Linsheng Huo

Crack detection and leakage monitoring on reinforced concrete pipe

Reinforced concrete underground pipelines are some of the most widely used types of structures in water transportation systems. Cracks and leakage are the leading causes of pipeline structural failures which directly results in economic losses and environmental hazards. In this paper, the authors propose a piezoceramic based active sensing approach to detect the cracks and the further leakage of concrete pipelines. Due to the piezoelectric properties, piezoceramic material can be utilized as both the actuator and the sensor in the active sensing approach. The piezoceramic patch, which is sandwiched between protective materials called smart aggregates, can be safely embedded into concrete structures. Circumferential and axial cracks were investigated. A wavelet packet-based energy analysis was developed to distinguish the type of crack and determine the further leakage based on different stress wave energy attenuation propagated through the cracks.

Monitoring of Grouting Compactness in a Post-Tensioning Tendon Duct Using Piezoceramic Transducers

A post-tensioning tendon duct filled with grout can effectively prevent corrosion of the reinforcement, maintain bonding behavior between the reinforcement and concrete, and enhance the load bearing capacity of concrete structures. In practice, grouting of the post-tensioning tendon ducts always causes quality problems, which may reduce structural integrity and service life, and even cause accidents. However, monitoring of the grouting compactness is still a challenge due to the invisibility of the grout in the duct during the grouting process. This paper presents a stress wave-based active sensing approach using piezoceramic transducers to monitor the grouting compactness in real time. A segment of a commercial tendon duct was used as research object in this study. One lead zirconate titanate (PZT) piezoceramic transducer with marble protection, called a smart aggregate (SA), was bonded on the tendon and installed in the tendon duct. Two PZT patch sensors were mounted on the top outside surface of the duct, and one PZT patch sensor was bonded on the bottom outside surface of the tendon duct. In the active sensing approach, the SA was used as an actuator to generate a stress wave and the PZT sensors were utilized to detect the wave response. Cement or grout in the duct functions as a wave conduit, which can propagate the stress wave. If the cement or grout is not fully filled in the tendon duct, the top PZT sensors cannot receive much stress wave energy. The experimental procedures simulated four stages during the grout pouring process, which includes empty status, half grouting, 90% grouting, and full grouting of the duct. Experimental results show that the bottom PZT sensor can detect the signal when the grout level increases towards 50%, when a conduit between the SA and PZT sensor is formed. The top PZT sensors cannot receive any signal until the grout process is completely finished. The wavelet packet-based energy analysis was adopted in this research to compute the total signal energy received by PZT sensors. Experimental results show that the energy levels of the PZT sensors can reflect the degree of grouting compactness in the duct. The proposed method has the potential to be implemented to monitor the tendon duct grouting compactness of the reinforced concrete structures with post tensioning.

Impedance-Based Pre-Stress Monitoring of Rock Bolts Using a Piezoceramic-Based Smart Washer—A Feasibility Study

Pre-stress degradation or looseness of rock bolts in mining or tunnel engineering threatens the stability and reliability of the structures. In this paper, an innovative piezoelectric device named a “smart washer” with the impedance method is proposed with the aim of developing a real-time device to monitor the pre-stress level of rock bolts. The proposed method was verified through tests on a rock bolt specimen. By applying high-frequency sweep excitations (typically >30 kHz) to the smart washer that was installed on the rock bolt specimen, we observed that the variation in impedance signatures indicated the rock bolt pre-stress status. With the degradation of rock bolt pre-stress, the frequency in the dominating peak of the real part of the electrical impedance signature increased. To quantify the effectiveness of the proposed technique, a normalized root mean square deviation (RMSD) index was developed to evaluate the degradation level of the rock bolt pre-stress. The experimental results demonstrated that the normalized RMSD-based looseness index, which was computed from the impedance value detected by the “smart washer”, increased with loss of the pre-stress of the rock bolt. Therefore, the proposed method can effectively detect the degradation of rock bolt pre-stress, as demonstrated by experiments.

Detection of Debonding Between Fiber Reinforced Polymer Bar and Concrete Structure Using Piezoceramic Transducers and Wavelet Packet Analysis

Fiber reinforced polymer (FRP), a composite material with high corrosion resistance and high strength-to-weight ratio, has been increasingly used in reinforced concrete structures. The effectiveness of the structures depends on the bonding behavior between FRP composites and concrete structures. Therefore, detection of the debonding between the FRP materials and the hosting concrete structure is of great importance to ensure the structural safety. This paper proposes a stress wave-based active sensing approach to monitor the debonding process of FRP bar with the hosting concrete structure. One shear-type lead zirconate titanate (PZT) patch bonded on the outer surface of the FRP bar was used as an actuator to generate stress wave. Two smart aggregates (SAs), which were fabricated by sandwiching a shear type PZT patch between two protection marble pieces, were embedded in the hosting concrete structure to detect the wave response. The occurrence of debonding between the FRP bar and the hosting concrete structure attenuates the wave propagation. An FRP bar reinforced concrete specimen was designed and fabricated in laboratory. A pullout test was conducted to simulate different degrees of debonding damage. The attenuation of the stress wave due to debonding was clearly observed from the signal received by SAs in both time and frequency domain. Furthermore, a damage index based on wavelet packet analysis was developed to evaluate the debonding status. Experimental results demonstrate that the proposed method has potentials to detect different degrees of debonding damage of FRP bar reinforced concrete composite structures.

Health monitoring of cuplok scaffold joint connection using piezoceramic transducers and time reversal method

Cuplok scaffolds are widely used to form temporary supporting structures when constructing bridges and other structures all over the world. The safety and stability of cuplok scaffolds are important issues during construction. Cuplok scaffolds are subjected to various types of vibrations, which may loosen the cuplok connection, negatively impacting the stability of the structure and even leading to severe accidents. In this paper, the authors propose a time reversal (TR) method to monitor the looseness status of the cuplok connection by using stress wave-based active sensing. Lead zirconate titanate (PZT), a commonly used piezoceramic material with a strong piezoelectric effect, is employed. In the proposed approach, PZT patches are used as sensors and actuators to monitor the cuplok joint looseness. One PZT patch is bonded to the vertical bar and two PZT patches are bonded to the cross bars of the cuplok scaffold. The PZT patch on the vertical bar is used as an actuator to generate a stress wave and the other two PZT patches are used as sensors to detect the propagated waves through the cuplok connection, the looseness of which will directly impact the stress wave propagation. The TR method is used to analyse the transmitted signal between the PZT patches through the cuplok connection. By comparing the peak values of the TR focused signal, it can be found that the peak value increases as the tightness of the cuplok connection increases. Therefore, the peak value of the TR focused signal can be used to monitor the tightness of the cuplok connection. In addition, the experimental results demonstrated that the TR method is superior to the energy method in consistency, sensitivity and anti-noise properties.

Structural health monitoring of multi-spot welded joints using a lead zirconate titanate based active sensing approach

Failures of spot welded joints directly reduce the load capacity of adjacent structures. Due to their complexity and invisibility, real-time health monitoring of spot welded joints is still a challenge. In this paper, a lead zirconate titanate (PZT) based active sensing approach was proposed to monitor the structural health of multi-spot welded joints in real time. In the active sensing approach, one PZT transducer was used as an actuator to generate a guided stress wave, while another one, as a sensor, detected the wave response. Failure of a spot welded joint reduces the stress wave paths and attenuates the wave propagation energy from the actuator to the sensor. A total of four specimens made of dual phase steel with spot welds, including two specimens with 20 mm intervals of spot welded joints and two with 25 mm intervals, were designed and fabricated for this research. Under tensile tests, the spot welded joints successively failed, resulting in the PZT sensor reporting decreased received energy. The energy attenuations due to the failures of joints were clearly observed by the PZT sensor signal in both the time domain and frequency domain. In addition, a wavelet packet-based spot-weld failure indicator was developed to quantitatively evaluate the failure condition corresponding to the number of failed joints.

Smart washer-a piezoceramic-based transducer to monitor looseness of bolted connection

The safety of a bolted connection, as one of the most common ways of making two or more parts/components work together in engineering structures, is very important in order to ensure the health of the whole structure. However, bolt loosening or pre-load degradation may induce the failure of the bolt connection, threatening the normal operation of the systems structure. As a result, it would be beneficial if the health condition of the bolt connection could be monitored in real time. In this paper, a smart washer, fabricated by embedding a piezoceramic patch into two pre-machined flat metal rings, was invented and then introduced as a transducer to detect the looseness of a bolted connection. A simple specimen, which consists of two steel plates connected by a nut, a bolt and two smart washers, was fabricated as the test object to study the performance of the smart washers (SWs). For the specimen, a smart washer was used as an actuator to generate a stress wave, and the other one was used as a sensor to detect the propagated wave that traveled through the interface of the bolted connection. A time reversal method was employed to quantify the energy of the stress wave propagating between the two washers, and thus it was possible to build a relationship between the extent of any pre-loaded degradation of the bolt connection and the response signal of the stress wave traveling between the two washers. In addition, a normalized bolt looseness index was proposed for evaluating the looseness of a bolt connection based on wavelet energy analysis.

Damage Detection of Structures for Ambient Loading Based on Cross Correlation Function Amplitude and SVM

An effective method for the damage detection of skeletal structures which combines the cross correlation function amplitude (CCFA) with the support vector machine (SVM) is presented in this paper. The proposed method consists of two stages. Firstly, the data features are extracted from the CCFA, which, calculated from dynamic responses and as a representation of the modal shapes of the structure, changes when damage occurs on the structure. The data features are then input into the SVM with the one-against-one (OAO) algorithm to classify the damage status of the structure. The simulation data of IASC-ASCE benchmark model and a vibration experiment of truss structure are adopted to verify the feasibility of proposed method. The results show that the proposed method is suitable for the damage identification of skeletal structures with the limited sensors subjected to ambient excitation. As the CCFA based data features are sensitive to damage, the proposed method demonstrates its reliability in the diagnosis of structures with damage, especially for those with minor damage. In addition, the proposed method shows better noise robustness and is more suitable for noisy environments.

Fault Tolerant Control for Civil Structures Based on LMI Approach

The control system may lose the performance to suppress the structural vibration due to the faults in sensors or actuators. This paper designs the filter to perform the fault detection and isolation (FDI) and then reforms the control strategy to achieve the fault tolerant control (FTC). The dynamic equation of the structure with active mass damper (AMD) is first formulated. Then, an estimated system is built to transform the FDI filter design problem to the static gain optimization problem. The gain is designed to minimize the gap between the estimated system and the practical system, which can be calculated by linear matrix inequality (LMI) approach. The FDI filter is finally used to isolate the sensor faults and reform the FTC strategy. The efficiency of FDI and FTC is validated by the numerical simulation of a three-story structure with AMD system with the consideration of sensor faults. The results show that the proposed FDI filter can detect the sensor faults and FTC controller can effectively tolerate the faults and suppress the structural vibration.

Influence of Axial Load on Electromechanical Impedance (EMI) of Embedded Piezoceramic Transducers in Steel Fiber Concrete

With the advantages of high tensile, bending, and shear strength, steel fiber concrete structures have been widely used in civil engineering. The health monitoring of concrete structures, including steel fiber concrete structures, receives increasing attention, and the Electromechanical Impedance (EMI)-based method is commonly used. Structures are often subject to changing axial load and ignoring the effect of axial forces may introduce error to Structural Health Monitoring (SHM), including the EMI-based method. However, many of the concrete structure monitoring algorithms do not consider the effects of axial loading. To investigate the influence of axial load on the EMI of a steel fiber concrete structure, concrete specimens with different steel fiber content (0, 30, 60, 90, 120) (kg/m3) were casted and the Lead Zirconate Titanate (PZT)-based Smart Aggregate (SA) was used as the EMI sensor. During tests, the step-by-step loading procedure was applied on different steel fiber content specimens, and the electromechanical impedance values were measured. The Normalized root-mean-square deviation Index (NI) was developed to analyze the EMI information and evaluate the test results. The results show that the normalized root-mean-square deviation index increases with the increase of the axial load, which clearly demonstrates the influence of axial load on the EMI values for steel fiber concrete and this influence should be considered during a monitoring or damage detection procedure if the axial load changes. In addition, testing results clearly reveal that the steel fiber content, often at low mass and volume percentage, has no obvious influence on the PZT’s EMI values. Furthermore, experiments to test the repeatability of the proposed method were conducted. The repeating test results show that the EMI-based indices are repeatable and there is a great linearity between the NI and the applied loading.