Detection of corrosion on 304 stainless steel by acoustic emission measurement

2010 ◽  
Vol 57 (3) ◽  
pp. 126-132 ◽  
Author(s):  
Gang Du ◽  
Weikui Wang ◽  
Shizhe Song ◽  
Shijiu Jin
Keyword(s):  
Stainless Steel ◽  
Acoustic Emission ◽  
Constant Load ◽  
Corrosion Process ◽  
304 Stainless Steel ◽  
Emission Measurement ◽  
Nacl Solution ◽  
Content Type ◽  
Ae Signal ◽  
Ae Signals

PurposeThe purpose of this paper is to report an investigation of the acoustic emission (AE) characteristics of the corrosion process of 304 stainless steel in acidic NaCl solution.Design/methodology/approachThe corrosion behavior of a specimen with constant load in acidic NaCl solution was studied, and the AE signal characteristics of the corrosion process were analyzed. Stress corrosion cracking of the specimen was detected using the AE and electrochemical noise (EN) techniques, and the acquired data were compared.FindingsThe results indicated that AE technology is very sensitive to the AE signals generated by 304 nitrogen controlled stainless steel in acidic NaCl solution. The characteristics of AE signals at different stages of the corrosion process are significantly different. Additionally, the AE test result is confirmed by the EN test results.Originality/valueThe characteristics of AE signals at different stages of the corrosion process are gained for the first time, which is an important guide by which to distinguishing different stages of corrosion.

scholarly journals Analysis of Acoustic Emission (AE) Signals for Quality Monitoring of Laser Lap Microwelding

2021 ◽  
Vol 11 (15) ◽  
pp. 7045
Author(s):  
Ming-Chyuan Lu ◽  
Shean-Juinn Chiou ◽  
Bo-Si Kuo ◽  
Ming-Zong Chen
Keyword(s):  
Stainless Steel ◽  
Acoustic Emission ◽  
Frequency Domain ◽  
Monitoring System ◽  
Welding Quality ◽  
Steel Sheets ◽  
Signal Features ◽  
Ae Signal ◽  
Laser Microwelding ◽  
Ae Signals

In this study, the correlation between welding quality and features of acoustic emission (AE) signals collected during laser microwelding of stainless-steel sheets was analyzed. The performance of selected AE features for detecting low joint bonding strength was tested using a developed monitoring system. To obtain the AE signal for analysis and develop the monitoring system, lap welding experiments were conducted on a laser microwelding platform with an attached AE sensor. A gap between the two layers of stainless-steel sheets was simulated using clamp force, a pressing bar, and a thin piece of paper. After the collection of raw signals from the AE sensor, the correlations of welding quality with the time and frequency domain features of the AE signals were analyzed by segmenting the signals into ten 1 ms intervals. After selection of appropriate AE signal features based on a scatter index, a hidden Markov model (HMM) classifier was employed to evaluate the performance of the selected features. Three AE signal features, namely the root mean square (RMS) of the AE signal, gradient of the first 1 ms of AE signals, and 300 kHz frequency feature, were closely related to the quality variation caused by the gap between the two layers of stainless-steel sheets. Classification accuracy of 100% was obtained using the HMM classifier with the gradient of the signal from the first 1 ms interval and with the combination of the 300 kHz frequency domain signal and the RMS of the signal from the first 1 ms interval.

Reciprocating compressor valve damage estimation under varying speeds through the acoustic emission technique

2019 ◽  
Vol 10 (5) ◽  
pp. 621-633
Author(s):  
Hoi-Yin Sim ◽  
Rahizar Ramli ◽  
Ahmad Saifizul
Keyword(s):  
Acoustic Emission ◽  
Regression Analysis ◽  
Flow Rate ◽  
Reciprocating Compressor ◽  
Damage Estimation ◽  
Content Type ◽  
Air Compressor ◽  
Ae Signal ◽  
Valve Opening ◽  
Ae Signals

Purpose The purpose of this paper is to examine the effect of reciprocating compressor speeds and valve conditions on the roor-mean-square (RMS) value of burst acoustic emission (AE) signals associated with the physical motion of valves. The study attempts to explore the potential of AE signal in the estimation of valve damage under varying compressor speeds. Design/methodology/approach This study involves the acquisition of AE signal, valve flow rate, pressure and temperature at the suction valve of an air compressor with speed varrying from 450 to 800 rpm. The AE signals correspond to one compressor cycle obtained from two simulated valve damage conditions, namely, the single leak and double leak conditions are compared to those of the normal valve plate. To examine the effects of valve conditions and speeds on AE RMS values, two-way analysis of variance (ANOVA) is conducted. Finally, regression analysis is performed to investigate the relationship of AE RMS with the speed and valve flow rate for different valve conditions. Findings The results showed that AE RMS values computed from suction valve opening (SVO), suction valve closing (SVC) and discharge valve opening (DVO) events are significantly affected by both valve conditions and speeds. The AE RMS value computed from SVO event showed high linear correlation with speed compared to SVC and DVO events for all valve damage conditions. As this study is conducted at a compressor running at freeload, increasing speed of compressor also results in the increment of flow rate. Thus, the valve flow rate can also be empirically derived from the AE RMS value through the regression method, enabling a better estimation of valve damages. Research limitations/implications The experimental test rig of this study is confined to a small pressure ratio range of 1.38–2.03 (free-loading condition). Besides, the air compressor is assumed to be operated at a constant speed. Originality/value This study employed the statistical methods namely the ANOVA and regression analysis for valve damage estimation at varying compressor speeds. It can enable a plant personnel to make a better prediction on the loss of compressor efficiency and help them to justify the time for valve replacement in future.

Research on Acoustic Emission Signals Characteristics of Pitting Corrosion on 304 Stainless Steel

2013 ◽  
Author(s):  
Zhongzheng Zhang ◽  
Hua Liang ◽  
Cheng Ye ◽  
Wensheng Cai ◽  
Jun Jiang ◽  
...  
Keyword(s):  
Stainless Steel ◽  
Acoustic Emission ◽  
Pitting Corrosion ◽  
High Frequency ◽  
Low Frequency ◽  
Ferric Chloride Solution ◽  
304 Stainless Steel ◽  
Flexural Wave ◽  
Higher Temperature ◽  
Ae Signals

In order to study acoustic emission (AE) signals waveform characteristics of pitting corrosion on 304 stainless steel under higher temperature than lower one, Pitting corrosion process on 304 stainless steel in 6% ferric chloride solution at 70°C was monitored by AE technology. Wavelet transform and mode acoustic emission technology were combined to deal with recorded AE signals, and micromorphologic observation was performed for further verification. The results showed that signal waveform was mainly composed of low-frequency (<100KHz) flexural wave with larger amplitude & energy and high-frequency (>100KHz) expansion wave with lesser amplitude & energy. The research results have some certain significance for AE monitoring of pitting corrosion on 304 stainless steel.

Determining the feasibility of identifying creep rupture of stainless steel cladding tubes on-line using acoustic emission technique

2015 ◽  
Vol 6 (3) ◽  
pp. 410-418
Author(s):  
N Mahendra Prabhu ◽  
K.A. Gopal ◽  
S. Murugan ◽  
T.K. Haneef ◽  
C. K. Mukhopadhyay ◽  
...  
Keyword(s):  
Stainless Steel ◽  
Acoustic Emission ◽  
Creep Rupture ◽  
Acoustic Emission Technique ◽  
Content Type ◽  
Fuel Pin ◽  
On Line ◽  
Clad Tube ◽  
Non Destructive ◽  
Ae Signals

Purpose – The purpose of this paper is to determine the feasibility of identifying the creep rupture of reactor cladding tubes using acoustic emission technique (AET). Design/methodology/approach – The creep rupture tests were carried out by pressuring stainless steel capsules upto 6 MPa at room temperature and then heating continuously in a furnace upto rupture. The acoustic emission (AE) signals generated during the creep rupture tests were recorded using a 150 kHz resonant sensor and analysed using AE Win software. Findings – When rupture occurs in the pressurized capsule tube representing the cladding tube, AE sensor attached to a waveguide captures the mechanical disturbance from the capsule and these data can be advantageously used to identify the creep rupture event of the cladding tube. Practical implications – The creep rupture data of fuel clad tube is very important in design and for smooth operation of nuclear reactors without fuel pin failure in reactors. Originality/value – AE is an advanced non-destructive evaluation technique. This technique has been successfully applied for on-line monitoring of creep rupture of the reactor cladding tube which otherwise could be detected by thermocouple readings only.

Experiment on Surface Roughness and Acoustic Emission Signal in Infeed Period of Cylindrical Plunge Grinding

2013 ◽  
Vol 690-693 ◽  
pp. 2442-2445 ◽  
Author(s):  
Hao Lin Li ◽  
Hao Yang Cao ◽  
Chen Jiang
Keyword(s):  
Surface Roughness ◽  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Feed Rate ◽  
Grinding Process ◽  
Experiment Research ◽  
Plunge Grinding ◽  
Emission Signal ◽  
Ae Signal ◽  
Ae Signals

This work presents an experiment research on Acoustic emission (AE) signal and the surface roughness of cylindrical plunge grinding with the different infeed time. The changed infeed time of grinding process is researched as an important parameter to compare AE signals and surface roughnesses with the different infeed time in the grinding process. The experiment results show the AE signal is increased by the increased feed rate. In the infeed period of the grinding process, the surface roughness is increased at first, and then is decreased.

scholarly journals Acoustic emission characteristics of stress corrosion cracks in a type 304 stainless steel tube

2015 ◽  
Vol 47 (4) ◽  
pp. 454-460 ◽  
Author(s):  
Woonggi Hwang ◽  
Seunggi Bae ◽  
Jaeseong Kim ◽  
Sungsik Kang ◽  
Nogwon Kwag ◽  
...  
Keyword(s):  
Stainless Steel ◽  
Acoustic Emission ◽  
Stress Corrosion ◽  
Steel Tube ◽  
304 Stainless Steel ◽  
Stainless Steel Tube ◽  
Emission Characteristics ◽  
Type 304 ◽  
Type 304 Stainless Steel
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