A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Improvement on health monitoring system using self-diagnosis materials for practical applications
In practical health monitoring of large sized civil infrastructures, acquisition and processing of a great amount of data obtained by long term monitoring have become challenging tasks. Several innovative research using advanced technology such as distributed processing or data mining has been started to cope with these tasks. Meanwhile, the application of the sensor to memorize peak values can also be a simple and promising candidate. In order to evaluate residual performance of the structures after the catastrophic disaster such as earthquakes, detection of the maximum deformation or strain caused to the structures is essentially required. Then, the application of the sensor that is able to retain experienced information makes it possible to eliminate the necessity of continuous monitoring, and enables the assessment of maximum damage to the structures based only on the measurement conducted after the occurrence of the event. The authors have continuously conducted research on the development of electrical conductive sensors using carbon materials, and proposed them as self-diagnosis materials. In previous studies, the conductive fiber reinforced composite, the glass fiber reinforced plastics containing nano-sized carbon black particles, has been confirmed to respond sensitively against applied strain and memorize the peak value. Because the percolation structure formed from carbon black causes irreversible change in resistance, the sensor maintains the electrical resistance value corresponding to the applied peak strain. Applicability of our damage detection method using self-diagnosis materials to RC or steel structures has also been demonstrated by several experimental studies. In this paper, our recent achievements of research aiming to put developed method in practical use are shown in detail. Firstly, practical production system of materials using pultrusion process has been established. This mass production system is expected to reduce both cost and performance variation as a sensor. Secondly, measuring devices to enable versatile and efficient evaluation have also been developed. Finally, the effort to enlarge the scope of applied target of our methods has been made. Applicability of our system to damage detection of wooden houses is discussed based on the experiments using timber frame structures.
Improvement on health monitoring system using self-diagnosis materials for practical applications
In practical health monitoring of large sized civil infrastructures, acquisition and processing of a great amount of data obtained by long term monitoring have become challenging tasks. Several innovative research using advanced technology such as distributed processing or data mining has been started to cope with these tasks. Meanwhile, the application of the sensor to memorize peak values can also be a simple and promising candidate. In order to evaluate residual performance of the structures after the catastrophic disaster such as earthquakes, detection of the maximum deformation or strain caused to the structures is essentially required. Then, the application of the sensor that is able to retain experienced information makes it possible to eliminate the necessity of continuous monitoring, and enables the assessment of maximum damage to the structures based only on the measurement conducted after the occurrence of the event. The authors have continuously conducted research on the development of electrical conductive sensors using carbon materials, and proposed them as self-diagnosis materials. In previous studies, the conductive fiber reinforced composite, the glass fiber reinforced plastics containing nano-sized carbon black particles, has been confirmed to respond sensitively against applied strain and memorize the peak value. Because the percolation structure formed from carbon black causes irreversible change in resistance, the sensor maintains the electrical resistance value corresponding to the applied peak strain. Applicability of our damage detection method using self-diagnosis materials to RC or steel structures has also been demonstrated by several experimental studies. In this paper, our recent achievements of research aiming to put developed method in practical use are shown in detail. Firstly, practical production system of materials using pultrusion process has been established. This mass production system is expected to reduce both cost and performance variation as a sensor. Secondly, measuring devices to enable versatile and efficient evaluation have also been developed. Finally, the effort to enlarge the scope of applied target of our methods has been made. Applicability of our system to damage detection of wooden houses is discussed based on the experiments using timber frame structures.
Improvement on health monitoring system using self-diagnosis materials for practical applications
Verbesserung der Zustandsüberwachung mittels selbstdiagnostifizierender Anwendungen
Inada, H. (author) / Inada, Y. (author) / Okuhara, Y. (author) / Hayashi, Y. (author)
2009
9 Seiten, 12 Bilder, 4 Quellen
Conference paper
English
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