Chatter detection in milling processes using frequency-domain Rényi entropy

Tools with unequal uteless spacing (UFS) feature are used to cut different materials. The UFS tool and a traditional tool differ in terms of the angle between the two cutting edges. The UFS tool experiences smaller axial and radial cutting forces than the traditional tool so cutting vibration is reduced, tool life is increased and the surface roughness of the workpiece increases. This study uses the smaller hole diameter (D), spindle speed (N) and cutting uid concentration (C) for the central composite design (CCD). MINITAB statistical software is used for the second-order response surface modeling of the maximum thread lling rate (f) and the minimum torque (T) for micro-forming M1.2 mm taps using UFS on AL-7075 aluminum alloy. The analysis of variance (ANOVA) results for f and T show that D and C are the important parameters that affect f , and D, N and C signi cantly affect T. Compared with the predicted conditions, the errors in f and T for the experiment are 2.51% and 2.25%, respectively. This study shows that the two second-order mathematical models that are derived using CCD and the response surface method (RSM) feature good prediction accuracy.

Section: Methodsmentioning

confidence: 99%

Study on micro-forming taps with unequal fluteless spacing

Chen²,

Huang³

et al. 2023

“…Frequency domain methods are also utilized to obtain decomposition parameters, estimate frequency bands, detect chatter occurrence or validate a new chatter model, as seen in [73,88,119,162,218,332,333]. For instance, Afazov and Scrimieri [334] proposed a Digital Twin model for chatter in milling and utilized the FFT of measured signals for model validation.…”

Section: Frequency Domain Analysismentioning

confidence: 99%

“…Entropy features represent the signal randomness and complexity. Some of them have been reported for chatter detection, including permutation entropy (PE) [134,157], Rényi entropy (RE) [162], Sample entropy (SampEn) [133,142,186], approximate entropy (ApEn) [88,133,169,170,183] and dispersion entropy [151]. Tran et al [154] utilized fuzzy entropy for feature selection.…”

Section: Feature Generationmentioning

confidence: 99%

Chatter detection in milling processes—a review on signal processing and condition classification

Navarro-Devia

Chen

Dao

et al. 2023

Among the diverse challenges in machining processes, chatter has a significant detrimental effect on surface quality and tool life, and it is a major limitation factor in achieving higher material removal rate. Early detection of chatter occurrence is considered a key element in the milling process automation. Online detection of chatter onset has been continually investigated over several decades, along with the development of new signal processing and machining condition classification approaches. This paper presents a review of the literature on chatter detection in milling, providing a comprehensive analysis of the reported methods for sensing and testing parameter design, signal processing and various features proposed as chatter indicators. It discusses data-driven approaches, including the use of different techniques in the time–frequency domain, feature extraction, and machining condition classification. The review outlines the potential of using multiple sensors and information fusion with machine learning. To conclude, research trends, challenges and future perspectives are presented, with the recommendation to study the tool wear effects, and chatter detection at dissimilar milling conditions, while utilization of considerable large datasets—Big Data—under the Industry 4.0 framework and the development of machining Digital Twin capable of real-time chatter detection are considered as key enabling technologies for intelligent manufacturing.

“…The grayscale threshold is manually adjusted or automatically calculated (auto threshold). For this study, the Renyi Entropy algorithm is used to calculate all image areas for the tapped thread [14]. Particle analysis is used to calculate the thread area and the result is given in units of mm 2 .…”

Section: Binarizationmentioning

confidence: 99%

Optimization of tool geometric parameters for a small fluteless forming tap (FFT)

Jian

Hsu³

et al. 2022

A small blind internal thread (SBIT) is used to firmly fasten some functional components to the cover of 3C electronic products. The small internal thread is made in a blind hole using a fluteless forming tap (FFT) that does not produce chips. However, the four geometric parameters (tool width (W), tooth root diameter (D2), front-end diameter (Df) and tooth angle (θ)) for the FFT affect the thread filling rate (f) and the minimum torque (T) for the tapping process. This study reports a Box-Behnken design (BBD) using DEFORM-3D (finite element model) and MINITAB (regression analysis) software to tap 7075-T6 aluminum alloy using a small FFT to achieve a repeatable thread filling rate and minimum torque. The experimental results show that the BBD accurately predicts and simulate the thread filling rate for tapping 7075-T6 aluminum alloy. The modelling software and the experimental design for this study can be used to optimize the design of tools that are used in industrial production.