather than a foresighted one, considering their periodicity. Therefore, if more accurate performance monitoring can be achieved using advanced data analysis techniques, we can expect more optimized operations and maintenance. This paper proposes a framework and describes associated methodologies for in-situ thermal performance analysis, which differs from conventional performance monitoring. The methodologies are effective for monitoring, diagnosis, and prognosis in pursuit of CBM. Our enabling techniques cover the intelligent removal of random and systematic errors, deviation detection between a best condition and a currently measured condition, degradation diagnosis using a structured knowledge base, and prognosis for decision-making about maintenance tasks. We also discuss how our new methods can be incorporated with existing performance tests. We provide guidance and directions for developers and end-users interested in in-situ thermal performance management, particularly in NPPs with large steam turbines.

• The Korean Journal of Financial Management
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• v.11 no.1
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• pp.263-284
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• 1994

This study examines the monitoring effects of institutions, outside directors, and outside blockholders by seeing managers' selection of antitakeover measures. In this paper, we hypothesize that managers use antitakeover techniques to entrench themselves when they are not monitored closely. Consequently, we hypothesize that institutional ownership, outside membership on board of directors, outside directors ownership, and outside blockholder ownership are less in firms which adopt harmful antitakeover measures. This paper analyzes whether the degree of monitoring by institutions, outside directors, and outside blockholders influences managers' adoption of different types of takeover defenses. We find interesting empirical results. First, aggregate institutional ownership is positively correlated with the likelihood of antitakeover techniques adoption. This result implies that institutional investors are passive. Second, total and active blockholder owner-ship is higher at firms that do not propose any defensive tactics. passive blockholder owner-ship is highest at fair price firms but low at poison pills firms. Ownership concentration by outside investors increases monitoring and reduces agency problems. Thirid, outside board monitoring is ineffective.

• Journal of the Korea institute for structural maintenance and inspection
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• v.5 no.3
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• pp.191-201
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• 2001

In spite of the increasing construction of segmental PSC box girder bridges, the techniques associated with real-time monitoring, construction control and safety assessment during construction have been less developed compared with the construction techniques. Thus, the development of an integrated system including real-time measurement and monitoring, control and safety assessment system during construction is necessary fur more safe and precise construction of the bridges. This study presents a prototype integrated monitoring system for preventing abnormal behavior and accidents under construction stages, that consist of behavior control system for precise construction, reliability-based safety assessment system, and structural analysis. Also, a prototype software system is developed on the basis of the proposed model. It is successfully applied to the Sea-Hae Grand Bridge built by FCM. The integrated system model and software system can be utilized for the safe and precise construction of segmental PSC bridges during construction.

• Structural Monitoring and Maintenance
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• v.3 no.3
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• pp.259-276
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• 2016

Historically the UK has been a pioneer and early adopter of experimental investigation techniques on new and operation structures, a technology that would now be descried as 'structural health monitoring' (SHM), yet few of these investigations have been enduring or carried out on the long span or tall structures that feature in flagship SHM applications in the Far East.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.46-46
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• 2000

A quadruped monitoring robot is introduced. The robot has several features that poses arbitrary position thanks to a 4-wheel hive mechanism, transmits an image and command data via RF wireless communication, and moreover, the imaged date are transferred through a network communication. The robot plays a role in monitoring what is happening around the robot and covers wide range due to a moving camera operated by the 4-wheel mechanism. The robot system can be applied k versatile models based the distinguished techniques introduced in this paper