Investigation of the Peculiarities of Deformation and Fracture of Metals Obtained on the Basis of 3D Printing with Registration of an Acoustic Emission Signal

2021 ◽  
Vol 1037 ◽  
pp. 71-76
Author(s):  
Maksim S. Anosov ◽  
Yury G. Kabaldin ◽  
Dmitrii A. Shatagin ◽  
Dmitry A. Ryabov ◽  
Pavel Kolchin
Keyword(s):  
Acoustic Emission ◽  
3D Printing ◽  
Test Temperature ◽  
Acoustic Emission Signal ◽  
Fracture Mechanisms ◽  
Characteristic Parameters ◽  
Diagnostic Features ◽  
Emission Signal ◽  
Deformation And Fracture ◽  
Ae Signal

The paper investigates the features of deformation and fracture of steels obtained using the technology of 3D printing by electric arc surfacing based on the registration of the acoustic emission signal. With a decrease in the test temperature of 07Cr25Ni13 steel, a decrease in the work expended in stretching the specimen is observed, both at the stage of elastic deformation and at the stage of strain hardening. It was found that the most informative characteristic parameters of the AE signal include: the pulse count rate N, the total count NΣ, and the AE signal entropy. With a decrease in the test temperature, there is a significant increase in the intensity of the AE signal, the total number of pulses at all stages of deformation and destruction of steel. The obtained regularities of changes in the characteristic parameters of the AE signal can be used as diagnostic features, both in assessing the stage of deformation and destruction of the material, and the structural state of the material. Fractographic studies have shown a significant decrease in the tough component of 08Mn2Si steel with a decrease in the test temperature. The fracture mechanisms of 07Cr25Ni13 steel change insignificantly with decreasing temperature, however, a significant decrease in the ductility of the metal is observed, as evidenced by a decrease in the size of ductile fracture cups.

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.

Health Index Evaluation on Acoustic Emission Signal for Concrete Structure by Intensity Analysis Method

2011 ◽  
Vol 403-408 ◽  
pp. 3729-3733 ◽  
Author(s):  
Shahidan Shahiron ◽  
Norazura Muhamad Bunnori ◽  
Md Noor Noorsuhada ◽  
Siti Ramziah Basri
Keyword(s):  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Concrete Structure ◽  
Concrete Structures ◽  
Signal Strength ◽  
Small Scale ◽  
Intensity Analysis ◽  
Reinforced Concrete Structure ◽  
Emission Signal ◽  
Ae Signal

Concrete structures have been facing several types of damage mechanisms during their lifetime. Mostly, the types are commonly defects in concretes structures are crack formations. Therefore, evaluation methods such as acoustic emission (AE) are required for assessing the deterioration on concrete structures. This paper gives a brief on the evaluations of the acoustic emission signal strength to the health monitoring of reinforced concrete structure beam. Small scale size beam have been used for this investigation and the AE signal processing are the main principal data in this work for assessing by using the statistical quantitative technique, which is known as intensity analysis (IA).This type of technique is able to quantify and evaluate the damage severity on concrete structures. Eventually, by using the AE signal strength data, the results indicates are greater instruments in determining the damage mechanism level on concretes structure.

Research on Gate Valve Internal Leakage Detection Based on Acoustic Emission Signal Processing

2014 ◽  
Vol 1037 ◽  
pp. 169-173 ◽  
Author(s):  
Liang Zhu ◽  
Bin Zou ◽  
Shao Hua Gao ◽  
Ming Jiang ◽  
Zhi Ping Li
Keyword(s):  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Gate Valve ◽  
Signal Acquisition ◽  
Production Environment ◽  
Emission Signal ◽  
Safety Production ◽  
On Line ◽  
Ae Signal ◽  
Adverse Influence

Gate valve is common equipment in the petrochemical industry. It often brings out internal leakage because of quality, operation, corrosion and other reasons, and has adverse influence on safety production, environment protection and energy conservation. This paper put forward the on-line detection method about the gate valve internal leakage detect problem on the basis of AE signal analysis. Firstly, introduced the structure of gate valve and main reasons of internal leakage, discovered the acoustic emission signal parameters of gate valve internal leakage, and derived the relation model between internal leakage and AE signal theoretically. Then, constructed internal leakage signal acquisition platform based on DN80 gate valve internal leakage simulation system. Finally, put forward gate valve gas internal leakage test, set the different pressure at different points on the conditions of different pressure valve of 0.2MPa, 0.4MPa and 0.6MPa, The experiment showed that gate valve internal leakage status can be displayed by the signal RMS value when the gate valve internal leakage AE signal is between 30kHz and 80kHz. The AE signal next to the gate valve downstream position is the strongest. Internal leakage of the valve exists if downstream signal was significantly greater than the upstream signal or the background noise. The AE signal strengthened while the pressure difference between upstream and downstream is increased.

Research of the cold resistance of metals by indentation with registration of an acoustic emission signal

2020 ◽  
pp. 61-64
Author(s):  
Yu.G. Kabaldin ◽  
A.A. Khlybov ◽  
M.S. Anosov ◽  
D.A. Shatagin
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Low Temperatures ◽  
Cold Resistance ◽  
Emission Signal ◽  
Impact Bending ◽  
Artificial Neural

The study of metals in impact bending and indentation is considered. A bench is developed for assessing the character of failure on the example of 45 steel at low temperatures using the classification of acoustic emission signal pulses and a trained artificial neural network. The results of fractographic studies of samples on impact bending correlate well with the results of pulse recognition in the acoustic emission signal. Keywords acoustic emission, classification, artificial neural network, low temperature, character of failure, hardness. [email protected]

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