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 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.

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.

Characterizing Fracture Development in Ti-Alloy with I-Type Cracks Using Acoustic Emission and Thermal Infrared Imaging

2016 ◽  
Vol 725 ◽  
pp. 477-482 ◽  
Author(s):  
Hao Ouyang ◽  
Jian Shi ◽  
Hidetoshi Sakamoto ◽  
Guang Hui Zhao
Keyword(s):  
Plastic Deformation ◽  
Acoustic Emission ◽  
Uniaxial Tension ◽  
Infrared Imaging ◽  
Thermal Infrared ◽  
Ti Alloy ◽  
Ae Energy ◽  
Deformation And Fracture ◽  
Fracture Development ◽  
Fracture Processes

This paper discusses the plastic deformation and fracture development of Ti-alloy under uniaxial tension. The energy dissipation and transfer characteristics in the plastic deformation and fracture processes were analyzed using acoustic emission (AE), thermal infrared (TIR) imaging, and thermocouples. Uniaxial tension tests were carried out, during which TIR images were obtained and the AE energy was observed. The mechanical characteristics of Ti-alloy with I-type cracks were analyzed based on the TIR images, AE energy, and temperature. The plastic work of the Ti-alloy specimen was found to dissipate as thermal energy rather than AE energy. Moreover, the TIR images were correlated well with the AE energy observed during the plastic deformation and fracture processes of the material.

scholarly journals Failure mechanism and acoustic emission signal characteristics of coatings under the condition of impact indentation

2019 ◽  
Vol 38 (2019) ◽  
pp. 601-611
Author(s):  
Dong Tian-Shun ◽  
Wang Ran ◽  
Li Guo-Lu ◽  
Liu Ming
Keyword(s):  
Acoustic Emission ◽  
Surface Morphology ◽  
Failure Mechanism ◽  
Bonding Strength ◽  
Cross Sectional ◽  
Emission Signal ◽  
Signal Characteristics ◽  
Interface Cracking ◽  
Ae Signal ◽  
The Impact

AbstractIn this work, the substrate, NiCr coating, Al2O3 coating with NiCr undercoating and Al2O3 coating were tested by an impact indentation device equipped with an acoustic emission (AE) detection equipment. The surface morphology, dimension, cross-sectional image, 3D topography of indention and bonding strength of coatings were analyzed. The failure mechanism and AE signal characteristics of the coatings under impact were studied. The results demonstrate that the failure mode of NiCr coating was dominated by interface cracking, and that of Al2O3 coating is fracture and accompanied by a small amount of interface cracking, while Al2O3 coating with NiCr undercoating possesses common characteristics of the first two. The energy counting and wave voltage of AE signal were more sensitive to the bonding strength of coating in the impact process, which can be used to characterize the bonding strength of coating.

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.

Study on Evaluation of AE Signals at Weld Region of SA 516 Steel

2006 ◽  
Vol 321-323 ◽  
pp. 1729-1732
Author(s):  
Na Eui Gyun ◽  
Kim Hoon ◽  
Kanji Ono
Keyword(s):  
Mechanical Properties ◽  
Heat Treatment ◽  
Plastic Deformation ◽  
Signal Strength ◽  
Post Weld Heat Treatment ◽  
Bend Test ◽  
Weld Region ◽  
Signal Characteristics ◽  
Ae Signal ◽  
Ae Signals

The purpose of this study is to find out the method to detect AE signals at around the notch tip and to evaluate the AE signal characteristics for the basemetal, PWHT(post weld heat treatment) and weldment specimens of SA-516 steel during bend test. AE signals were produced in the process of plastic deformation. AE signal strength and amplitude of the weldment was the strongest, followed by PWHT specimen and basemetal. More AE signals were produced from the weldment because of the oxides, and discontinuous mechanical properties. The stronger AE signal strength, amplitude and more AE event counts for the weldment were shown.

Acoustic Emission Signal Analysis for Tool Condition Monitoring in Microendmilling of Aluminium Alloy

2014 ◽  
Vol 984-985 ◽  
pp. 25-30
Author(s):  
Muniyandi Prakash ◽  
P. Ravisankar ◽  
Mani Kanthababu
Keyword(s):  
Acoustic Emission ◽  
Tool Wear ◽  
Aluminium Alloy ◽  
Condition Monitoring ◽  
Dominant Frequency ◽  
Tool Condition Monitoring ◽  
Tool Condition ◽  
Ae Energy ◽  
Ae Signal ◽  
Ae Signals

In this study, the effect of tool wear is correlated with acoustic emission (AE) signal during microendmilling of aluminium alloy (AA 1100). The AE signals were acquired using Kistler make AE sensor and the signal features are analyzed in time domain (root mean square (RMS)) and frequency domain (dominant frequency and amplitude). The dominant frequency of the AE signal shows increasing trend with increase in the tool wear, where as AERMSshow uneven trend. The discrete wavelet transformation technique (DWT) has also been carried out by decomposing the required AE signal in different frequency bands. The AERMSand specific AE energy were computed for the decomposed AE signals. From the specific AE energy, it is observed that shearing occurs during microendmilling and also found to be similar that of macro-regieme endmilling. The result demonstrated that the AE signals are potential indicator for tool condition monitoring in microendmilling.

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.

scholarly journals The Chemical Softening Effect and Mechanism of Low Rank Coal Soaked in Alkaline Solution

2019 ◽  
Vol 17 (1) ◽  
pp. 1449-1458
Author(s):  
Gao Zhixiang ◽  
Guo Hongyu ◽  
Dong Zhiwei ◽  
Luo Yuan ◽  
Xia Daping
Keyword(s):  
Alkaline Solution ◽  
Count Rate ◽  
Coal Sample ◽  
Low Rank ◽  
Stress Strain ◽  
Softening Effect ◽  
Energy Rate ◽  
Ae Energy ◽  
Ae Signal ◽  
Chemical Softening

AbstractIn order to analyze the feasibility of chemical softening on low rank coals, bituminous coal was collected from the Qianqiu mine in Henan Province, China, and soaked in water and alkaline solution for different lengths of time. The complete stress-strain and acoustic emission (AE) experiments on the coal samples under uniaxial compression were tested on the RMT-150B Rock Mechanics Testing System and DS2 series AE signal analyzer. The results showed that the coal samples soaked in the water and alkaline solution present different characteristics in the deformation and failure process. As we increase the soaking time, the uniaxial compressive strength and deformation degree of the soaked coal samples in the alkaline solution and water decreased by 42.7% and 94.8% respectively. In the loading test, an AE signal is generated in all coal samples and the maximum ringing count rate and AE energy rate are present near the stress maximum for a short time. Moreover, the ringing count rate and AE energy rate have a good consistency with the stress-strain of the coal samples. The cumulative ringing count of the two groups soaked in water and alkaline solution decreased by 51% and 89% compared to the original coal sample. However, the decreased degree of the samples soaked in the alkaline solution is much higher than that of those soaked in water and the results showed that the alkaline solution has a better softening effect on the coal sample. With the increase of the alkaline solution concentration, the contact angle decreased from 112.5° to 41°. Through microscope and scanning electron microscopy (SEM) analysis of the soaked coal samples, we found that the pores and fissures increased, the structure of coal became loose, and the mechanical strength decreased sharply after soaking in the alkaline solution, thus achieving a chemical softening effect.

Sign in / Sign up

Export Citation Format

Share Document