Damage Identification Of Reinforced Concrete Structures Based On Data-driven Model With Piezoelectric Impedance

Civil engineering structures are subject to erosion by natural disasters such as earthquakes,floods and strong winds,as well as their own aging and environmental factors during service.If the minor structural damage is not detected in time,the continuous development may lead to the destruction of structural elements.With further development,a sudden failure of the structural overall stability can cause the major accidents and the accompanying heavy losses to life or property.Therefore,it is of great scientific and engineering significance to monitor the health status of civil engineering structures in service in real time and to identify the initial minor damage in time in service.Faced with the huge data set of health monitoring system,the traditional structural health status assessment system has some limitations in data processing.It is urgent to establish a simple and efficient data-driven algorithm model.In this dissertation,the reinforced concrete elements are taken as the research object.The damage identification tests of the elements specimens pasted with the piezoelectric ceramics(PZT)sensor on the surface under various working conditions are carried out based on the high sensitivity of the piezoelectric impedance characteristics to minor damage.The damage identification test data is analyzed by the data-driven algorithm model,and the temperature effect is also considered.In this dissertation,the main research works and results include:1.The effect of environmental temperature factors on the damage identification results of the reinforced concrete structures based on PZT piezoelectric impedance is investigated.Four self-made PZT sensors are pasted on the surface of reinforced concrete specimens.Damage identification is carried out by comparing the electrical conductance signals of PZT-reinforced concrete specimens before and after damage,and the effect of temperature was considered.The sensor is found to identify the damage in the specimen under the same temperature condition.While changing the temperature under the same damage condition;the admittance curve of the sensor has high temperature sensitivity that the curve shifts to the left as the temperature increases.2.The influence of the combined action of the damage and temperature on the conductance curve(admittance curve)of the PZT sensor is discussed.The sensor is found to be more sensitive to the changes of the external environment when the two factors are considered simultaneously.Seen from the admittance curve,the increase of the damage or the temperature can both cause the horizontal shift of the curve to the left.Although there are still overlapping numerical points between the data,the two factors are obviously different.3.The feasibility of damage identification for reinforced concrete structures based on piezoelectric impedance data and principal component analysis(PCA)algorithm model is studied.The data-driven model can solve the problem of overlapping numerical points in the traditional impedance analysis method by extracting the data features of different influencing factors separately.After feature extraction by principal component analysis,the algorithm model uses self-organizing mapping to cluster and visualize the data to get the final analysis results.The results that the algorithm model can identify effectively microdamage in reinforced concrete structures,and can distinguish the effect of temperature on the sensors effectively from the changes caused by damage demonstrate the feasibility of the proposed model in damage identification.4.The feasibility that the damage of the reinforced concrete structures can be identified based on piezoelectric impedance data and kernel principal component analysis(KPCA)algorithm is researched.Numerical and experimental results show that the proposed model can identify the micro-damage in the reinforced concrete specimens and distinguish the effect of temperature on the sensor from that of damage.The calculation results of the algorithm model being not affected by the initial state of the structure(health or not)demonstrate better usability in the practical applications.Finally,the influence of low temperature environment is studied,and the results show that the micro-damage in the reinforced concrete structures can be identified accurately by the combination of the datadriven model with the piezoelectric impedance monitoring data.The influence of environmental change on the determination results can be reduced.