Corrosion Damage Monitoring of Stainless Steel by Acoustic Emission

Transcription

1 Corrosion Damage Monitoring of Stainless Steel by Acoustic Emission Kaige Wu A, Seung-mi Lee B, Won-Sik Lee C, Dong-Pyo Hong D and Jai-Won Byeon A Abstract In this work, the acoustic emission signals of gas bubbling reaction during pitting corrosion of stainless steel 34 was investigated by acoustic emission(ae) technique and potentiodynamic method. The electrochemical and acoustical tests were carried out simultaneously at room temperature in a 3% NaCl solution acidified to ph 2 via a bubble-detected three-electrode system. The results showed that a short time delay was observed before AE signal detected after pit potential. This time delay was supposed to be closely correlated with a threshold of gas pressure for H 2 bubble to break-up, which again be associated with a minimum amount of corrosion. Considering the delay time, the AE signals of accumulative counts, rise time, duration in time domain shown three different stages with different signal features. The signals were compared by frequency analysis and the evolution of pit was studied by reproducible tests with different durations. The change of pits in size and quantity during corrosion process was supposed to account for different process of gas bubbling, which could again account for the different features of different stages. A good correlation between AE signals and pit quantity was observed. The results demonstrate the feasibility of employing AE signal of gas bubbling as an on-line monitoring tool for estimating non-intrusively the overall of the pitting corrosion process in stainless steel. Keywords Acoustic Emission, Stainless Steel, Pitting Corrosion, Gas Bubbling, Cumulative Counts s I. INTRODUCTION tainless steels have been finding extensive applications not only in industrial field but also in people s daily life due to its unsurpassed property of excellent resistance to corrosion. This very commonly used materials, however, can undergo localized pitting corrosion, which rapidly leads to final failure. This work was supported by the Technology Innovation Program (No , Development of rapid mold manufacturing technology for mass customized medical devices with SLS hybrid 3D printing technology) funded By the Ministry of Trade, industry & Energy(MI, Korea)" Kaige Wu is with the Department of Materials Science and Engineering, Seoul National University of Science and Technology, SOUTH KOREA, , SOUTH KOREA, ( kaigewu@seoultech.ac.kr) Seung-Mi Lee is with the Department of Graduate School of NID Fusion Technology, Seoul national university of science & technology, SOUTH KOREA, , Korea, ( smlee@seoultech.ac.kr). Won-Sik Lee is with the Advanced Process and Materials R&D Group Korea Institute of Industrial Technology, 7-47 Songdo-dong, Yeonsu-gu, Incheon, 46-84, SOUTH KOREA, ( wonslee@kitech.re.kr). Dong-Pyo Hong is with the Department of Mechanical Systems Engineering, Chonbuk National University, Chonju, , SOUTH KOREA, ( hongdp@jbnu.ac.kr). Jai-Won Byeon is with the Department of Materials Science and Engineering, Seoul National University of Science and Technology, Seoul, , SOUTH KOREA, (Corresponding author to provide phone: ; fax: ; byeonjw@seoultech.ac.kr). During all the electrochemical corrosion in laboratory research by AE technique, pitting corrosion of stainless steels has been of major concern for many years. Taking the AE signal analysis into consideration, Fregonese et al. [1-2] classified the signal into short signal and resonant signal, and the resonant signal was supposed to be associated with the evolution of H 2 bubbles within the occluded pits. Similar features were also shown by Jian Xu et al. [6], but their main disputation is when classifying the AE signals, the record length of signal was largely shorter than the duration time, which thus possibly make the classify method to be distrusted. Jirarungsatian and Prateepasen [5] used the duration to discriminate the breakdown of passive films and pit growth during pitting corrosion, but the AE waveform analysis was not studied though they proposed the 65us of duration to differentiate the two process. Taking the AE source analysis into consideration, hydrogen bubble evolution has been regarded as the most emissive source during electrochemical corrosion processes by many authors [1-7], and they suggested that hydrogen bubbles were generated inside the occluded pits as the AE source. Fregonese et al. [1] established that the hydrolysis of the resulting corrosion products leads to acidification within the pits and then to hydrogen evolution based on theoretical analysis. In this study, Acoustic emission (AE) technique was proposed to In-situ evaluate the pitting corrosion of 34 stainless steel. II. EXPERIMENTAL METHOD A. Material and Specimen Preparation Table 2.1 Compositions of 34 SS investigated in the present study, wt%. Commercial 34 stainless steel, which composition is given in Table 2.1, was used for this work. The specimens were cut from a 2 mm thick 34 stainless steel plate into a shape size of 75mm*15mm. They were wet ground up to No. 15 sand paper, followed by polishing from 6µm to 1µm by diamond gel. Subsequently the specimens received a passivation treatment of 3min in 2% HNO 3 at 6, after which they were rinsed with de-ionized water then acetone and dried in a stream of cool air. ISBN:

2 The exposed surface equal to 1*1 cm 2 controlled by mounting with fast curing epoxy (Araldite Rapid, Huntsman Advanced Materials (Switzerland) GmbH.) as shown in Fig USA). The AE signals were collected in one acquisition device (PCI 2 from PAC. USA). The threshold was set at 22dB and pre-amplifier was set at 4dB, respectively. Fig. 2.1 A schematically view of specimen geometry. III. RESULTS AND DISCUSSIONS A. Polarization curve Fig. 2.3 shows the anodic potentiodynamic polarization curve of stainless steel in 3% NaCl solution which was acidified to ph 2 by addition of HCl. In the polarization curve, when the applied potential is relatively lower than pit potential, the current density changes hardly and keeps at a relatively low level, which exhibited a range of passivity. Whereas as applied potential surpassed critical pitting potential, current density appeared to increase sharply with potential increasing. It is from this point, that metal passive film was ruptured and pits began to form on the surface of specimen. B. Morphology of specimen Fig. 2.4 shows the integrated morphologies of the specimen before and after anodic polarization process of 34 stainless steel in experimental solution, respectively. It clearly indicates that the occurrence of severe pitting corrosion on the surface of specimen after the applied polarization testing. Fig A schematically view of experimental apparatus: Hydrogen bubble detected three-electrode system. E ref. (V) Anodic polarization curve of SS34 E p B. Electrochemical Setup for Pitting Corrosion Control The pitting corrosion process was controlled with apply of anodic polarization by potentiodynamic method which was carried out in a typical three-electrode electrochemical cell: A Platinum wire counter electrode (CH115, CH Instruments Inc. USA) and a reference electrode of saturated Ag/AgCl/NaCl (3M) electrode (SSE) (RE-5B, Bioanalytical Systems Inc. USA) were employed, and the specimen as the working electrode. The corrosion test was implemented in 3% sodium chloride solution acidified to an initial ph of 2 controlled by HCl, which was prepared from de-ionized water, extra pure grade NaCl (Duksan Pure Chemicals, Korea) and extra pure grade HCl (Duksan Pure Chemicals, Korea). The specimens were anodically polarized at room temperature from open circuit potential (OCP) with a scan rate of.4mv/s after immersion in the test solution for 2 minutes. C. Acoustic Emission Measurement As shown in Fig. 2.2, in attempting to study the AE behavior of hydrogen bubbling in corrosion process, experimental setup was designed as gas-detected system with R15 sensor (PAC, USA) employed. The R15 type sensor was mounted by ultrasonic couplant to the specimen. The other end of R15 sensor was connected to AE system via a preamplifier (PAC..2. Fig. 2.3 Anodic potentiodynamic polarization curve of 34 stainless steel in 3% NaCl solution, ph=2 controlled by addition of HCl. C. AE activity I (A/cm 2 ) Fig. 2.4 shows the integrated morphologies of the specimen Fig. 2.4 The morphology of the specimen before (a) and after (b) pitting corrosion of 34 stainless steel in 3% NaCl solution, ph=2. ISBN:

3 before and after anodic polarization process of 34 stainless steel in experimental solution, respectively. It clearly indicates that the occurrence of severe pitting corrosion on the surface of specimen after the applied polarization testing. Fig. 2.5 shows the AE signals of cumulative counts detected during pitting corrosion of stainless steel 34 in gas bubbling detected system during anodic polarization process. AE signals were not detected immediately after applied potential surpassed the pit potential. When applied potential and current density reached a certain value which is higher than pitting potential, the AE signals started to be active. This short time lagging was reported as the phenomenon of time delay by many researchers [4-6, 9]. ]. However, it should be noted that they found the phenomenon of time delay in gas-undetected system, in which the gas bubbling was supposed to be noise and was eliminated always via a salt bridge. current density in this period also increased more sharply than previous stage. D. AE parameters Amplitude (db) Duration ( s) Fig. 2.6 The cross-plot of amplitude and duration of the AE signals detected during anodic polarization process of 34 stainless steel in solution of 3% NaCl, ph=2. Fig. 2.6 shows the cross-plot of amplitude and duration of the AE signals detected during the testing. It clearly indicates a distribution feature of amplitude versus duration cluster in one region of between 22dB and 48dB. E. AE waveforms and Hydrogen bubble evolution on the electrode..5 Time (ms) Fig. 2.5 AE signals of cumulative counts detected during pitting corrosion of stainless steel 34 in gas bubbling detected system during anodic polarization process in solution of 3% NaCl, ph=2. In the gas-detected system, the occurrence of time delay is observed for the first time. The important critical value like potential and time corresponding to the evolution of pit and related AE signals are given in Table 2.2. (a) (b) Magnitude Peak-FRQ 129kHz Frequency (khz) Voltage (mv) Table 2.2 Summary of important critical values corresponding to the evolution of pitting and related AE signals in Fig. 2.3 and Fig It is worth noting that the AE signal in time domain could be divided into three stages with taking the delay time into consideration. In stage I, which is the period of delay time, the signal is zero. In stage II, the AE signal was detected after the delay time. The AE signal of cumulative counts number exhibited as rather low increasing rate, as well as the current density. Subsequently in stage III, the AE signal increased sharply with a higher increasing rate comparing to stage II. The Fig. 2.7 (a) AE waveforms and corresponding FFT results (b) Morphology of bubble evolution on the surface of counter electrode. Fig. 2.7 (a) shows the typical waveforms and their corresponding Fast Fourier Transform (FFT) analysis results of AE signals in stage II. It clearly indicates that AE signals are ISBN:

4 characterized by a frequency content between about 9kHz and 2kHz and peak frequency around 125kHz. In other hands, the duration of AE signals in this stage is less than 3μs. Fig. 2.7 (b) shows bubble evolution on the surface of counter electrode. Note the size of breaking bubble in this stage was around.8mm. Percentage Rate (%) Percentage rate (%) Peak Frequency (khz) (a): Stage II: total 1351 hits Fig. 2.8 Spectral analysis of AE activity (a) in stage II and (b) in stage III. Fig. 2.8 (a) and (b) shows the spectral analysis of AE activity of stage II and stage III, respectively. The results of the analysis suggested that the frequency contents of stage II and stage III both cluster mainly in the range of 11 khz and 175 khz, reaching a ratio of 92.81% in stage II and 98.95% in stage III, respectively. Especially the range of 126 khz and 15 khz dominates distinctly as 73.87% in stage II and 83.56% in stage III, respectively. Pit Number (N) (b): Stage III: total hits Peak-Frequency (khz) Pit Number Linear fit of pit number I (A/cm 2 ) Fig. 2.9 Correlation between total pits number generated and applied anodic current density during pitting corrosion of stainless steel 34 in 3% NaCl solution, ph=2. Pit number (N) Pit number Linear fit of pit number 1x1 6 2x1 6 3x1 6 4x1 6 Cumulative AE counts (N) Fig. 2.1 Correlation between total pits number generated and AE signal of cumulative counts during pitting corrosion of stainless steel 34 in 3% NaCl solution, ph=2. Fig. 2.9 shows a correlation between total pits number generated and anodic current density during the experiment process. Fig. 2.1 shows a similar correlation between total pits number generated and the AE signal of cumulative counts. The good agreement between the two curves indicates that increasing both in size and quantity of pits can be corresponding to increase of corrosion amount, thus leading to the increasing trend of AE signals. This phenomenon is surprisingly observed for the first time in our gas-detected system, though a similar occurrence of time delay has been reported previously in gas-undetected system by many researchers [1-2, 6]. Fregonese et al. [1, 2] reported the ime delay above 1 seconds up to 35 seconds around. J. Xu et al. [6] also shown the time delay about a few hundred seconds. Apparently, the length of time delay in our study is far shorter than previous report results, proving our AE signal in early stage is the result of gas bubbling other than other physical sources. After considerable time corresponding to the time delay in gas-undetected system, the AE signal in our gas-detected system has presented to be huge comparing to that of pitting corrosion itself in gas-undetected system. Their effect on trend of AE signal of gas bubbling could be ignored. This proves again that AE signals in present gas-detected experiment setup could be supposed to be the result of hydrogen gas bubbling generated on counter electrode. The distribution feature of amplitude versus duration almost in one clustering (Fig. 2.8) could speak for this point to some extent. Taking the period of time delay phenomenon into consideration, the AE signal of gas bubbling could be divided into three stages based on different features, as shown in Table 2.2. In order to interpret the evolution of AE signal and hydrogen gas bubbling, the relationship of AE and bubbles needs to discuss firstly. The acoustic energy of bubble oscillation and bubble break-up was firstly studied by Minneart [7], and then investigated and demonstrated by Strasberg [8], Leighton [9, 1] and Lec.et al. [11]. In stage I, of which gas bubbling is shown in Fig. 2.7b, after ISBN:

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