Based on Multi-Sensor Tool Steel Hard Turning Process Monitoring and Controlling

Wu, Fei; Wang, Xi; Zhong, Wei; Yu, Hui; Liu, Li Bing; Liao, Dong Ting

doi:10.4028/www.scientific.net/amr.108-111.549

Cited by 3 publications

(3 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Albers et al [ 30 ] on the basis on real time monitoring of AE proposed prediction of the product surface quality. Some researchers used another monitoring methods to achieve high quality and required surface roughness, i.e., Wu et al [ 31 ] used AE, vibration and temperature measurement. Mikołajczyk et al [ 32 ] propose an application of automatic detection of cutting edge wear on the basis of optical methods and artificial neural network in real-time monitoring systems.…”

Section: Introductionmentioning

confidence: 99%

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

Dudzik

Labuda

2020

Materials

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

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

Dudzik

Labuda

2020

Materials

View full text Add to dashboard Cite

show abstract

“…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

View full text Add to dashboard Cite

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

show abstract

“…/E，E31/E，E32/E，E33/E，E34/E，E35/E，E36/E，E37/E] (5) Vector T is a characteristic vector after normalization, which represents the proportion of energy of different frequency band of the entire energy[7].TemperatureSignals Analysis and Processing. According to temperature signals in different condition as shown in table 1, use db3 wavelet base function to decompose 15 layers wavelet.…”

mentioning

confidence: 99%

An Experimental Study on Electric Hot Milling for T10A Tool Steel

Chen

Wang

Liu

et al. 2011

AMM

View full text Add to dashboard Cite

This paper introduces a kind of electric hot milling method for T10A tool steel and analyses its feasibility. Collect temperature signals and vibration signals in the machining process by a set of signal acquisition system. Afterwards, process these signals by using wavelet transform and wavelet packet transform, compare and analyze them in different working conditions. The results of the study indicate that through comparison between dry milling and electric hot milling, the latter can be more effectively milling tool steel, and improve the cutting tool durability.

show abstract

Based on Multi-Sensor Tool Steel Hard Turning Process Monitoring and Controlling

Cited by 3 publications

References 4 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

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

An Experimental Study on Electric Hot Milling for T10A Tool Steel

Contact Info

Product

Resources

About