At early ages of concrete structures, strength monitoring is important to determine the structures' readiness for service. Piezoelectric-based strength monitoring methods provide an innovative experimental approach to conduct concrete strength monitoring at early ages. In this paper, piezoelectric transducers in the form of 'smart aggregates' are embedded into the concrete specimen during casting. Piezoceramic materials can be used as actuators to generate high frequency vibrating waves, which propagate within concrete structures; meanwhile, they can also be used as sensors to detect the waves. The smart aggregate is a one cubic inch, precast concrete block with a wired, embedded PZT (lead zirconate titanate, a type of piezoceramic) patch. The strength development of concrete structures is monitored by observing the development of harmonic response amplitude from the embedded piezoelectric sensor at early ages. From experimental results, the amplitude of the harmonic response decreases with increasing concrete strength. The concrete strength increases at a fast rate during the first few days and at a decreasing rate after the first week. Concordantly, the amplitude of the harmonic response from the piezoelectric sensor drops rapidly for the first week and continues to drop slowly as hydration proceeds, matching the development of the concrete strength at early ages. Concrete is heterogeneous and anisotropic, which makes it difficult to analyze mathematically. Fuzzy logic has the advantage of conducting analysis without requiring a mathematical model. In this paper, a fuzzy logic system is trained to correlate the harmonic amplitude with the concrete strength based on the experimental data. The experimental results show that the concrete strength estimated by the trained fuzzy correlation system matches the experimental strength data. The proposed piezoelectric-based monitoring method has the potential to be applied to strength monitoring of concrete structures at early ages.

In this paper, a smart aggregate-based approach is proposed for the structural health monitoring of a concrete shear wall structure. The piezoceramic-based smart aggregates were distributed in predetermined locations prior to the casting of the concrete structure to form an active-sensing system for the health monitoring purpose. To evaluate the damage in different areas, the concrete shear wall was sectioned into sub-domains and a wavelet-packet-based damage index matrix is proposed to evaluate the health status in these sections. A cyclic loading procedure was applied to gradually fail the concrete shear wall and the proposed structural health monitoring approach was used to perform structural health monitoring during this loading procedure. The experimental results have shown that the proposed smart aggregate-based approach effectively evaluated the damage status in different areas and detected the precautionary point to predict the structural failure. The proposed approach has the potential to be applied to the structural health monitoring of large-scale concrete shear wall structures.

Structural health monitoring (SHM) systems can improve the safety and reliability of structures, reduce maintenance costs, and extend service life. Research on concrete SHMs using piezoelectric-based smart aggregates have reached great achievements. However, the newly developed techniques have not been widely applied in practical engineering, largely due to the wiring problems associated with large-scale structural health monitoring. The cumbersome wiring requires much material and labor work, and more importantly, the associated maintenance work is also very heavy. Targeting a practical large scale concrete crack detection (CCD) application, a smart aggregates-based wireless sensor network system is proposed for the CCD application. The developed CCD system uses Zigbee 802.15.4 protocols, and is able to perform dynamic stress monitoring, structural impact capturing, and internal crack detection. The system has been experimentally validated, and the experimental results demonstrated the effectiveness of the proposed system. This work provides important support for practical CCD applications using wireless smart aggregates.

This paper aims to set up a finite element model using piezoelectric elements to realize pipeline structure damage identification analysis. Ultrasonic guided wave propagation characteristics and damage identification of pipeline structures are analyzed by the ABAQUS software. The pulse-echo method using an L(0, 2) mode impulse guided wave with a central frequency of 70 kHz is applied to evaluate different size circumferential cracks. An experiment was performed for the validation of the numerical analysis results. Both of the results show that the proposed FEM model with piezoelectric elements can efficiently reveal the dynamic behaviors, which can be used in much more precise numerical simulations than the equivalent dynamic displacement loading method.