Punch Press Monitoring with Acoustic Emission (AE) Part I: Signal Characterization and Stock Hardness Effects

1983 ◽  
Vol 105 (4) ◽  
pp. 295-300 ◽  
Author(s):  
B. S. Kim
Keyword(s):  
Acoustic Emission ◽  
Shear Fracture ◽  
Signal Amplitude ◽  
Relative Timing ◽  
Component Identification ◽  
Ae Signal ◽  
Signal Characterization ◽  
Ae Counts ◽  
Three Components ◽  
Punch Press

As an integral part of the punch press monitoring research program, the Acoustic Emission (AE) signal emitted from a Minster1 #3 punch press is completely characterized in terms of signal component identification, relative timing and signal amplitude of each component. The AE signal generated during punching is found to consist of three components: initial impact, shear fracture and rupture. Effects of stock hardness are then examined in terms of relative timing and amplitude of those three components. Good correlations are found between stock hardness and the corresponding AE signals (and thus AE counts).

Punch Press Monitoring with Acoustic Emission (AE) Part II: Effects of Process Variables

1983 ◽  
Vol 105 (4) ◽  
pp. 301-306 ◽  
Author(s):  
B. S. Kim
Keyword(s):  
Acoustic Emission ◽  
Tool Wear ◽  
Shear Fracture ◽  
Relative Timing ◽  
Process Variables ◽  
Excellent Correlation ◽  
Ae Signal ◽  
Ae Signals ◽  
Three Components ◽  
Punch Press

In a previous paper, the acoustic emission (AE) signal emitted from a Minster1 #3 punch press was completely characterized and effects of stock hardness were examined. The AE signal emitted during punching was found to consist of three components: initial impact, shear fracture and rupture. Effects of stock hardness on the AE signal were then examined in terms of relative timing and amplitude of these three components and an excellent correlation was found between AE count and stock hardness. As a continuation, effects of stock thickness, tool size and tool wear are examined in this report. Similar to the previous study, their effects are investigated qualitatively in terms of relative timing and amplitude of the AE component and quantitatively in terms of AE count. Again good correlations are found between these process variables and the AE signals.

Acoustic Emission Analysis of Nanoindentation-Induced Fracture Events

2004 ◽  
Vol 841 ◽  
Author(s):  
Pawel Dyjak ◽  
Raman P. Singh
Keyword(s):  
Acoustic Emission ◽  
Brittle Materials ◽  
Signal Amplitude ◽  
Crack Arrest ◽  
Quantitative Information ◽  
Local Failure ◽  
Emission Analysis ◽  
Specimen Holder ◽  
Cube Corner ◽  
Ae Signal

ABSTRACTMonitoring of acoustic emission (AE) activity was employed to characterize the initiation and progression of local failure processes during nanoindentation-induced fracture. Specimens of various brittle materials were loaded with a cube-corner indenter and AE activity was monitored during the entire loading and unloading event using an AE transducer mounted inside the specimen holder. As observed from the nanoindentation and AE response, there were fundamental differences in the fracture behavior of the various materials. Post-failure observations were used to identify particular features in the AE signal (amplitude, frequency, rise-time) that correspond to specific types of fracture events. Furthermore, analysis of the parametric and transient AE data was used to establish the crack-initiation threshold, crack-arrest threshold, and energy dissipation during failure. It was demonstrated that the monitoring of AE signals yields both qualitative and quantitative information regarding highly local failure events in brittle materials.

Acoustic Emission Monitoring During Rupture Test of Pressure Vessel and Laboratory Fracture Test

1981 ◽  
Vol 103 (2) ◽  
pp. 191-199 ◽  
Author(s):  
N. Ohtsuka ◽  
M. Nakano ◽  
H. Ueyama
Keyword(s):  
Acoustic Emission ◽  
Signal Amplitude ◽  
Fracture Test ◽  
Crack Tip Opening Displacement ◽  
Opening Displacement ◽  
Test Conditions ◽  
Significant Difference ◽  
Ae Signal ◽  
Loading Parameter ◽  
Crack Tip Opening

In order to relate the results of a field AE test on a large structure to observations made from small laboratory specimens, acoustic emission (AE) was monitored during a pressurization test on a model vessel containing several kinds of artificial defects and during laboratory tests on small specimens to simulate the defects. The active AE sources in the vessel were concentrated mainly around an artificial weld crack and a sawcut notch. The total number of AE events is compared with displacement, load, crack tip opening displacement, and AE signal amplitude under various test conditions on two types of defects. The significant difference in AE generating mechanism, size of defects, loading parameter and rate between the tests is discussed by the fracture mechanics approach.

Comparative Study of Acoustic Emission Characteristics for Intergranular Corrosion of 316L Stainless Steel Parent Material and Weldment

2014 ◽  
Author(s):  
Wenjie Bai ◽  
Mengyu Chai ◽  
Lichan Li ◽  
Quan Duan
Keyword(s):  
Stainless Steel ◽  
Acoustic Emission ◽  
Comparative Analysis ◽  
Intergranular Corrosion ◽  
316L Stainless Steel ◽  
Signal Amplitude ◽  
Parent Material ◽  
Ae Signal ◽  
Preliminary Corrosion ◽  
Spectrum Characteristics

The 316L stainless steel parent material and weldment specimens were made to carry out intergranular corrosion(IGC) test using the method of boiling nitric acid. During the corrosion experiment, the acoustic emission(AE) signals were collected. Through the comparative analysis of corrosion rate and metallographic structure, the results showed that the IGC of parent material and weldment can be divided into the preliminary corrosion stage and the rapid corrosion stage. The AE parameters and spectrum characteristics of the two corrosion stages of the parent material and weldment were analyzed. The results showed that: in preliminary and rapid corrosion stages, the AE signal amplitude and energy of weldment were higher than that of parent material; the spectrum characteristics of weldment was more abundant than that of parent material. Based on the results of the comparative analysis, the AE sources of parent material and weldment IGC and the possibilities of monitoring IGC using AE technique were analyzed.

Acoustic Emission From Single-Plate Martensitic Transformation

1991 ◽  
Vol 58 (4) ◽  
pp. 889-894 ◽  
Author(s):  
Xiangying Liu ◽  
Elijah Kannatey-Asibu
Keyword(s):  
Acoustic Emission ◽  
Martensitic Transformation ◽  
Growth Process ◽  
Martensite Plate ◽  
Signal Amplitude ◽  
Elastic Half Space ◽  
Plate Martensite ◽  
Single Plate ◽  
Plate Formation ◽  
Ae Signal

Martensitic transformation occurs in a diffusionless manner at high velocity, with acoustic emission (AE) being generated during the process. The AE signal contains information about the dynamic process of martensitic transformation. In this analysis, a model is developed for the AE signal, or dynamic displacement, from the transformation strains and the growth process of martensitic transformation in an elastic half-space using Green’s functions. The AE signal amplitude is found to be inversely proportional to the distance between the martensite source and the sensor, and to the duration of transformation. It also depends on the orientation of the martensite plate. The spectral bandwidth increases as the duration of plate formation decreases. In addition, raising the carbon content increases the fraction of plate martensite, and consequently the signal amplitude.

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.

scholarly journals The duration-energy-size enigma for acoustic emission

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Blai Casals ◽  
Karin A. Dahmen ◽  
Boyuan Gou ◽  
Spencer Rooke ◽  
Ekhard K. H. Salje
Keyword(s):  
Acoustic Emission ◽  
Mean Field Theory ◽  
Mean Field ◽  
Maximum Amplitude ◽  
Time Profile ◽  
Power Law Distribution ◽  
Model Predictions ◽  
Ae Signal ◽  
Strain Signal ◽  
Better Than

AbstractAcoustic emission (AE) measurements of avalanches in different systems, such as domain movements in ferroics or the collapse of voids in porous materials, cannot be compared with model predictions without a detailed analysis of the AE process. In particular, most AE experiments scale the avalanche energy E, maximum amplitude Amax and duration D as E ~ Amaxx and Amax ~ Dχ with x = 2 and a poorly defined power law distribution for the duration. In contrast, simple mean field theory (MFT) predicts that x = 3 and χ = 2. The disagreement is due to details of the AE measurements: the initial acoustic strain signal of an avalanche is modified by the propagation of the acoustic wave, which is then measured by the detector. We demonstrate, by simple model simulations, that typical avalanches follow the observed AE results with x = 2 and ‘half-moon’ shapes for the cross-correlation. Furthermore, the size S of an avalanche does not always scale as the square of the maximum AE avalanche amplitude Amax as predicted by MFT but scales linearly S ~ Amax. We propose that the AE rise time reflects the atomistic avalanche time profile better than the duration of the AE signal.

scholarly journals Bearing defect diagnosis and acoustic emission

2003 ◽  
Vol 217 (4) ◽  
pp. 257-272 ◽  
Author(s):  
A Morhain ◽  
D Mba
Keyword(s):  
Acoustic Emission ◽  
Threshold Level ◽  
Diagnostic Methods ◽  
Non Destructive Testing ◽  
Test Rig ◽  
Destructive Testing ◽  
High Background ◽  
Bearing Defect ◽  
Non Destructive ◽  
Ae Counts

Acoustic emission (AE) was originally developed for non-destructive testing of static structures, but over the years its application has been extended to health monitoring of rotating machines and bearings. It offers the advantage of earlier defect detection in comparison with vibration analysis. However, limitations in the successful application of the AE technique for monitoring bearings have been partly due to the difficulty in processing, interpreting and classifying the acquired data. The investigation reported in this paper was centred on the application of standard AE characteristic parameters on a radially loaded bearing. An experimental test rig was modified such that defects could be seeded onto the inner and outer races of a test bearing. As the test rig was adapted for this purpose, it offered high background acoustic emission noise providing a realistic test for fault diagnosis. In addition to a review of current diagnostic methods for applying AE to bearing diagnosis, the results of this investigation validated the use of r. m. s., amplitude, energy and AE counts for diagnosis. Furthermore, this study determined the most appropriate threshold level for AE count diagnosis, the first known attempt.

Study on Acoustic Emission of 1-3 Orthotropic Cement Based Piezoelectric Sensors

2012 ◽  
Vol 487 ◽  
pp. 471-475 ◽  
Author(s):  
Shi Hui Xie ◽  
Mi Mi Li ◽  
Mei Juan Zhou ◽  
Min Sun ◽  
Shi Feng Huang
Keyword(s):  
Acoustic Emission ◽  
Volume Fraction ◽  
Signal Strength ◽  
Signal Wave ◽  
Functional Material ◽  
Wave Shape ◽  
Sensing Element ◽  
Piezoelectric Composites ◽  
Ae Signal ◽  
Amplitude Decrease

1-3 orthotropic cement based piezoelectric composites were fabricated by cut-filling and arrange-filling technique, using PZT-51 ceramic as functional material and cement as passive matrix. 1-3 orthotropic cement based piezoelectric composites were prepared into Acoustic Emission (AE) sensors, the attenuation of AE signal on the concrete and the response of different sensors on the concrete with increasing distance were researched. The results showed that the signal strength received by sensing element increases with the increasing PZT volume fraction; signal peaks and amplitude decrease gradually when the testing distance increases; signal strength received on the ceramic title is stronger than on the concrete; the attenuation of signal wave shape received on the concrete is much slower when compared with ceramic title.

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.

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