Acoustic Emission And Electrochemical Noise In-situ Monitoring Of Corrosion Damages Of Nuclear-grade 304 Stainless Steel

The structural materials were continuously served in high temperature,high pressure radioactive aqueous environments,and corrosion damages including pitting corrosion,stress corrosion cracking(SCC),crevice corrosion,corrosion fatigue and so on sometimes happened,which seriously threaten the safe operation of the NPPs.Therefore,developing effective on-line monitoring techniques aiming for these corrosion damages is essential to ensure the safe operation of the NPPs.In addition,on-line and in-situ monitoring can provide the direct evidences of the evolution of the corrosion damages,which is benefit for the understanding of the corrosion mechanisms.This paper started with the two techniques which are suitable for NPPs,namely acoustic emission(AE)and electrochemical noise(EN),firstly studied the ability of AE and EN to monitoring corrosion damages,especially SCC and pitting corrosion from two aspects of data acquisition and signal interpretation,then the two techniques were coupled to monitor SCC in high temperature and high pressure water.This paper was mainly focused on the signal processing methods and the relationship between in-situ signals and corrosion damages.The progress is as fo lows.Studied the AE characteristics of 304 stainless steel generated by SCC in high temperature and high pressure water.Both burst and continuous waveforms were monitored.Through relating the different waveforms of the AE signals with the SCC process,it was found that the burst signals originated from the residual ligament tear and continuous signals were derived from the plastic deformation of the crack tip.Meanwhile,it is proposed to discriminate the SCC mode by calculating the ratio of the burst signal and the continuous signal(?),the ? of transgranular SCC(TGSCC)is close to 1,and the ? decreased to 0 with increasing the ratio of intergranular stress corrosion cracking(IGSCC).Based on the traditional AE characteristic parameters,the random forest model is proposed to distinguish the AE waveform,and the classification accuracy rate is 98.6%.The combination of the above discriminant factor and the discriminant model can achieve the automatic monitoring of SCC.Studied the possibility of AE technique to quantitatively evaluate the SCC crack growth rate of sensitized 304 stainless steel in high temperature and high pressure water.Meanwhile,the recurrence quantification analysis(RQA)method was used to distinguish the AE waveform.It is found that the RQA parameters can better reflect the difference between the burst and the continuous waveform,the burst signal has high recurrence rate,average diagonal length and Shannon entropy,while the value of the continuous signal is low.Found there is a linear relationship between the AE cumulative hits rate and the SCC crack growth rate,which provides an alternative possibility for quantitative evaluation of SCC in high temperature and high pressure water.Studied the EN characteristics of 304 stainless steel generated by uniform corrosion,pitting corrosion and passivation.It is found that to a certain extent the statistical parameters,shot noise parameters,wavelet parameters and RQA parameters can distinguish the three corrosion mechanisms.However,the discriminant accuracy is low.Proposed a novel pattern recognition system based on coupling the above characteristic parameters to identify the corrosion mechanisms,and the discrimination accuracy rate is 99.7%;The application value of the present pattern recognition system was evaluated,and found that the discriminant model can obtain satisfactory discriminant results in different materials and environments.Studied the physical meaning of RQA parameters of the EN signals generated by different pitting stages of 304 stainless steel.It was found that the metastable pitting of 304 stainless steel has high recurrence rate and deterministic rate,while stable pitting has low recurrence rate and deterministic rate.Studied the EN signal generated by SCC of 304 stainless steel in high temperature and high pressure water.The evolution of the EN signals was related with the SCC process by coupling AE.It is found that the annealed 304 stainless steel undergoed TGSCC under the synergy of high temperature and high pressure water and stress.Through the Weibull analysis of the EN signals,EN technique can separate the SCC events from the uniform corrosion.Found that with the development of SCC process,the Hilbert time-frequency spectrum of the EN signals gradually migrates from high frequency to low frequency,corresponding to the uniform corrosion,crack initiation and crack propagation.Coupling the AE and EN technique can in-situ monitor SCC in high temperature and high pressure water,AE technique is suitable for monitoring the crack propagation stage of SCC,while EN is more favorable to monitor the early stage of SCC crack initiation.