Grouting Compactness Detection In Post-Tensioning Tendon Ducts Using Piezoceramic Ultrasonic Waves

In recent years,the prestressed concrete structure has been widely used in bridge construction all over the world.However,many factors such as unqualified construction materials and nonstandard construction process would cause grouting defects in practice,which seriously threatens the service life and operation safety of bridges.How to detect the grouting compactness of tendon ducts accurately and effectively has became an urgent problem to be solved.Piezoelectric ceramics could be used as actuator and sensor,and also have the advantages of low cost,low power consumption,wide frequency response range and so on,which make them have great potential in the field of structural damage detection and health monitoring.A method based on wavelet packet transform(WPT)and Bayes classifier is proposed to evaluate grouting quality in post-tensioning tendon ducts by using stress waves generated and received by piezoceramic transducers.A series of numerical simulation and experimental research are carried out to verify the performance of the proposed grouting compactness detection method.The main contents of this thesis are listed as follows:(1)The multi-physical field coupling models for detecting grouting defects in prestressed tendon ducts are established to investigate the wave field distribution of ultrasonic generated by piezoceramic actuator under different grouting conditions,which helps to verify the feasibility of the proposed method and guide the experimental research.(2)Six kinds of grouting conditions(0% grouting,60% grouting,90% grouting,4cm cavity,1cm cavity,100% grouting)are designed according to the two typical grouting defects of partial grouting and cavity defects in practice.The strength of signals received by sensors grossly decreases with the increase of grouting defects,which meets well with simulation results.(3)WPT is applied to conduct time-frequency analysis on the received ultrasonic signals,and the WPT components are obtained.The energy vector of all the WPT components is constructed,which is used as the characteristic index for detecting the grouting compactness in tendon ducts.Compared with the traditional total energy of time domain waveform or total energy of WPT components,the energy vector is more sensitive to grouting defects and contains more structural information.(4)The detection of grouting defects in practice inevitably has a certain randomness.Therefore,Bayes classifier is applied to identify and classify different grouting conditions.The results show that Bayes classifier with energy vector of WPT components could identify different grouting conditions with higher accuracy.(5)The proposed grouting compactness detection method based on piezoelectric ceramic ultrasonic could detect grouting compactness in tendon ducts with larger area along the length direction and has the potential to be applied at key spots of the tendon ducts in practice.Six typical grouting conditions have been investigated in this paper.If an unexpected grouting scenario occurs,the identification result of the proposed method would be the most similar class investigated in this paper.