The identification of abrasive grains in the decohesion process by acoustic emission signal patterns

Sutowski, Paweł; Nadolny, Krzysztof

doi:10.1007/s00170-016-8504-9

Cited by 3 publications

(2 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The AE generated during machining and grinding processes has been proved to be related to the process state and to the surface condition of the tool and workpiece [ 17 , 18 ]. Therefore, AE technology has been widely used as a non-destructive inspection method for monitoring a wide variety of machining processes and industrial applications [ 19 ], including grinding [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 ], turning [ 31 , 32 , 33 ], electro-discharge grinding [ 20 ], sawing [ 34 ], abrasive water jet machining [ 35 ], rock bridge stability [ 36 ], welding [ 37 ], vibroarthrography [ 38 ], monitoring of concrete materials [ 39 , 40 ], leakage [ 41 ], and power system [ 42 ].…”

Section: Introductionmentioning

confidence: 99%

Grinding Wheel Loading Evaluation by Using Acoustic Emission Signals and Digital Image Processing

Liu

2020

Sensors

View full text Add to dashboard Cite

In the manufacturing industry, grinding is used as a major process for machining difficult-to-cut materials. Grinding is the most complicated and precise machining process. For grinding machines, continuous generating gear grinding machines are widely used to machine gears which are essential machine elements. However, due to its complicated process, it is very difficult to design a reliable measurement method to identify the grinding wheel loading phenomena during the grinding process. Therefore, this paper proposes a measurement method to identify the grinding wheel loading phenomenon in the grinding process for continuous generating gear grinding machines. In the proposed approach, an acoustic emission (AE) sensor was embedded to monitor the grinding wheel conditions; an offline digital image processing technique was used to determine the loading areas over the surface of Al2O3 grinding wheels; and surface roughness of the ground workpiece was measured to quantify its machining quality. Then these three data were analyzed to find their correlation. The experimental results have shown that there are two stages of grinding in the grinding process and the proposed measurement method can provide a quantitative grinding wheel loading evaluation from the AE signals online.

show abstract

Section: Introductionmentioning

confidence: 99%

Grinding Wheel Loading Evaluation by Using Acoustic Emission Signals and Digital Image Processing

Liu

2020

Sensors

View full text Add to dashboard Cite

show abstract

“…So far, the use of this type of sensor in centrifugal disc finishing process research has not been noticed by authors. Sutowski and Sutowska [6] presented a possible AE diagnostic method to be applied in the abrasive waterjet machining, cylindrical grinding [7], abrasive electro-discharge grinding process [8], and analysis of decohesion process of abrasive grains [9].…”

Section: Introductionmentioning

confidence: 99%

Determining kinetic energy distribution of the working medium in a centrifugal disc finishing process—part 2: experimental analysis with the use of acoustic emission signal

Sutowski

Plichta

Kaldunski

2019

Int J Adv Manuf Technol

Self Cite

View full text Add to dashboard Cite

This paper addresses the problem of estimating the kinetic energy distribution of the working medium in a centrifugal disc finishing process. Centrifugal disc finishing is a highly effective way of finishing surfaces, especially in the case of complex shapes, made from a variety of materials. The process is, however, frequently very time-consuming. The identification method of a region with a high kinetic energy potential by measurement of acoustic emission signal is described and verified by surface roughness tests. Signal analysis was carried out in both time and frequency domain. The results presented in experimental tests and analyses indicate that various parameters of the AE signal, including its energy, are variable and determined by abrasive particles' velocity and location in an axial cross section of the working medium. On the basis of the root mean square value of the signal, the maps of the distribution of the energy potential of the working medium are presented. Experimental results demonstrate process improvement and a significant reduction (approx 60%) of the arithmetic mean deviation of surface roughness, obtained at the same time of machining. The article also presents the functional relations between the selected AE signal descriptors and the rotational speed of the working chamber rotor. Since the article is a continuation of the previous studies, the results obtained were briefly referred to the simulation results.

show abstract

Evaluation of grinding wheel loading phenomena by using acoustic emission signals

Liu

2018

Int J Adv Manuf Technol

View full text Add to dashboard Cite

The identification of abrasive grains in the decohesion process by acoustic emission signal patterns

Cited by 3 publications

References 25 publications

Grinding Wheel Loading Evaluation by Using Acoustic Emission Signals and Digital Image Processing

Grinding Wheel Loading Evaluation by Using Acoustic Emission Signals and Digital Image Processing

Determining kinetic energy distribution of the working medium in a centrifugal disc finishing process—part 2: experimental analysis with the use of acoustic emission signal

Evaluation of grinding wheel loading phenomena by using acoustic emission signals

Contact Info

Product

Resources

About