Monitoring of the High-Technology Nailing of CFRTP Material under Ultrasonic Vibration by Acoustic Emission Method

2020 ◽  
Vol 1009 ◽  
pp. 25-30
Author(s):  
Yoshiaki Akematsu ◽  
Hiromitsu Gotho ◽  
Takayuki Tani ◽  
Hideaki Murayama ◽  
Tsuyoshi Matsuo ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Ultrasonic Vibration ◽  
Energy Parameter ◽  
High Technology ◽  
Acoustic Emission Method ◽  
Emission Method ◽  
Thermoplastic Material ◽  
Signal Characteristics ◽  
Ae Signal ◽  
Ae Signals

In this study, the potential to monitor the high-technology nailing of carbon fiber reinforced thermoplastic material (CFRTP) under ultrasonic vibration was investigated by acoustic emission (AE) method. AE signals were detected by a piezoelectric AE sensor during high-technology nailing under ultrasonic vibration. This paper describes some experimental results on AE signal characteristics and observation of the high-technology nailing. In order to investigate the effects of machining condition, we focused on RMS voltage, which is dependent on the energy parameter of the AE signal. It was found that the AE method is a useful method of monitoring high-technology nailing.

scholarly journals Separation of AE signals for detecting solidification cracking of Al–7 mass%Si alloy by using acoustic emission method

2010 ◽  
Vol 60 (10) ◽  
pp. 492-498 ◽  
Author(s):  
Itaru Endo ◽  
Hiroyuki Chiba ◽  
Toru Ueki ◽  
Takanari Toriyama ◽  
Makoto Yoshida
Keyword(s):  
Acoustic Emission ◽  
Solidification Cracking ◽  
Acoustic Emission Method ◽  
Emission Method ◽  
Ae Signals

scholarly journals Comparative analysis of the strength of restoration polymers of light polymerization for dental restoration using the acoustic emission method: part one

2021 ◽  
Vol 107 (3) ◽  
pp. 26-32
Author(s):  
V. Kukhta ◽  
◽  
V. Makeev ◽  
O. Kyrmanov ◽  
V. Skalsky ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Comparative Analysis ◽  
High Energy ◽  
Dental Restoration ◽  
Acoustic Emission Method ◽  
Local Loading ◽  
Emission Method ◽  
Composite Failure ◽  
Initial Stage ◽  
Ae Signals

Purpose. Comparative analysis of the strength of hybrid restoration composites of light polymerization during their local loading using the phenomenon of acoustic emission. The following restoration composites were studied: Latelux, Tetric N-Ceram, Charisma Classic. Results. It was determined that the nature of the destruction of all composites is the same: elastic-plastic at the initial stage of the load with a transition to brittle as its further growth. Three types of composite failure are observed: correct, incorrect and mixed. The first predominated during fracture under the action of local loading of the Latelux composite, for Tetric N-Ceram and Charisma Classic materials a mixed type of fracture is characteristic. Conclusions. Analysis of the parameters of the AE signals showed that the signals had the highest amplitude and energy when the Tetric N-Ceram composite was destroyed, and the lowest – Latelux. All dental composites are dominated by high-energy ductile-brittle and brittle fracture, which indicates the spread of micro- and macrocracks of various sizes in materials. Key words: polymer composites, strength, acoustic emission method.

The Design of Bearing Monitoring System Based on Acoustic Emission Signal

2014 ◽  
Vol 716-717 ◽  
pp. 940-943
Author(s):  
Ke Huang ◽  
Zhi Kang Bu ◽  
Chi Zhang ◽  
Heng Lian Xie
Keyword(s):  
Acoustic Emission ◽  
Monitoring System ◽  
Acoustic Emission Method ◽  
Emission Method ◽  
Emission Signal ◽  
Bearing Fault Diagnosis ◽  
Bearing Condition Monitoring ◽  
Condition Monitoring System ◽  
Bearing Monitoring ◽  
Ae Signals

After experimental verification, in terms of low-speed bearing fault diagnosis, the acoustic emission method is superior to the traditional vibration method. In order to further the study of the correlation between AE signals and the bearing state, this article refers to the bearing condition monitoring system, and gives detailed parts models, the acoustic emission acquisition system, which provides help for further researches.

Contrasts between the Acoustic Emission Signals Generated by Monopole Versus Dipole Sources

2006 ◽  
Vol 13-14 ◽  
pp. 61-68 ◽  
Author(s):  
Marvin A. Hamstad
Keyword(s):  
Acoustic Emission ◽  
Point Sources ◽  
Pass Filter ◽  
Signal Characteristics ◽  
Out Of Plane ◽  
Edge Surface ◽  
Ae Signal ◽  
Plane Displacement ◽  
Dipole Sources ◽  
Ae Signals

Acoustic emission (AE) practitioners routinely use surface pencil lead breaks (monopoles) to observe expected AE signal characteristics. In contrast, stress-generated AE sources are almost universally composed of dipoles. Thus, understanding the primary differences between the signals generated by these two different source classes is of key importance. This research had the goal of analyzing and contrasting the AE signals generated by monopole and dipole sources. A finite-element-modeled database of AE signals provided an ideal means to study these two source types. The AE signals represented the top-surface out-of-plane displacement versus time from point sources inside an aluminum plate 4.7 mm thick. In addition, monopole sources both on the plate top surface and the edge surface were included in the database. The AE signals were obtained from both in-plane and out-of-plane monopole and dipole sources. Results were analyzed with both a 100 to 300 kHz bandpass filter and a 40 kHz high-pass filter. The wide-plate specimen domain effectively eliminated edge reflections from interfering with the direct signal arrivals.

scholarly journals The Possibility of Applying Acoustic Emission Method for Monitoring Lathing Process

2019 ◽  
Vol 26 (2) ◽  
pp. 21-27
Author(s):  
Krzysztof Dudzik
Keyword(s):  
Acoustic Emission ◽  
Cutting Speed ◽  
Acoustic Emission Method ◽  
Turning Process ◽  
Frequency Range ◽  
Emission Method ◽  
Machining Processes ◽  
Stable Conditions ◽  
Ae Signal

Abstract Nowadays acoustic emission (AE) method is used in many fields of science, including in the diagnosis and monitoring of machining processes such as turning, grinding, milling, etc. Monitoring of turning process allows ensuring stable conditions of treatment. Stable conditions of turning process have a great impact on the quality of the surface. This is especially important during finishing treatment. The research was carried out on a universal ZMM-SLIVEN CU500MRD lathe centre-using tool with removable insert SANDVIK Coromant WNMG 080408 – WMX Wiper. Lathing process was performed on the shaft of 74 mm in diameter made of S235 steel. The research was carried out at constant cutting speed v = 230 m/min. Changed parameters were feed f = 0.1; 0.2; 0.4 mm/rev and cutting depth ap = 0.5; 0.75; 1 mm. In the research was used a set of acoustic emission Vallen System. The kit includes: 4 channel signal recorder AMSY 6, two measurement modules ASIP-2/S, preamplifier with a frequency range 20 kHz – 1 MHz and the strengthening of 34dB and AE signal measurement sensor type VS 150M, with a frequency range 100 – 450 kHz. During the study, the acoustic emission (AE) generated during the lathing process were recorded parameters e.g. amplitude, number of events – hits, the effective value of the signal (RMS). The test results indicate, that the higher instability of the process was during turning with parameters: ap = 0.75 mm and f = 0.1 mm/rev. The study can be the basis for the use of acoustic emission method for monitoring lathing process to ensure stable conditions of that process and the same to obtain a high quality surface.

The Study of Residual Stress in Welded Specimens of Aluminium Alloy by Using Acoustic Emission Method

2011 ◽  
Vol 110-116 ◽  
pp. 3617-3623
Author(s):  
Zaman Saeidi Nia ◽  
Mehdi Ahmadi Najaf Abadi ◽  
D. Jawabvar
Keyword(s):  
Residual Stress ◽  
Acoustic Emission ◽  
Residual Stresses ◽  
Offshore Structures ◽  
Pressure Vessels ◽  
Steel Bridge ◽  
Acoustic Emission Method ◽  
Emission Method ◽  
Tensile Stresses ◽  
Ae Signals

Welding is one of the most significant causes of residual stresses and typically produces large tensile stresses whose maximum value can be approximately equal to the yield strength of the materials being joined. These large tensile stresses are often responsible for premature component failure. Metallurgical welding joints are extensively used in the fabrication industry, including ships, offshore structures, steel bridge, and pressure vessels. In this study, residual stresses in welded specimens of AL–6061 were evaluated by using ACOUSTIC EMISSION method which is one of the nondestructive tests. In this work, AE signals formed during the tensile test of welded specimens were investigated. The results show that AE signals in specimens which have large amount of residual stress were detected in less load.

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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