摘要
The pull test is a damaging detection method that fails to measure the actual length of a bolt.Thus,the ultrasonic echo is an important non?destructive testing method for bolt quality detection.In this research,the variational modal decomposition(VMD)method is introduced into the bolt detection signal analysis.On the basis of morphological filtering(MF)and the VMD method,a VMD?combined MF principle is established into a bolt detection signal analysis method(MF?VMD).MF?VMD is used to analyze the vibration and actual bolt detection signals of the simulation.Results show that MF?VMD effectively separates intrinsic mode function,even under strong interference.In comparison with conventional VMD method,the proposed method can remove noise interference.An intrinsic mode function of the field detection signal can be effectively identified by reflecting the signal at the bottom of the bolt.
The pull test is a damaging detection method that fails to measure the actual length of a bolt. Thus,the ultrasonic echo is an important non-destructive testing method for bolt quality detection. In this research,the variational modal decomposition(VMD)method is introduced into the bolt detection signal analysis. On the basis of morphological filtering(MF) and the VMD method,a VMD-combined MF principle is established into a bolt detection signal analysis method(MF-VMD). MF-VMD is used to analyze the vibration and actual bolt detection signals of the simulation. Results show that MF-VMD effectively separates intrinsic mode function,even under strong interference. In comparison with conventional VMD method,the proposed method can remove noise interference. An intrinsic mode function of the field detection signal can be effectively identified by reflecting the signal at the bottom of the bolt.
基金
supported by the Key Project of the National Natural Science Foundation of China (No.51739006)
the Open Research Fund of the Fundamental Science on Radioactive Geology and Exploration Technology Laboratory (No.RGET1502)
the Open Research Fund of Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering (No.2017SDSJ05)
the Project of the Hubei Foundation for Innovative Research Groups (No.2015CFA025)
