Acoustic Emission Monitoring Technology Used in the Ceramics Grinding Cut Depth Control

2011 ◽  
Vol 103 ◽  
pp. 464-468
Author(s):  
Min Wang ◽  
Tao Zan ◽  
Lei Hu ◽  
Jian Zhong Hu ◽  
Xin Yun Zhang
Keyword(s):  
Acoustic Emission ◽  
Material Removal ◽  
Ductile Material ◽  
Precision Grinding ◽  
Depth Control ◽  
Ceramic Grinding ◽  
Fracture Damage ◽  
Cut Depth ◽  
The Relationship ◽  
Ae Signals

Precision grinding on brittle materials accomplished without generating subsurface fracture damage is called ductile-regime grinding. The most important key point for maintaining a ductile material removal regime is to ensure that the cut depth made by grinding process does not exceed the critical cut depth. Through collecting and processing the acoustic emission(AE) signals generated by zirconia (PSZ) ceramic grinding tests, and analyzed the characteristics of AE signals under different grinding parameters. As a result of the experiments described in this paper, it can be concluded that AE signals measured during micro-grinding are sensitive to the changes of cut d- epths. The relationship between AE signals and material removal regime could lead to an in-process sensing strategy of the cut depths for ensuring grinding processes under ductile regime.

Grinding Acoustic Emission Classification in Terms of Mechanical Behaviours

2007 ◽  
Vol 329 ◽  
pp. 15-20 ◽  
Author(s):  
Xun Chen ◽  
James Griffin
Keyword(s):  
Neural Network ◽  
Acoustic Emission ◽  
Material Removal ◽  
Grinding Process ◽  
Short Time Fourier Transform ◽  
Fundamental Investigation ◽  
Mechanical Behaviours ◽  
Wavelets Transform ◽  
Short Time ◽  
Ae Signals

The material removal in grinding involves rubbing, ploughing and cutting. For grinding process monitoring, it is important to identify the effects of these different phenomena experienced during grinding. A fundamental investigation has been made with single grit cutting tests. Acoustic Emission (AE) signals would give the information relating to the groove profile in terms of material removal and deformation. A combination of filters, Short-Time Fourier Transform (STFT), Wavelets Transform (WT), statistical windowing of the WT with the kurtosis, variance, skew, mean and time constant measurements provided the principle components for classifying the different grinding phenomena. Identification of different grinding phenomena was achieved from the principle components being trained and tested against a Neural Network (NN) representation.

scholarly journals Internal Leakage Predicition of Hydraulic Spool valves Based on Acoustic Emission Technology

2021 ◽  
Vol 2113 (1) ◽  
pp. 012016
Author(s):  
Fei Song ◽  
Likun Peng ◽  
Jia Chen ◽  
Benmeng Wang
Keyword(s):  
Acoustic Emission ◽  
High Frequency ◽  
Peak Frequency ◽  
Leakage Rate ◽  
High Frequency Band ◽  
Signal Characteristics ◽  
Spool Valves ◽  
The Relationship ◽  
Ae Signals ◽  
Acoustic Emission Technology

Abstract In order to realize the nondestructive testing (NDT) of the internal leakage fault of hydraulic spool valves, the internal leakage rate must be predicted by AE (acoustic emission) technology. An AE experimental platform of internal leakage of hydraulic spool valves is built to study the characteristics of AE signals of internal leakage and the relationship between AE signals and leakage rates. The research results show the AE signals present a wideband characteristic. The main frequencies are concentrated in 30~50 kHz and the peak frequency is around 40 kHz. When the leakage rate is large, there are significant signal characteristics appearing in the high frequency band of 75~100 kHz. The exponent of the root mean square(RMS) of AE signals is positively correlated with the exponent of the leakage rate only if the leakage rate is greater than 2~3 mL/min. This find could be used to predict the internal leakage rate of hydraulic spool valves.

Acoustic Emission During Athermal Martensitic Transformation in Steels

1990 ◽  
Vol 112 (1) ◽  
pp. 84-91 ◽  
Author(s):  
Xiangying Liu ◽  
Elijah Kannatey-Asibu
Keyword(s):  
Free Energy ◽  
Acoustic Emission ◽  
Martensitic Transformation ◽  
Signal Intensity ◽  
Temperature Derivative ◽  
Process Characteristics ◽  
Ae Signal ◽  
The Relationship ◽  
Ae Signals ◽  
Start Temperature

A relationship developed earlier between acoustic emission signals and the process of athermal martensitic transformation based on the free energy associated with the process is extended and verified experimentally. The relationship is found to model the process characteristics very well. The intensity of AE signal generated during transformation was found to be proportional to the temperature derivative of the fraction of martensite, the cooling rate, and volume of specimen. The AE signal was also found to be related to the carbon content of the steel. During transformation, the signal intensity was found to increase to a peak, and then tail off near the end of the transformation. Values of the martensite start temperature obtained from plots of the total RMS squared AE signals were also found to correlate well with values from the literature.

Quantitative Relationship between Strain and Acoustic Emission Response in Monitoring Fatigue Damage

2013 ◽  
Vol 66 (1) ◽  
Author(s):  
M. Mohammad ◽  
S. Abdullah ◽  
N. Jamaludin ◽  
O. Innayatullah
Keyword(s):  
Acoustic Emission ◽  
Failure Mechanism ◽  
Fatigue Failure ◽  
Quantitative Relationship ◽  
Steel Specimen ◽  
Cyclic Fatigue ◽  
Steel Component ◽  
Specific Data ◽  
The Relationship ◽  
Ae Signals

This study was carried out to investigate the relationship between the strain and acoustic emission (AE) signals, thus, to confirm the capability of AE technique to monitor the fatigue failure mechanism of a steel component. To achieve this goal, strain and AE signals were captured on the steel specimen during the cyclic fatigue test.  Both signals were collected using specific data acquisition system by attaching the strain gauge and AE piezoelectric transducer simultaneously at the specimen during the test. The stress loading used for the test was set at 600 MPa, and the specimens were fabricated using the SAE 1045 carbon steel.  The related parameters for both signals were determined at every 2000 seconds until the specimen failed.  It was found that a meaningful correlation of all parameters, i.e. amplitude, kurtosis and energy, was established. Finally, all AE parameters are correlated with the damage values, which have been estimated using the Coffin-Manson model.  Hence, it was suggested that the AE technique can be used as a monitoring tool for fatigue failure mechanism in a steel component.

Material removal monitoring in precision cylindrical plunge grinding using acoustic emission signal

2013 ◽  
Vol 228 (4) ◽  
pp. 715-722 ◽  
Author(s):  
Chen Jiang ◽  
Haolin Li ◽  
Yunfei Mai ◽  
Debao Guo
Keyword(s):  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Material Removal ◽  
Grinding Force ◽  
Force Model ◽  
Precision Grinding ◽  
Emission Signal ◽  
Proposed Model ◽  
Acoustic Emission Sensing ◽  
Series Of Experiments

A mathematical model of the acoustic emission signal during a grinding cycle is proposed for the monitoring of material removal in precision cylindrical grinding. Acoustic emission signals generated during precision grinding are sensitive to forces in grinding and present opportunities in accurate and reliable process monitoring. The proposed model is developed on the basis of a traditional grinding force model. Using the developed model, a series of experiments were performed to demonstrate the effectiveness of the acoustic emission-sensing approach in estimating the time constant and material removal in grinding. Results indicate that acoustic emission measurements can be used in the prediction of material removal in precision grinding with excellent sensitivity.

Research on the AE Characteristic of the Rock with Rockburst Proneness

2014 ◽  
Vol 608-609 ◽  
pp. 689-692
Author(s):  
Mo Xiao Li ◽  
Guang Zhang ◽  
Jing Xi Chen
Keyword(s):  
Acoustic Emission ◽  
Uniaxial Compression ◽  
Rock Mechanics ◽  
Compression Tests ◽  
Entire Process ◽  
The Relationship ◽  
Ae Signals

In this paper, in order to strengthen the prediction of rockburst and inquire the relationship between the rockburst proneness of rock and its AE characteristic, each kind of typical rock of volcanic, sedimentary and metamorphic were selected to doing indoor rock mechanics experiments. Calculate the rockburst proneness of these rocks by uniaxial compression tests. In uniaxial compression, we collect the entire process of AE signals by using acoustic emission instrument, then we analysis the AE characteristics of different rocks to inquire the relationship between the AE characteristic and its rockburst proneness.

Acoustic Emission Signals in the Micro-EDM of PCD

2008 ◽  
Vol 33-37 ◽  
pp. 1181-1186 ◽  
Author(s):  
M. Mahardika ◽  
Kimiyuki Mitsui ◽  
Zahari Taha
Keyword(s):  
Acoustic Emission ◽  
Elastic Wave ◽  
Electrical Discharge ◽  
Material Removal ◽  
Electrical Discharge Machining ◽  
Polycrystalline Diamond ◽  
Micro Edm ◽  
Micro Electrical Discharge Machining ◽  
Single Discharge ◽  
Ae Signals

The mechanism of fracture in micro-electrical discharge machining (-EDM) processes is related to the discharge pulses energy. This paper investigates the correlation of fractures and discharge pulses energy in the -EDM of polycrystalline diamond (PCD) to the acoustic emission (AE) signals. The evaluation of fracture mechanism was done by measuring the generation and propagation of elastic wave in single discharge pulse by using AE sensor. The results show a strong correlation between fractures and discharge pulses energy to the AE signals and mechanism of material removal in the -EDM processes.

Identification of Brittle-Ductile Material Removal Characteristics in Ultrasonic Aided Lapping of Engineering Ceramics

2010 ◽  
Vol 126-128 ◽  
pp. 487-492 ◽  
Author(s):  
Feng Jiao ◽  
Chong Yang Zhao ◽  
Bo Zhao
Keyword(s):  
Material Removal ◽  
Online Monitoring ◽  
Ductile Material ◽  
Precision Engineering ◽  
Monitoring Technology ◽  
Engineering Ceramics ◽  
Online Identification ◽  
Ductile Regime Machining ◽  
Wavelet Package Analysis ◽  
Ae Signals

For the precision engineering ceramics parts, semi-ductile regime machining technologies are usually adopted to obtain the final surface. It is very important to research the brittle-ductile material removal characteristics and corresponding monitoring technology in ultrasonic aided lapping of engineering ceramics to obtain better surface quality. A series of lapping tests were carried out in the paper and the influence law of lapping parameters on the ductile percentage of ultrasonic lapped surface was achieved, which enables to off-line identify the material removal characteristics. Though the material removal characteristics can be online judged through monitoring the ratio of lapping component forces qualitatively, the monitoring effect is worse just because of lower response frequency of dynamometer and the relativity of lapping force. In this paper, a novel online monitoring technology of material removal characteristics is put forward based on AE technology. Through the wavelet package analysis of AE signals, the discrimination index and standard of material removal characteristics can be obtained. It is proved that this technology can realize online identification of the brittle-ductile material removal characteristics in ultrasonic aided lapping of engineering ceramics effectively.

The Efficiency Optimization of the Cylindrical Grinding Based on Acoustic Emission Signals

2014 ◽  
Vol 494-495 ◽  
pp. 721-724
Author(s):  
Qi Song
Keyword(s):  
Acoustic Emission ◽  
Newton Method ◽  
Grinding Process ◽  
Stable Point ◽  
Efficiency Optimization ◽  
Cylindrical Grinding ◽  
Grinding Efficiency ◽  
The Relationship ◽  
Ae Signals ◽  
Grinding Time

To improve the efficiency of cylindrical plunge grinding, an optimization of grinding process is developed using the Acoustic emission (AE) signals. The relationship between the grinding feed and grinding depth is established based on the elastic deflection between wheel and workpiece. Acoustic emission (AE) signals are curve fitted through the gauss - Newton method to find the stable point of various grinding processes. Therefore, grinding time of each grinding stage is reduced to improve the grinding efficiency.

scholarly journals Study on the Acoustic Emission Characteristics of Different Rock Types and Its Fracture Mechanism in Brazilian Splitting Test

2021 ◽  
Vol 9 ◽  
Author(s):  
Li Shengxiang ◽  
Xie Qin ◽  
Liu Xiling ◽  
Li Xibing ◽  
Luo Yu ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Rock Fracture ◽  
Peak Frequency ◽  
Test System ◽  
Mineral Particle ◽  
Splitting Test ◽  
Ae Signal ◽  
The Relationship ◽  
Ae Signals ◽  
Internal Fracture

In order to investigate the relationship between rock microfracture mechanism and acoustic emission (AE) signal characteristic parameters under split loads, the MTS322 servo-controlled rock mechanical test system was employed to carry out the Brazilian split tests on granite, marble, sandstone, and limestone, while FEI Quanta-200 scanning electron microscope system was employed to carry out the analysis of fracture morphology. The results indicate that different scales of mineral particle, mineral composition, and discontinuity have influence on the fracture characteristics of rock, as well as the b-value. The peak frequency distribution of the AE signal has obvious zonal features, and these distinct peak frequencies of four types of rock fall mostly in ranges of 0–100 kHz, 100–300 kHz, and above 300 kHz. Due to the different rock properties and mineral compositions, the proportions of peak frequencies in these intervals are also different among the four rocks, which are also acting on the b-value. In addition, for granite, the peak frequencies of AE signals are mostly distributed above 300 kHz for granite, marble, and limestone, which mainly derive from the internal fracture of k-feldspar minerals; for marble, the AE signals with peak frequency are mostly distributed in over 300 kHz, which mainly derive from the internal fracture of dolomite minerals and calcite minerals; AE signals for sandstone are mostly distributed in the range of 0–100 kHz, which mainly derive from the internal fracture of quartz minerals; for limestone, the AE signals with peak frequency are mostly distributed in over 300 kHz, which mainly derive from the internal fracture of granular-calcite minerals. The relationship between acoustic emission signal frequency of rock fracture and the fracture scale is constructed through experiments, which is of great help for in-depth understanding of the scaling relationship of rock fracture.

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