| Anchor bolt has been widely used in coal mine,slope and other engineering construction,but the complexity of geological conditions leads to the inevitable quality problems and safety hazards in the construction process of anchor bolt,and major engineering accidents caused by anchor defects occur from time to time.Therefore,it is of great significance to strengthen the inspection of anchor bolt anchoring quality and ensure the stability and safety of anchor engineering.Thus,based on the ultrasonic guided wave nondestructive testing technology,the anchor bolt signals without defects and with defects were studied in this paper.The propagation mechanism of guided wave in the anchor system was analyzed,and then the length and location of defects in the anchor body were identified,which provides reference for the evaluation of bolt anchoring quality by nondestructive testing technology.Firstly,the propagation law of guided wave in the anchor bolt was analyzed,and the dispersion equation of longitudinal guided wave in the anchor bolt was established and solved.The optimal excitation frequency of guided wave propagation was obtained by the dispersion curves of group velocity,phase velocity and wave number,the reduction of guided wave modes was helpful for signal analysis and has provided a theoretical basis for numerical simulation research.Secondly,ultrasonic guided wave tests were carried out on anchor bolts without defects and with different defect lengths.The low frequency signal as decomposed by db5 wavelet 5 scale was used to extract the reflected echo information and identify the position of feature points on the anchorage end face.The energy ratio parameter k was introduced to represent the anchoring quality of bolt,and the corresponding relationship between k value and the extreme value of anchoring end face signal was established.Through comparative analysis of k values under different anchoring states,the defect length ld increases logarithmically with the increase of k values.The calculation formula between the energy ratio parameter k and the defect length ld was proposed to realize the identification of the anchoring defect length.Thirdly,according to the test results of anchor bolt at different defect positions,the signals were measured from the perspective of complexity.Defects increase the complexity of the detection signal,and the multiscale entropy of the anchorage system with defects is higher than that without defects.With the increase of scale factor,entropy value increases gradually.Moreover,the farther the distance between the defect and the anchoring start face,the higher the complexity of the signal,and the greater the deviation of the entropy curve of the signal with defect and without defect.PMSE was proposed to quantitatively describe the difference between the two signal entropy curves,the relationship between PMSE and the distance x between the defect and the starting end of anchorage was established,and the variation law of the two accorded with the exponential relationship,which realized the identification of the defect location.Finally,a numerical simulation study is carried out on the anchor bolts with changes in the distribution position of a single defect,the number of defects,and the change in the distribution position.The corresponding relationships among the position,number and length of the defects and the signal complexity of the anchorage system were established by using the multiscale entropy method.At lower scales,the sample entropy values of the specimens are relatively close;as the scale factor increases,the entropy curve gradually rises,and all reach the highest entropy value at the 20th scale.The simulation results of the distribution position change of a single defect are consistent with the experimental entropy curve.When the number and distribution of defects change,the increase of defect number has little effect on signal complexity.With the increase of defect length,the change of entropy curve is obvious,which proves the change of defect length is the main reason of signal complexity. |