The authors have been studying the strain sensitive materials which are based on conductivity change resulting from structural change in percolation system. In this study, we have developed a maximum strain memory sensor, which enables to detect damage to structures easily even after a large earthquake. To confirm the performance as the sensor, tensile tests embedded into concrete specimen have been conducted. As a result, it is discovered that this sensor is sufficiently effective to diagnose cracks in the concrete structure.
In recent years, the importance of Structural Health Monitoring has been recognized but an SHM system still confronts serious problems related to complexity and cost in practical use. To solve these problems, the authors have developed the simple and smart SHM system by integrating self-diagnosis material and a wireless data measurement device. By installing this SHM system, it is possible to detect damage to structures easily even after a large earthquake or other disaster and also to inspect possible deterioration of a structure in a short time. As a practical matter this SHM system is expected to be very reliable, and when it is mass-produced it should have a low cost. To confirm the utility of the damage detection of a building after a large earthquake, the pre-production system was installed in a specimen simulating the beam-to-column connection part in a mid-size conventional reinforced concrete building, and a loading test was performed on the specimen. The effectiveness of the proposed system is demonstrated by the test results.
The authors have been continuously conducting a series of research works on the development of the fiber reinforced composites as self-diagnosis materials. The function to detect damage is based on the property of carbon materials as a conductor of electricity. The conductive fiber reinforced composite, which is the glass fiber reinforced plastics added carbon particles for electrical conductivity, has been confirmed to possess excellent sensitivity as a self-diagnosis materials. In this study, a self-diagnosis material with the ability to memorize damage history has been applied. Irreversible resistance changes dependent on the strain histories of the composites were utilized to achieve this ability. The authors have also developed an electrically conductive film sensor bonded on the concrete surface to detect cracks and measure crack width. The specimens of the reinforced concrete bridge pier columns were tested under quasi-static cyclic lateral loading. The performance of the proposed self-diagnosis materials to detect damage to concrete structures is evaluated through confirmation of the relationship between the extent of damage and the variation of electrical conductivity of self-diagnosis materials. On the basis of the obtained experimental results, the applicability of self-diagnosis materials to structural health monitoring for concrete structures are discussed in detail, and the practical monitoring techniques for structures are proposed.
The authors have developed an electrically conductive fiber reinforced composite that its electrical resistance changes almost in proportion to strain. This material was tested for its tensile and bond behaviors. As a result, it was discovered that this material applied for the strengthening of concrete structures is highly effective to diagnose cracks in the concrete.