Experimental study of tool life transition and wear monitoring in turning operation using a hybrid method based on wavelet multi-resolution analysis and empirical mode decomposition

Babouri, Mohamed Khemissi; Ouelaa, Nouredine; Djebala, Abderrazek

doi:10.1007/s00170-015-7530-3

Cited by 34 publications

(16 citation statements)

References 22 publications

(18 reference statements)

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“…According to the definition, acoustic emission is an evanescent elastic wave, which is the result of rapid release of the energy stored in the material by propagating a micro-damage (increase in micro-cracks, the movement of groups of dislocations) in the material or by a process (friction, leakage, etc. ), confirmed in research of Babouri et al [19]. The frequency range of a typical acoustic emission signal is usually determined in the range of 20 kHz to 2 MHz [20].…”

Section: Introductionmentioning

confidence: 82%

The Possibility of Applying Acoustic Emission and Dynamometric Methods for Monitoring the Turning Process

Dudzik

Labuda

2020

Materials

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Ensuring optimal turning conditions has a huge impact on the quality and properties of the machined surface. The condition of the cutting tool is one of the factors to achieve this goal. In order to control its wear during the turning process, monitoring was used. In this study, the acoustic emission method and measure of cutting forces during turning were used for monitoring that process. The research was carried out on a universal lathe center (CU500MRD type) using a Kistler dynamometer with assembled removable insert CCET09T302R-MF by DIJET Industrial CO., LTD. A dynamometer allows to measure forces Fx (radial force), Fy (feed force) and Fz (cutting force). The turning process was performed on a shaft with 60 mm diameter made of 304L stainless steel. The AE research was carried at Physical Acoustics Corporation with the kit that includes: recorder USB AE Node, preamplifier, AE-sensor VS 150M and computer with dedicated software used for recording and analyzing AE data. The aim of this paper is to compare selected diagnostic methods: acoustic emission and cutting forces measurement for monitoring wear of cutting tool edge. Analysis of the research results showed that both selected methods of monitoring the turning process allowed the determination of the beginning of the tool damage process.

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Section: Introductionmentioning

confidence: 82%

The Possibility of Applying Acoustic Emission and Dynamometric Methods for Monitoring the Turning Process

Dudzik

Labuda

2020

Materials

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“…Most studies presented results obtained on mechanized and robotized stands for welding methods that are carried out in an automated manner, such as gas metal arc (GMA) and TIG welding. This is the case for arc length-arc voltage relationship investigation [27][28][29][30] and for the monitoring of the welding process using vision systems [31][32][33]. Welding arcs glow brightly, and that glow comes from the radiation that the arc produces.…”

Section: Introductionmentioning

confidence: 99%

Assessing MMA Welding Process Stability Using Machine Vision-Based Arc Features Tracking System

Jamrozik

Górka

2020

Sensors

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Arc length is a crucial parameter of the manual metal arc (MMA) welding process, as it influences the arc voltage and the resulting welded joint. In the MMA method, the process’ stability is mainly controlled by the skills of a welder. According to that, giving the feedback about the arc length as well as the welding speed to the welder is a valuable property at the stage of weld training and in the production of welded elements. The proposed solution is based on the application of relatively cheap Complementary Metal Oxide Semiconductor (CMOS) cameras to track the welding electrode tip and to estimate the geometrical properties of welding arc. All measured parameters are varying during welding. To validate the results of image processing, arc voltage was measured as a reference value describing in some part the process stability.

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“…Additional advantage is longer tool operational time. Monitoring the tool wear allows obtaining high quality of machined surface and avoiding unplanned breaks in production caused by its catastrophic failure [5,6,7,8]. On the other hand, there is requirement of possible the best machining efficiency which results in reducing production costs [9,10].…”

Section: Introductionmentioning

confidence: 99%

The Possibility of Applying Acoustic Emission Method to Optimize Determination of Milling Parameters

Dudzik

2020

Wseas Transactions on Systems and Control

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Nowadays acoustic emission (AE) method is used in many fields of science, including in thediagnosis and monitoring of machining processes such as turning, grinding, milling, etc. Monitoring of millingprocess allows to ensure stable conditions of treatment. Stable conditions of milling process have a great impacton the quality of the surface. There are different methods used for monitoring machining processes, i.e.dynamometer methods, thermography, vibrations measurement, acoustic emission, etc. The research wascarried out on a universal FUW3157 III milling machine using end mills made of HSS. Tools were in differentstages of wear. The research was carried out at constant rotational speed and variable other cutting parameters,i.e. feed, depth of cut. Milling process was performed on a sheet made of EN AW-7020 aluminium alloy. Themilling process was monitored by an acoustic emission set made by Physical Acoustics Corporation (PAC).The PAC system consists of: preamplifier USB AE Node, type 1283 with bandpass 20 kHz – 1 MHz, AE signalmeasurement sensor type VS 150M, with a frequency range 100 – 450 kHz, computer with AE Win for USBVersion E5.30 software for recording and analysing AE data. During the study, the acoustic emission signalsgenerated during milling process were recorded and then chosen parameters were analyzed e. g.: amplitude,number of events - hits, the effective value of the signal (RMS). The study can be the basis for the use ofacoustic emission method for monitoring milling process and determining the parameters to ensure stableconditions of that process and the same to obtain a high quality surface

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Experimental study of tool life transition and wear monitoring in turning operation using a hybrid method based on wavelet multi-resolution analysis and empirical mode decomposition

Cited by 34 publications

References 22 publications

The Possibility of Applying Acoustic Emission and Dynamometric Methods for Monitoring the Turning Process

The Possibility of Applying Acoustic Emission and Dynamometric Methods for Monitoring the Turning Process

Assessing MMA Welding Process Stability Using Machine Vision-Based Arc Features Tracking System

The Possibility of Applying Acoustic Emission Method to Optimize Determination of Milling Parameters

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