Reliability estimation for cutting tools based on logistic regression model using vibration signals

Chen, Baojia; Chen, Xuefeng; Li, Bing; He, Zhengjia

doi:10.1016/j.ymssp.2011.03.001

Cited by 136 publications

(72 citation statements)

References 26 publications

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“…Chen et al [18] have present on reliability estimation for cutting tools based on logistic regression model using vibration signals. The three steps of new reliability estimation approach for cutting tools are as follows.…”

Section: Introductionmentioning

confidence: 99%

Effects of Cutting Tool Parameters on Vibration

İnce

Asiltürk

2016

MATEC Web Conf.

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Abstract. This paper presents of the influence on vibration of Co28Cr6Mo medical alloy machined on a CNC lathe based on cutting parameters (rotational speed, feed rate, depth of cut and tool tip radius). The influences of cutting parameters have been presented in graphical form for understanding. To achieve the minimum vibration, the optimum values obtained for rpm, feed rate, depth of cut and tool tip radius were respectively, 318 rpm, 0.25 mm/rev, 0.9 mm and 0.8 mm. Maximum vibration has been revealed the values obtained for rpm, feed rate, depth of cut and tool tip radius were respectively, 636 rpm, 0.1 mm/rev, 0,5 mm and 0.8 mm.

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Section: Introductionmentioning

confidence: 99%

Effects of Cutting Tool Parameters on Vibration

İnce

Asiltürk

2016

MATEC Web Conf.

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“…Lin investigated the reliability and failure of face-milling tools when cutting stainless steel and the effect of different cutting conditions (cutting speed, feed, cutting depth) on the tool life [22]. Chen et al performed a reliability estimation for cutting tools based on a logistic regression model using vibration signals [5]. However, to the best of our knowledge, there have been no studies on the machining accuracy reliability of CNC machine tools.…”

Section: Reliability Analysismentioning

confidence: 99%

“…As shown in Eqs. (10) to (16), only 3 M , 5 M , 6 M and 7 M are related to the machining accuracy reliability of the machine center in Z-direction. As shown in Table 9, the failure probabilities of 3 M and 6 M are greater than the failure probabilities of 5 M and 7 M .…”

mentioning

confidence: 99%

A method to analyze the machining accuracy reliability sensitivity of machine tools based on Fast Markov Chain simulation

Cheng¹,

Sun²,

Zhao³

et al. 2016

EiN

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“…Shao et al [15] applied a modified single-channel blind sources separation (BSS) technique based on the wavelet transform and independent component analysis to separate the source signals related to a milling cutter and a spindle for the application of tool breakage monitoring. Chen et al [16] measure the tool vibrations, apply the wavelet transform and use a logistical correlation study of the wavelet energy is made to identify feature frequency bands that indicate tool wear. 3.…”

Section: Tool Condition Monitoringmentioning

confidence: 99%

Linear friction weld process monitoring of fixture cassette deformations using empirical mode decomposition

Bakker

Gibson

Wilson

et al. 2015

Mechanical Systems and Signal Processing

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Due to its inherent advantages, linear friction welding is a solid-state joining process of increasing importance to the aerospace, automotive, medical and power generation equipment industries. Tangential oscillations and forge stroke during the burn-off phase of the joining process introduce essential dynamic forces, which can also be detrimental to the welding process. Since burn-off is a critical phase in the manufacturing stage, process monitoring is fundamental for quality and stability control purposes. This study aims to improve workholding stability through the analysis of fixture cassette deformations. Methods and procedures for process monitoring are developed and implemented in a fail-or-pass assessment system for fixture cassette deformations during the burn-off phase. Additionally, the denoised signals are compared to results from previous production runs. The observed deformations as a consequence of the forces acting on the fixture cassette are measured directly during the welding process. Data on the linear friction-welding machine are acquired and de-noised using empirical mode decomposition, before the burn-off phase is extracted. This approach enables a direct, objective comparison of the signal features with trends from previous successful welds. The capacity of the whole process monitoring system is validated and demonstrated through the analysis of a large number of signals obtained from welding experiments.

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Reliability estimation for cutting tools based on logistic regression model using vibration signals

Cited by 136 publications

References 26 publications

Effects of Cutting Tool Parameters on Vibration

Effects of Cutting Tool Parameters on Vibration

A method to analyze the machining accuracy reliability sensitivity of machine tools based on Fast Markov Chain simulation

Linear friction weld process monitoring of fixture cassette deformations using empirical mode decomposition

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