In this study, the piezoceramic smart aggregates (PSAs) are used to perform structural health monitoring (SHM) and detect crack damage on the ordinary reinforced concrete (RC) and New RC column. The piezoceramic smart aggregates (PSAs) are utilized as actuators and sensors, respectively. In the ordinary RC column, the sensors are installed at two depth ranges (40-50 and 70-80 mm) beneath the surface of the column to investigate the effect of the sensor depth on the damage index, while in the study on the New RC specimen, the sensors are installed in different height to investigate the optimum locations of the sensor.
The energy and amplitude-based damage indexes are developed. Both approaches follow the same trend under various drift ratios of the specimen. However, the value of energy-based damage index is much higher than the amplitude index for all peak drift ratio of the specimen. From the study on the ordinary RC column using post-embedded PSAs, it recommends a depth of 80 mm as optimal for post-embedded smart aggregates, since it could receive more stable signals in various frequencies. According to the study on New RC column, two different heights range are recommended for installing the sensor. First is around the mid-height of the column, and second is near the top of the column. The damage indexes obtained from the sensors that are installed in these locations have highest correlation values with the maximum residual crack width.
In the proposed health monitoring approach using PSAs, the equation to predict the maximum residual crack width and damage index smart aggregates are developed. The normalized damage index equation which in this study is referred to as “crack damage index” is introduced and used to calculate the limiting value for each damage level. The suggested value of the crack damage index for each damage level is also provided. The energy, strength and stiffness reduction factors of RC column for each damage level, which correlate with the crack damage index are also presented herein. These results demonstrate that the proposed smart aggregate has the potential to be used as a tool for SHM on an RC column.

In this study, the piezoceramic smart aggregates (PSAs) are used to perform structural health monitoring (SHM) and detect crack damage on the ordinary reinforced concrete (RC) and New RC column. The piezoceramic smart aggregates (PSAs) are utilized as actuators and sensors, respectively. In the ordinary RC column, the sensors are installed at two depth ranges (40-50 and 70-80 mm) beneath the surface of the column to investigate the effect of the sensor depth on the damage index, while in the study on the New RC specimen, the sensors are installed in different height to investigate the optimum locations of the sensor.
The energy and amplitude-based damage indexes are developed. Both approaches follow the same trend under various drift ratios of the specimen. However, the value of energy-based damage index is much higher than the amplitude index for all peak drift ratio of the specimen. From the study on the ordinary RC column using post-embedded PSAs, it recommends a depth of 80 mm as optimal for post-embedded smart aggregates, since it could receive more stable signals in various frequencies. According to the study on New RC column, two different heights range are recommended for installing the sensor. First is around the mid-height of the column, and second is near the top of the column. The damage indexes obtained from the sensors that are installed in these locations have highest correlation values with the maximum residual crack width.
In the proposed health monitoring approach using PSAs, the equation to predict the maximum residual crack width and damage index smart aggregates are developed. The normalized damage index equation which in this study is referred to as “crack damage index” is introduced and used to calculate the limiting value for each damage level. The suggested value of the crack damage index for each damage level is also provided. The energy, strength and stiffness reduction factors of RC column for each damage level, which correlate with the crack damage index are also presented herein. These results demonstrate that the proposed smart aggregate has the potential to be used as a tool for SHM on an RC column.

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