Haichang Gu

Concrete structural health monitoring using embedded piezoceramic transducers

Health monitoring of reinforced concrete bridges and other large-scale civil infrastructures has received considerable attention in recent years. However, traditional inspection methods (x-ray, C-scan, etc) are expensive and sometimes ineffective for large-scale structures. Piezoceramic transducers have emerged as new tools for the health monitoring of large-scale structures due to their advantages of active sensing, low cost, quick response, availability in different shapes, and simplicity for implementation. In this research, piezoceramic transducers are used for damage detection of a 6.1 m long reinforced concrete bridge bent-cap. Piezoceramic transducers are embedded in the concrete structure at pre-determined spatial locations prior to casting. This research can be considered as a continuation of an earlier work, where four piezoceramic transducers were embedded in planar locations near one end of the bent-cap. This research involves ten piezoceramic patches embedded at spatial locations in four different cross-sections. To induce cracks in the bent-cap, the structure is subjected to loads from four hydraulic actuators with capacities of 80 and 100 ton. In addition to the piezoceramic sensors, strain gages, LVDTs, and microscopes are used in the experiment to provide reference data. During the experiment, one embedded piezoceramic patch is used as an actuator to generate high frequency waves, and the other piezoceramic patches are used as sensors to detect the propagating waves. With the increasing number and severity of cracks, the magnitude of the sensor output decreases. Wavelet packet analysis is used to analyze the recorded sensor signals. A damage index is formed on the basis of the wavelet packet analysis. The experimental results show that the proposed methods of using piezoceramic transducers along with the damage index based on wavelet packet analysis are effective in identifying the existence and severity of cracks inside the concrete structure. The experimental results demonstrate that the proposed method has the ability to predict the failure of a concrete structure as verified by results from conventional microscopes (MSs) and LVDTs.

Health monitoring and rehabilitation of a concrete structure using intelligent materials

This paper presents the concept of an intelligent reinforced concrete structure (IRCS) and its application in structural health monitoring and rehabilitation. The IRCS has multiple functions which include self-rehabilitation, self-vibration damping, and self-structural health monitoring. These functions are enabled by two types of intelligent (smart) materials: shape memory alloys (SMAs) and piezoceramics. In this research, Nitinol type SMA and PZT (lead zirconate titanate) type piezoceramics are used. The proposed concrete structure is reinforced by martensite Nitinol cables using the method of post-tensioning. The martensite SMA significantly increases the concretes damping property and its ability to handle large impact. In the presence of cracks due to explosions or earthquakes, by electrically heating the SMA cables, the SMA cables contract and close up the cracks. In this research, PZT patches are embedded in the concrete structure to detect possible cracks inside the concrete structure. The wavelet packet analysis method is then applied as a signal-processing tool to analyze the sensor signals. A damage index is defined to describe the damage severity for health monitoring purposes. In addition, by monitoring the electric resistance change of the SMA cables, the crack width can be estimated. To demonstrate this concept, a concrete beam specimen with reinforced SMA cables and with embedded PZT patches is fabricated. Experiments demonstrate that the IRC has the ability of self-sensing and self-rehabilitation. Three-point bending tests were conducted. During the loading process, a crack opens up to 0.47 inches. Upon removal of the load and heating the SMA cables, the crack closes up. The damage index formed by wavelet packet analysis of the PZT sensor data predicts and confirms the onset and severity of the crack during the loading. Also during the loading, the electrical resistance value of the SMA cable changes by up to 27% and this phenomenon is used to monitor the crack width.

Health monitoring of reinforced concrete shear walls using smart aggregates

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.

An overheight vehicle-bridge collision monitoring system using piezoelectric transducers

With increasing traffic volume follows an increase in the number of overheight truck collisions with highway bridges. The detection of collision impact and evaluation of the impact level is a critical issue in the maintenance of a concrete bridge. In this paper, an overheight collision detection and evaluation system is developed for concrete bridge girders using piezoelectric transducers. An electric circuit is designed to detect the impact and to activate a digital camera to take photos of the offending truck. Impact tests and a health monitoring test were conducted on a model concrete bridge girder by using three piezoelectric transducers embedded before casting. From the experimental data of the impact test, it can be seen that there is a linear relation between the output of sensor energy and the impact energy. The health monitoring results show that the proposed damage index indicates the level of damage inside the model concrete bridge girder. The proposed overheight truck–bridge collision detection and evaluation system has the potential to be applied to the safety monitoring of highway bridges.

Multi-functional smart aggregate-based structural health monitoring of circular reinforced concrete columns subjected to seismic excitations

In this paper, a recently developed multi-functional piezoceramic-based device, named the smart aggregate, is used for the health monitoring of concrete columns subjected to shake table excitations. Two circular reinforced concrete columns instrumented with smart aggregates were fabricated and tested with a recorded seismic excitation at the structural laboratory at the University of Nevada—Reno. In the tests, the smart aggregates were used to perform multiple monitoring functions that included dynamic seismic response detection, structural health monitoring and white noise response detection. In the proposed health monitoring approach, a damage index was developed on the basis of the comparison of the transfer function with the baseline function obtained in the healthy state. A sensor-history damage index matrix is developed to monitor the damage evolution process. Experimental results showed that the acceleration level can be evaluated from the amplitude of the dynamic seismic response; the damage statuses at different locations were evaluated using a damage index matrix; the first modal frequency obtained from the white noise response decreased with increase of the damage severity. The proposed multi-functional smart aggregates have great potential for use in the structural health monitoring of large-scale concrete structures.

Progressive collapse of a two-story reinforced concrete frame with embedded smart aggregates

This paper reports the experimental and analytical results of a two-story reinforced concrete frame instrumented with innovative piezoceramic-based smart aggregates (SAs) and subjected to a monotonic lateral load up to failure. A finite element model of the frame is developed and analyzed using a computer program called Open system for earthquake engineering simulation (OpenSees). The finite element analysis (FEA) is used to predict the load–deformation curve as well as the development of plastic hinges in the frame. The load–deformation curve predicted from FEA matched well with the experimental results. The sequence of development of plastic hinges in the frame is also studied from the FEA results. The locations of the plastic hinges, as obtained from the analysis, were similar to those observed during the experiment. An SA-based approach is also proposed to evaluate the health status of the concrete frame and identify the development of plastic hinges during the loading procedure. The results of the FEA are used to validate the SA-based approach for detecting the locations and occurrence of the plastic hinges leading to the progressive collapse of the frame. The locations and sequential development of the plastic hinges obtained from the SA-based approach corresponds well with the FEA results. The proposed SA-based approach, thus validated using FEA and experimental results, has a great potential to be applied in the health monitoring of large-scale civil infrastructures.

Damping augmentation of nanocomposites using carbon nanofiber paper

Vacuum-assisted resin transfer molding (VARTM) process was used to fabricate the nanocomposites through integrating carbon nanofiber paper into traditional glass fiber reinforced composites. The carbon nanofiber paper had a porous structure with highly entangled carbon nanofibers and short glass fibers. In this study, the carbon nanofiber paper was employed as an interlayer and surface layer of composite laminates to enhance the damping properties. Experiments conducted using the nanocomposite beam indicated up to 200-700% increase of the damping ratios at higher frequencies. The scanning electron microscopy (SEM) characterization of the carbon nanofiber paper and the nanocomposites was also conducted to investigate the impregnation of carbon nanofiber paper by the resin during the VARTM process and the mechanics of damping augmentation. The study showed a complete penetration of the resin through the carbon nanofiber paper. The connectivities between carbon nanofibers and short glass fibers within the carbon nanofiber paper were responsible for the significant energy dissipation in the nanocomposites during the damping tests.

Wind turbine blade health monitoring with piezoceramic-based wireless sensor network

In this paper, a piezoceramic-based wireless sensor network (WSN) was developed for health monitoring of wind turbine blades with active sensing approach. The WSN system has an access point that coordinates the network and connects to a PC to control the wireless nodes. One wireless node functions as an actuator to excite an embedded piezoceramic patch with desired guided waves. The remaining wireless nodes function as sensors to detect and transmit the wave responses at distributed locations. The damage status inside the blade was evaluated through the analysis of the sensor signals. Based on wavelet packet analysis results, a damage index and a damage matrix were developed to evaluate the damage status at different locations. To verify the effectiveness of the proposed approach, a static loading test and a wind tunnel test were performed in the Laboratory of Joint Wind Tunnel and Wave Flume at Harbin Institute of Technology (HIT), China. Experimental results show that damage in wind turbine blades can be detected and evaluated by the proposed approach.

Active Vibration Suppression of a Smart Flexible Beam Using a Sliding Mode Based Controller

This article investigates robust active vibration suppression of a flexible beam with a low dominant frequency using piezoceramic sensor and actuators. The piezoceramic sensor and actuators are in patch form and are surface-bonded to the cantilevered end of the flexible beam. The robust sliding mode control, which has the advantages of being robust to plant parameter variation, insensitive to the unmodeled dynamics, and easy to implement, is adopted in this article for active vibration control of the flexible beam. Unlike other commonly used vibration suppression methods, such as positive position feedback control, strain rate feedback control, and lead compensation, the sliding mode controller requires almost no knowledge of the flexible beam. To avoid the chattering problem commonly associated with sliding mode control, a smooth switching function employing a hyperbolic tangent function is used. A low pass filter is applied to the output of the sliding mode controller to avoid excitation of the higher modes of the flexible beam. To demonstrate the advantage of sliding mode based active vibration reduction, its experimental results are compared with those of Proportional plus Derivative (PD) control and lead compensation. The comparison shows that the sliding mode controller reduces vibration of the flexible beam much more rapidly. To verify the robustness of the proposed sliding mode controller, vibration suppression of the beam is conducted for a case where the modal frequency of the beam is changed by adding masses. In addition, vibration suppression of the beam when subjected to a multi-modal excitation is also conducted. Experimental results demonstrate the robustness of the proposed controller with respect to varying model parameters and even the dynamics of higher modes.

Health monitoring of a concrete structure using piezoceramic materials

Health monitoring for reinforced concrete bridges and other large-scale civil infrastructure has received considerable attention in recent years. Traditional inspection methods (x-ray, C-scan etc.) are expensive and sometimes ineffective for large-scale structures. Piezoceramic transducers have emerged as new tools to health monitoring of large size structures due to the advantages of active sensing, low cost, quick response, availability in different shapes, and simplicity for implementation. In this research, piezoceramic transducers in the form of patches are used to detect internal cracks of a 6.1-meter long reinforced concrete bridge bent-cap. Piezoceramic patches are embedded in the concrete structure at pre-determined spatial locations prior to casting. This research can be considered as a continuation of an early work, where four piezoceramic patches were embedded in planar locations near one end of the bent-cap. This research involves ten piezoceramic patches embedded at spatial locations in four different cross-sections. To induce cracks in the bent-cap, the structure is subjected to loads from four hydraulic actuators with capacities of 80-ton and 100-ton. In addition to the piezoceramic sensors, strain gages, LVDTs, and microscopes are used in the experiment. During the experiment, one embedded piezoceramic patch is used as an actuator to generate sweep sinusoidal waves, and the other piezoceramic patches are used as sensors to detect the propagating waves. With the increase of number of and severity of cracks, the magnitude of the sensor output decreases. Wavelet packet analysis is used to analyze the recorded sensor signals. A damage index is formed on the basis of the wavelet packet analysis. The experimental results show that the proposed methods using piezoceramic transducers along with the damage index based on wavelet packet analysis is effective in identifying the existence and severity of cracks inside the concrete structure. The experimental results also show that the proposed method has the ability to predict the failure of concrete as verified by results from conventional microscopes (MS) and LVDTs.