An active sensing diagnostic system for reinforced concrete SHM has been under investigation. PZT elements were mounted on the surface of reinforced bar to form a smart rebar system. Test results show that the system based guided wave can detect the damage of the concrete structure, and it is sensitive to anomalies in structures. But the damping of concrete is high, which causes energy to be dissipated fast when transmitting through it, and lead to the amplitude of output signal be too small to be used in real engineering application. System optimization has been performed based on experimental tests and numerical simulation. By changing both PZT layout and size, test results showed that the output signals have been increased significantly with magnitudes. Then the optimized active sensing system has been applied to explore the detection of the fell-off of CA layer. CA layer fell-off is the most common defect in ballastless track, one of the key element of high speed railway structure. Through the experimental tests, it proves that the amplitude of output signal will be decreased exponentially with increase of the thickness of covered concrete around the rebar, which implies that the output signal’s amplitude would be increased noticeably with CA mortar layer’s fell-off. This leads to a potential method to monitor the fell-off of CA mortar layer. Keywords: PZT rebar, Signal optimization, CA mortar layer fell-off detection
doi: 10.12783/SHM2015/241