In-Process Tool Fracture Detection

1984 ◽  
Vol 106 (2) ◽  
pp. 111-118 ◽  
Author(s):  
M. S. Lan ◽  
D. A. Dornfeld
Keyword(s):  
Acoustic Emission ◽  
Fracture Surface ◽  
Signal Analysis ◽  
Cutting Tool ◽  
Fracture Detection ◽  
Acoustic Emission Energy ◽  
Emission Energy ◽  
Ae Signal ◽  
The Relationship ◽  
Carbide Insert

This paper investigates the feasibility of using acoustic emission (AE) signal analysis for the detection of the breakage as well as the chipping of a cutting tool during machining. Experiments were conducted on a lathe using conventional carbide insert tools under realistic cutting conditions. The tangential and feed forces were also measured for comparisons. The sensitivities of the AE signal and cutting forces to insert chipping and fracture are illustrated. The relationship between acoustic emission energy and the combined effect of fracture surface area and cutting load is discussed.

scholarly journals Analysis of the Suitability of Signal Features for Individual Sensor Types in the Diagnosis of Gradual Tool Wear in Turning

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6489
Author(s):  
Joanna Kossakowska ◽  
Sebastian Bombiński ◽  
Krzysztof Ejsmont
Keyword(s):  
Acoustic Emission ◽  
Tool Wear ◽  
Signal Analysis ◽  
Cutting Tool ◽  
Large Set ◽  
Signal Features ◽  
Signal Characteristics ◽  
Basic Set ◽  
New Generation ◽  
The Relationship

There are many items in the literature indicating that certain signal features (SFs) of cutting forces, vibrations or acoustic emission are useful for the diagnosis of tool wear in certain single experiments. There is no answer to whether these SFs are universal. The novelty of this article is an attempt to answer these questions and propose a large set of SFs related to tool wear, but without including superfluous SFs. The analysis of the usefulness of the signal properties for the state of the cutting tool in turning was carried out on a large experiment. A number of various SFs obtained for various signal analysis methods were selected for the study. It is found that no SF is always related to the tool wear, so we define many different signal characteristics that can be related to the tool wear (basic set) and automatically select those associated with it in a given machining case. To this end, the relationship between the measures and the wear of the tool was analyzed. Interrelated measures were excluded from it. The obtained results can be used to build a new generation of more effective tool wear diagnostics systems. One of the goals of the tool wear diagnosis system is to save the energy used. The results can also enable the refinement of existing algorithms that predict the energy consumption of a machine.

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.

Subcritical Fracturing of Sandstone Characterized by the Acoustic Emission Energy

2019 ◽  
Vol 52 (7) ◽  
pp. 2459-2469 ◽  
Author(s):  
Yuekun Xing ◽  
Guangqing Zhang ◽  
Bin Wan ◽  
Hui Zhao
Keyword(s):  
Acoustic Emission ◽  
Acoustic Emission Energy ◽  
Emission Energy
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