Acoustic Emission From Simple Upsetting of Solid Cylinders

1982 ◽  
Vol 104 (2) ◽  
pp. 145-152 ◽  
Author(s):  
David A. Dornfeld ◽  
Edward Diei
Keyword(s):  
Plastic Deformation ◽  
Acoustic Emission ◽  
Count Rate ◽  
Effective Strain ◽  
Signal Amplitude ◽  
Amplitude Distribution ◽  
Degree Of Deformation ◽  
Surface Cracking ◽  
Cumulative Count ◽  
Ae Signals

Acoustic emission (AE) generated during simple upsetting (forging) of solid cylinders contains information that could potentially be used to separate the upsetting process into a range of zones of plastic deformation and a zone of both plastic deformation and cracking. This investigation monitored the AE signals during the upsetting of cylindrical specimens of 7075-T6 Aluminum from the start of plastic deformation through eventual cracking. The count rate (N˙) and cumulative count (N) as a function of effective strain were determined. The count rate data are characterized by three distinct regions, an initial peak during yielding of the material, a period of gradual increase during the progression of plastic deformation and the accompanying changes in specimen geometry, and finally a region of rapid increase in N˙ as cracking begins. The cumulative count and rms data follow similar patterns. An analysis of the amplitude distribution of the cumulative count data over a range of strain was made, and in the region of higher amplitude emissions, changes in the distribution of up to two orders of magnitude are observed for data obtained during plastic deformation and surface cracking compared to that from the region of pure deformation only. If plotted as log count (N) versus signal amplitude, the resulting data can be fit with a line using least squares methods yielding a power law relationship sensitive to the degree of deformation.

scholarly journals Acoustic Emission and Damage Characteristics of Granite Subjected to High Temperature

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
X. L. Xu ◽  
Z.-Z. Zhang
Keyword(s):  
Acoustic Emission ◽  
High Temperatures ◽  
Count Rate ◽  
Shear Failure ◽  
Rock Fracture ◽  
Mechanical Damage ◽  
Strain Curve ◽  
Effect Of Temperature ◽  
Compression Tests ◽  
Ae Signals

Acoustic emission (AE) signals can be detected from rocks under the effect of temperature and loading, which can be used to reflect rock damage evolution process and predict rock fracture. In this paper, uniaxial compression tests of granite at high temperatures from 25°C to 1000°C were carried out, and AE signals were monitored simultaneously. The results indicated that AE ring count rate shows the law of “interval burst” and “relatively calm,” which can be explained from the energy point of view. From 25°C to 1000°C, the rock failure mode changes from single splitting failure to multisplitting failure, and then to incomplete shear failure, ideal shear failure, and double shear failure, until complete integral failure. Thermal damage (DT) defined by the elastic modulus shows logistic increase with the rise of temperature. Mechanical damage (DM) derived by the AE ring count rate can be divided into initial stage, stable stage, accelerated stage, and destructive stage. Total damage (D) increases with the rise of strain, which is corresponding to the stress-strain curve at various temperatures. Using AE data, we can further analyze the mechanism of deformation and fracture of rock, which helps to gather useful data for predicting rock stability at high temperatures.

Acoustic Emission Diagnostics of the Destruction of Welded Joints Stainless Steel Pipes Arising Welding

2015 ◽  
Vol 770 ◽  
pp. 60-65
Author(s):  
A.M. Apasov
Keyword(s):  
Stainless Steel ◽  
Acoustic Emission ◽  
Structural Analysis ◽  
Welded Joints ◽  
Crack Nucleation ◽  
Amplitude Distribution ◽  
Steel Pipes ◽  
Weld Root ◽  
Ae Signals ◽  
Insight Into

It is now possible to formulate the relation of the linear size of cracking arising on welding the cylindrical homogeneous-metal. Mathematical simulation of metal crystallization on welding and micro structural analysis give an insight into the fact that there begins crack nucleation in a weld root. Experimentally, by means of Acoustic Emission (AE), one can study welding and obtain the amplitude distribution of AE signals from cracking against the background of the hindrance accompanying this process. The conditions were found making impossible cracking.

Acoustic Emission Test on Steel/Composite and Steel/Composite/Steel Built-Up Sections

2011 ◽  
Author(s):  
Rushie Ghimire ◽  
Gary Anderson ◽  
Fereidoon Delfanian
Keyword(s):  
Acoustic Emission ◽  
Tensile Tests ◽  
Glue Line ◽  
Stress And Strain ◽  
Steel Component ◽  
Cumulative Count ◽  
Steel Composite ◽  
Acoustic Emission Test ◽  
Ae Signals ◽  
Composite Steel

Acoustic Emission (AE) has been widely used to monitor and inspect built-up steel/composite sections; primarily at the glue line. AE testing was conducted on steel-composite (SC) and steel-composite-steel (SCS) built-up sections to determine the glue line failure and damage sustained by the inner layer of the built-up section by putting the sensors on the inner and outer layers of the built-up sections. The straight specimens of steel/composite and steel/composite/steel were tested with load applied to only one steel layer. The AE sensors were placed on the outer steel component so that detected signals traveled through the loaded steel, glue lines, and the composite or the loaded steel component, two glue lines, composite and unloaded steel components of the built-up section(s). The AE signals received by the sensors placed on the loaded steel in tension was compared to signals of sensors placed directly opposite on the unloaded steel or composite to determine the effect the steel/composite and steel/composite/steel built-up sections had on the signal. AE signals were also compared to signals generated during tensile tests of steel specimens only and composite specimens only. AE parameters like amplitude, hits, counts, frequency, cumulative count, and rise time of the AE signals were recorded, analyzed, and compared. AE parameters were also compared to traditional material properties (like yield and failure stress and strain). Tested specimens were examined with a microscope and observations were compared and analyzed relative to AE and material parameters, and reported.

METHOD OF REJECTION OF DEFECTS IN CARBON FIBER SAMPLES BY PARAMETERS OF ACOUSTIC EMISSION SIGNALS UNDER STATIC AND THERMAL LOADING

2020 ◽  
pp. 4-13
Keyword(s):  
Acoustic Emission ◽  
Carbon Fiber ◽  
Thermal Loading ◽  
Tensile Load ◽  
Signal Amplitude ◽  
Informative Parameters ◽  
Complete Destruction ◽  
Static Tensile ◽  
Ae Signals ◽  
Structural Coefficient

A method for rejecting defects in T 800 carbon fiber samples loaded with a static tensile load at an interval of ΔP = 10 kN until complete destruction is proposed. One part of the samples was loaded at a temperature of 20 °C, and the other part was subjected to simultaneous static loading and heating to a temperature of 100 °C. Samples made of carbon fiber with a size of 600×100×0.9 mm were made using autoclave and vacuum technologies at temperatures of 80; 135; 180 °C. the process of destruction of samples was controlled by acoustic emission (AE). To perform defect rejection, informative parameters of AE signals (structural coefficient and median signal amplitude) were used. The critical damage associated with the breaking of the fibers in the composite corresponded to AE signals with a structural coefficient less than a threshold and a median of amplitudes greater than a threshold.

scholarly journals Amplitude Distribution of Acoustic Emission Signals in Plastic Deformation

1977 ◽  
Vol 41 (9) ◽  
pp. 897-904 ◽  
Author(s):  
Teruo Kishi ◽  
Akira Katoh ◽  
Kazuhiko Kuribayashi ◽  
Ryo Horiuchi
Keyword(s):  
Plastic Deformation ◽  
Acoustic Emission ◽  
Amplitude Distribution

Investigation of the Stages of Damage Accumulation in Polymer Composite Materials

2019 ◽  
Vol 945 ◽  
pp. 515-521 ◽  
Author(s):  
O.V. Bashkov ◽  
A.A. Bryansky ◽  
I.V. Belova ◽  
Denis B. Solovev
Keyword(s):  
Acoustic Emission ◽  
Power Law ◽  
Experimental Studies ◽  
Amplitude Distribution ◽  
B Value ◽  
Bending Test ◽  
Emission Data ◽  
Three Point Bending ◽  
Destructive Processes ◽  
Ae Signals

This paper presents the results of the study of strength and fracture processes of FRP samples, obtained by vacuum and vacuum-autoclave molding methods. The experimental studies consisted of a three-point bending test with step loading, accompanied by an acoustic emission method. Based on the acoustic emission data recorded using the acoustic-emission software and hardware complex during the experiments, a method for estimating the accumulated damage using various techniques for analyzing acoustic emission parameters was tested. The results of methods for analyzing the power-law coefficient of accumulation of total AE, b-value and density distribution of amplitudes and median frequencies are considered. An estimate of the power-law coefficient of accumulation of the total AE made it possible to determine the bearing capacity of PCM samples. Using the techniques for analyzing the amplitude distribution of the AE signals and the distribution density of the amplitudes and median frequencies of the AE signals, destructive processes in the volume of samples were described and the stages of their damaging were revealed.

scholarly journals Prediction of the Stability of the Loaded Rock Based on the Acoustic Emission Characteristics of the Loaded Rock Based on Data Mining

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Mengyao Li ◽  
Chang Su ◽  
Guolong Li
Keyword(s):  
Data Mining ◽  
Plastic Deformation ◽  
Acoustic Emission ◽  
Rock Mass ◽  
Early Warning ◽  
Ae Energy ◽  
Signal Characteristics ◽  
Ae Signal ◽  
Cumulative Count ◽  
Loaded Rock

The rock masses that occur in nature are damaged and unstable due to the impact of rock burst, coal and gas outbursts, and other human mining activities, posing a major threat to human life and safety. In the light of the early warning of the danger of the loaded rock mass, this paper adopts acoustic emission (AE) device to analyze the AE signal characteristics and damage laws of the loaded rock under different stress levels. Then, based on the AE signal characteristics of the loaded rock, data mining technology is used to construct a model to predict the failure and instability of the loaded rock mass and, finally, verify the reliability of the prediction model based on data mining. The results show that the AE signal characteristics of red sandstone under uniaxial load are related to the magnitude of the bearing stress. Before the plastic deformation stage, the AE energy and the cumulative count per second are both small. After the loaded rock enters the plastic deformation stage, the AE energy and the cumulative count per second both increase sharply. After the AE energy is greater than 500 mV ∗ ms and the cumulative count per second is greater than 150, the loaded rock mass will issue an early warning signal. The research results can provide a reference value for the safe production of the project site and the dangerous early warning of the loaded rock mass.

Acoustic Emission during Isothermal Oxidation of 2.25Cr-1Mo Steel

2009 ◽  
Vol 294 ◽  
pp. 93-104
Author(s):  
B.B. Jha ◽  
Barada Kanta Mishra ◽  
S.N. Ojha
Keyword(s):  
Acoustic Emission ◽  
Energy Release ◽  
Oxidation Rate ◽  
Amplitude Distribution ◽  
Isothermal Oxidation ◽  
Rate Variation ◽  
Mean Square ◽  
The Difference ◽  
Event Rates ◽  
Ae Signals

Acoustic emission (AE) signals, obtained during the isothermal oxidation of 2.25Cr-1Mo steel at 773 K, 873 K, 973 K and 1073 K, have been analyzed. The results indicated that the rate of occurrence of AE events and consequently the total number of AE events generated during isothermal oxidation at these temperatures increased with an increase in the oxidation rate. Variation in the temperature of oxidation did not show any variation in the root mean square (RMS) level of the AE signals. The b-parameters obtained from a logarithmic cumulative amplitude distribution plot indicated that the strength of the AE signals did not change during isothermal oxidation carried out at these temperatures. Different event rates, and consequently the difference in the total number of AE events generated during isothermal oxidation at these temperatures, are indicative of the increased rate of energy release associated with the growth of oxide layers formed at higher temperatures. The rate of energy release has been found to be higher for higher temperatures of oxidation.

Evaluation of the mechanical properties of Inconel 718 to SCM 440 dissimilar friction welding through real-time monitoring of the acoustic emission system

2021 ◽  
pp. 146442072199383
Author(s):  
Yu Sik Kong ◽  
Muralimohan Cheepu ◽  
Jin-Kyung Lee
Keyword(s):  
Acoustic Emission ◽  
Friction Welding ◽  
Inconel 718 ◽  
Low Voltage ◽  
Dissimilar Materials ◽  
Average Frequency ◽  
Very High Frequency ◽  
Cumulative Count ◽  
Emission System ◽  
Very High

Friction welding was chosen for its versatility in the joining of dissimilar materials with high quality. The aim of this study is to determine the optimal welding conditions for attaining quality joints by using online monitoring of acoustic emission system signals. During friction welding, the formation of cracks, defects, or any abnormalities in the joining process which have a detrimental effect on the joints quality was identified. The most widely used materials in the aerospace industry—Inconel 718 and molybdenum steel—were joined by friction welding. The precision of the joints, internal defects, and quality are major concerns for aerospace parts. The results of the present research determined the optimal welding conditions for high tensile strength by nondestructively inducing acoustic emission signals. During friction time and upset time periods, the typical waveforms and frequency spectrum of the acoustic emission signals were recorded, and their energy level, average frequency, cumulative count, and amplitude were analyzed. Both cumulative count and amplitude were found to be useful parameters for deriving the optimal welding conditions. In the initial stage of friction welding, a very high voltage of continuous form was generated with frequency characteristics of 0.44 MHz and 0.54 MHz. The signals generated during the upset stage had a low voltage, but a very high frequency of 1.56 MHz and 1.74 MHz with a burst-type signal. The amplitude of the signal generated for the optimally welded joints was about 100 dB at the friction time and about 45 dB at the upset time.

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.

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