Whirling detection in deep hole drilling process based on multivariate synchrosqueezing transform of orthogonal dual-channel vibration signals

2022 ◽  
Vol 167 ◽  
pp. 108621
Author(s):  
Yue Si ◽  
Lingfei Kong ◽  
Jih-Hua Chin ◽  
Weichao Guo ◽  
Qilong Wang
Keyword(s):  
Hole Drilling ◽  
Drilling Process ◽  
Deep Hole ◽  
Vibration Signals ◽  
Deep Hole Drilling ◽  
Dual Channel ◽  
Synchrosqueezing Transform

scholarly journals Temperature monitoring in the subsurface during single lip deep hole drilling

2020 ◽  
Vol 87 (12) ◽  
pp. 757-767
Author(s):  
Robert Wegert ◽  
Vinzenz Guski ◽  
Hans-Christian Möhring ◽  
Siegfried Schmauder
Keyword(s):  
Cutting Parameters ◽  
Drill Hole ◽  
Machining Process ◽  
Hole Drilling ◽  
Drilling Process ◽  
Deep Hole ◽  
Machining Processes ◽  
Deep Hole Drilling ◽  
Feed Force ◽  
Cutting Zone

AbstractThe surface quality and the subsurface properties such as hardness, residual stresses and grain size of a drill hole are dependent on the cutting parameters of the single lip deep hole drilling process and therefore on the thermomechanical as-is state in the cutting zone and in the contact zone between the guide pads and the drill hole surface. In this contribution, the main objectives are the in-process measurement of the thermal as-is state in the subsurface of a drilling hole by means of thermocouples as well as the feed force and drilling torque evaluation. FE simulation results to verify the investigations and to predict the thermomechanical conditions in the cutting zone are presented as well. The work is part of an interdisciplinary research project in the framework of the priority program “Surface Conditioning in Machining Processes” (SPP 2086) of the German Research Foundation (DFG).This contribution provides an overview of the effects of cutting parameters, cooling lubrication and including wear on the thermal conditions in the subsurface and mechanical loads during this machining process. At first, a test set up for the in-process temperature measurement will be presented with the execution as well as the analysis of the resulting temperature, feed force and drilling torque during drilling a 42CrMo4 steel. Furthermore, the results of process simulations and the validation of this applied FE approach with measured quantities are presented.

scholarly journals Improved empirical wavelet denoising algorithm with application to whirling detection in deep hole drilling process

Procedia CIRP ◽  
2021 ◽  
Vol 104 ◽  
pp. 1924-1929
Author(s):  
Yue Si ◽  
Xuyang Li ◽  
Lingfei Kong ◽  
Jianming Zhen ◽  
Yan Li
Keyword(s):  
Wavelet Denoising ◽  
Hole Drilling ◽  
Drilling Process ◽  
Deep Hole ◽  
Deep Hole Drilling

The thermal modeling of deep-hole drilling process under MQL condition

2017 ◽  
Vol 29 ◽  
pp. 194-203 ◽  
Author(s):  
A.T. Kuzu ◽  
K. Rahimzadeh Berenji ◽  
B.C. Ekim ◽  
M. Bakkal
Keyword(s):  
Thermal Modeling ◽  
Hole Drilling ◽  
Drilling Process ◽  
Deep Hole ◽  
Deep Hole Drilling

scholarly journals 501 A Countermeasure Against a Rifling Mark Generating Phenomenon on BTA Deep Hole Drilling Process : Experimental Study

2011 ◽  
Vol 2011 (0) ◽  
pp. _501-1_-_501-7_
Author(s):  
Shotaro NAKAO ◽  
Kenichiro MATSUZAKI ◽  
Takahiro RYU ◽  
Atsuo SUEOKA ◽  
Kazuhisa OMURA
Keyword(s):  
Experimental Study ◽  
Hole Drilling ◽  
Drilling Process ◽  
Deep Hole ◽  
Deep Hole Drilling

1E2 Experimental Study on the Mechanism of Rifling Mark Generation in BTA Deep Hole Drilling Process

2014 ◽  
Vol 2014 (0) ◽  
pp. _1E2-1_-_1E2-2_
Author(s):  
Keita HIRASE ◽  
Takahiro RYU ◽  
Kenichiro MATSUZAKI ◽  
Keizo TSUKAMOTO ◽  
Katsushi FUJII ◽  
...  
Keyword(s):  
Experimental Study ◽  
Hole Drilling ◽  
Drilling Process ◽  
Deep Hole ◽  
Deep Hole Drilling

Modeling and Optimization of Machining Parameters Using Regression and Cuckoo Search in Deep Hole Drilling Process

2019 ◽  
Vol 892 ◽  
pp. 177-184 ◽  
Author(s):  
Azizah Mohamad ◽  
Azlan Mohd Zain ◽  
Noordin Mohd Yusof ◽  
Farhad Najarian ◽  
Razana Alwee ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Cuckoo Search ◽  
Experimental Result ◽  
Hole Drilling ◽  
Drilling Process ◽  
Machining Parameters ◽  
Deep Hole ◽  
Computing Technique ◽  
Deep Hole Drilling ◽  
Modeling And Optimization

This study presents the modeling and optimization of the machining parameters in deep hole drilling process using statistical and soft computing technique. Regression analysis is used for modeling and Cuckoo Search, CS algorithm is used for the optimization process. Design of Experiment (DoE), have been carried using a Full Factorial design with added centre point that comprises of machining parameters (feed rate (f), spindle speed (s), depth of hole (d) and minimum quantity lubrication, MQL (m)) and machining performance which is surface roughness, Ra. Next, the mathematical models (Multiple Linear Regression, MLR and 2-factor interaction, 2FI) are developed for the experimental results of Ra and Analysis of variance, ANOVA are used to check the significance of the models developed. The results showed that both of mathematical models (MLR and 2FI) have outperformed the minimum Ra value compared to the experimental result.

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