Detection of the Rotating Cutting Tool Failure with an Acoustic Emission Sensor.

Development of modern society is converging to a status where many human actions can be performed by machines. To achieve production without human intervention, machines require artificial receptors. Data gathering for processing and analysis of signals, together with determination of feedback reactions can be achieved by a suitable decision maker unit. A sensed value suited to this so-called intelligent sensing process would be the acoustic emission signal. In the case of intelligent cutting tools this would require miniature highly sensitive sensors integrated into the cutting tool body. Part I of this paper deals with the possibility of practical usage of the piezoelectric properties of copolymer foils for the acoustic emission sensor as a transducer of a mechanical surface wave into electrical signal. Part II of the paper deals with the most fundamental requirement for monitoring of cutting conditions during machining, i.e. excellent processing of measured data. Data obtained from machining process obtained by means of acoustic emission sensors, as discussed in the first part of this article, have high-frequency and continuous character of a white noise. These data are very difficult to process. New apparatus for transformation of acoustic emission into audible sound in the workplace is presented. The first stage of processing is by listening to transformed data it is subjectively possible to recognize differences in audible spectrum, corresponding to different states of the cutting tool. The second step is visualization of the differences via the fast Fourier transform (FFT) in the spectrum graphic chart.

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Experimental investigation on time-domain features in the diagnosis of rolling element bearings by acoustic emission

Journal of Vibration and Control ◽

10.1177/10775463211016130 ◽

2021 ◽

pp. 107754632110161

Author(s):

Aref Aasi ◽

Ramtin Tabatabaei ◽

Erfan Aasi ◽

Seyed Mohammad Jafari

Keyword(s):

Acoustic Emission ◽

Condition Monitoring ◽

Time Domain ◽

Central Moment ◽

Rolling Element Bearings ◽

Test Rig ◽

Acoustic Emission Sensor ◽

Outer Race ◽

Common Time ◽

Rolling Element

Inspired by previous achievements, different time-domain features for diagnosis of rolling element bearings are investigated in this study. An experimental test rig is prepared for condition monitoring of angular contact bearing by using an acoustic emission sensor for this purpose. The acoustic emission signals are acquired from defective bearing, and the sensor takes signals from defects on the inner or outer race of the bearing. By studying the literature works, different domains of features are classified, and the most common time-domain features are selected for condition monitoring. The considered features are calculated for obtained signals with different loadings, speeds, and sizes of defects on the inner and outer race of the bearing. Our results indicate that the clearance, sixth central moment, impulse, kurtosis, and crest factors are appropriate features for diagnosis purposes. Moreover, our results show that the clearance factor for small defects and sixth central moment for large defects are promising for defect diagnosis on rolling element bearings.

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Development of a low‐power wireless acoustic emission sensor node for aerospace applications

Structural Control and Health Monitoring ◽

10.1002/stc.2701 ◽

2021 ◽

Author(s):

Stephen Grigg ◽

Rhys Pullin ◽

Matthew Pearson ◽

David Jenman ◽

Robert Cooper ◽

...

Keyword(s):

Acoustic Emission ◽

Low Power ◽

Sensor Node ◽

Acoustic Emission Sensor ◽

Aerospace Applications

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Acoustic Emission Studies on Carbon/Phenolic Ablative Composites using PCD and PCBN Tools

Advanced Composites Letters ◽

10.1177/096369359900800301 ◽

1999 ◽

Vol 8 (3) ◽

pp. 096369359900800 ◽

Cited By ~ 3

Author(s):

P. S. Sreejith ◽

R. Krishnamurthy

Keyword(s):

Acoustic Emission ◽

Condition Monitoring ◽

Cutting Tool ◽

Tool Condition Monitoring ◽

Tool Condition ◽

The Status ◽

Emission Studies ◽

Pcbn Tools ◽

Cutting Speeds ◽

Phenolic Composite

During manufacturing, the performance of a cutting tool is largely dependent on the conditions prevailing over the tool-work interface. This is mostly dependent on the status of the cutting tool and work material. Acoustic emission studies have been performed on carbon/phenolic composite using PCD and PCBN tools for tool condition monitoring. The studies have enabled to understand the tool behaviour at different cutting speeds.

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High-temperature (> 1000 °C) acoustic emission sensor

10.1117/12.2009301 ◽

2013 ◽

Cited By ~ 2

Author(s):

Joseph A. Johnson ◽

Kyungrim Kim ◽

Shujun Zhang ◽

Di Wu ◽

Xiaoning Jiang

Keyword(s):

Acoustic Emission ◽

High Temperature ◽

Acoustic Emission Sensor

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Tool Wear Detection Using Time Series Analysis of Acoustic Emission

Journal of Engineering for Industry ◽

10.1115/1.3188750 ◽

1989 ◽

Vol 111 (3) ◽

pp. 199-205 ◽

Cited By ~ 125

Author(s):

S. Y. Liang ◽

D. A. Dornfeld

Keyword(s):

Time Series ◽

Acoustic Emission ◽

Tool Wear ◽

Time Series Analysis ◽

Cutting Tool ◽

Shear Zones ◽

Parameter Vector ◽

Model Parameter ◽

Cutting Tool Wear ◽

Series Analysis

This paper discusses the monitoring of cutting tool wear based on time series analysis of acoustic emission signals. In cutting operations, acoustic emission provides useful information concerning the tool wear condition because of the fundamental differences between its source mechanisms in the rubbing friction on the wear land and the dislocation action in the shear zones. In this study, a signal processing scheme is developed which uses an autoregressive time-series to model the acoustic emission generated during cutting. The modeling scheme is implemented with a stochastic gradient algorithm to update the model parameters adoptively and is thus a suitable candidate for in-process sensing applications. This technique encodes the acoustic emission signal features into a time varying model parameter vector. Experiments indicate that the parameter vector ignores the change of cutting parameters, but shows a strong sensitivity to the progress of cutting tool wear. This result suggests that tool wear detection can be achieved by monitoring the evolution of the model parameter vector during machining processes.

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Study of the Metal Crack Propagation by Acoustic Emission Testing

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.105-107.2179 ◽

2011 ◽

Vol 105-107 ◽

pp. 2179-2182

Author(s):

Wei Min Zhang ◽

Shu Xuan Liu ◽

Yong Qiu ◽

Cheng Feng Chen

Keyword(s):

Acoustic Emission ◽

Crack Propagation ◽

Acquisition System ◽

Signal Acquisition ◽

Sensor Signal ◽

Acoustic Emission Sensor ◽

Axial Tension ◽

Emission Testing ◽

Acoustic Emission Testing ◽

Signal Operating

Crack propagation is the main reason which leads to the invalidity of the metal components. A set of detecting equipment based on the acoustic emission method was designed, and it was mainly composed of acoustic emission sensor, signal operating circuits and signal acquisition system. Specimens of 16MnR material were manufactured and the static axial tension test of them was carried on. Acoustic emission signals from the specimen were detected by acoustic emission equipment by using piezoelectric ceramic sensor. Signal datum were acquired and operated by the acquisition system, as well as the acquisition program written for it. The final results has demonstrated that acoustic emission equipment designed for the test performed well in acquiring the signals induced by the metal crack propagation.

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Simultaneous Monitoring of Rolling-Element and Journal Bearings Using Analysis of Structure-Born Ultrasound Acoustic Emissions

Volume 13: Sound, Vibration and Design ◽

10.1115/imece2010-39814 ◽

2010 ◽

Cited By ~ 1

Author(s):

A. Albers ◽

M. Dickerhof

Keyword(s):

Acoustic Emission ◽

Acoustic Emissions ◽

Piezoelectric Sensor ◽

Journal Bearings ◽

Rolling Element Bearings ◽

Acoustic Emission Sensor ◽

Outer Race ◽

Rolling Element ◽

Characteristic Values ◽

Acoustic Emission Technology

The application of Acoustic Emission technology for monitoring rolling element or hydrodynamic plain bearings has been addressed by several authors in former times. Most of these investigations took place under idealized conditions, to allow the concentration on one single source of emission, typically recorded by means of a piezoelectric sensor. This can be achieved by either eliminating other sources in advance or taking measures to shield them out (e. g. by placing the acoustic emission sensor very close to the source of interest), so that in consequence only one source of structure-born sound is present in the signal. With a practical orientation this is often not possible. In point of fact, a multitude of potential sources of emission can be worth considering, unfortunately superimposing one another. The investigations reported in this paper are therefore focused on the simultaneous monitoring of both bearing types mentioned above. Only one piezoelectric acoustic emission sensor is utilized, which is placed rather far away from the monitored bearings. By derivation of characteristic values from the sensor signal, different simulated defects can be detected reliably: seeded defects in the inner and outer race of rolling element bearings as well as the occurrence of mixed friction in the sliding surface bearing due to interrupted lubricant inflow.

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