Research On Metal Magnetic Memory Signal Quantitative Feature Of Welding Crack

Welding crack is one of the most dangerous factors that caused the welding joint of oil and gas pipeline invalidation. It is an important application that non-destructive test (NDT) technology is used to test the welding crack. As a brand-new NDT method, Metal Magnetic Memory (MMM) testing technology, which used the relation between the stress concentration of inner material and the scattering magnetic field on the material surface, has a great potential in the NDT application of early damnification of material.This dissertation concentrates on the difficult problem that the quantitative inspection of welding crack, which used the contemporaneity signal processing and neural network technology, the relation of stress concentration and MMM signal based on theoretical analysis and experiments or testing is researched, and the MMM signal feature of welding crack is extracted at the same time. The main achievements of this dissertation are as follows:The connection of stress concentration and MMM signal has been researched. The concept of magnetic field gradient index is put forward, the method that determined the critical state of the ferromagnetic material inner stress concentration is established and the critical magnetic field gradient index of X70 pipeline steel is determined; the amplitude spectrum entropy effected by stress degree is studied, through the relation of amplitude spectrum entropy and MMM signal, the stress state can be determined; the relation between stress and correlation dimension of MMM signal is investigation. Research shows that with the stress degree increase, the correlation dimension of MMM signal decrease, when the material ate the state of plastic nature, the correlation dimension of MMM signal will under the value 1.3.The MMM signal feature of welding crack is extracted. The wavelet energy spectrum of MMM signal, which includes scale- wavelet energy spectrum and space wavelet energy spectrum, is employed to denote the welding crack. The wavelet analysis is employed to decomposition the detail section form MMM signal, and the spectrum amplitude is obtained through Fourier transformation. The spectrum amplitude reflects the degree of stress concentration which can distinguish crack from general stress concentration; the quantitative inspection of welding crack is implemented with the wave characteristic of MMM signal and with its differential coefficient.With the MMM signal characteristic of welding crack as input parameter, the neural network is established that is used to recognize the welding crack quantitative and intelligence. The MMM quantitative inspection system is development successful with the software VB6.0 and Matlab which contact with ActiveX.