Singularity Analysis of Cutting Force and Vibration for Tool Condition Monitoring in Milling

Zhou, Chang’an; Guo, Kai; Yang, Bin; Wang, Haijin; Sun, Jie; Lu, Laixiao

doi:10.1109/access.2019.2941287

Cited by 36 publications

(14 citation statements)

References 42 publications

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“…The selection of wavelet basis functions is critical for the singularity analysis of sensory signals. Zhou et al [24], [25] found the wavelet basis with two vanishing moments were the most appropriate wavelet to detect the singularities in the vibration signals of the milling process. And Gaussian wavelet can ensure the continuity of the modulus maxima line [18].…”

Section: Results and Discussion A He Estimation Proceduresmentioning

confidence: 99%

“…While calculating WTMMs, the samples dominated by noise would result in a large number of pseudo-WTMMs. And these pseudo-WTMMs would increase remarkably as the s reduces, this characteristic can be employed to remove these contaminations as a de-noising method [25].…”

Section: B Holder Exponentmentioning

confidence: 99%

“…Holder Exponent (HE), estimated from the cutting force to classify different tool statuses in micro-milling. Zhou et al [24], [25] studied the difference in adopting singularity analysis to estimate the cutting force and vibration of the milling process, and established a TCM approach with good performances. However, there are few researches on employing singularity features to establish tool tipping monitoring models published.…”

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confidence: 99%

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The Monitoring of Milling Tool Tipping by Estimating Holder Exponents of Vibration

et al. 2020

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The gradual tool wear is unavoidable in the machining process, it directly influences the surface integrity and dimensional tolerances of the components. The tool condition monitoring (TCM) systems have the capacity to make full use of the cutting potential of the cutting tools, which is of great significance for improving production efficiency and ensuring product quality. In milling titanium alloys, tool tipping is one of the main failure modes. Therefore, this study focuses on establishing a tool tipping monitoring approach for the milling process. The singularity analysis method based on wavelet transform was employed to characterize the variation of vibration waveforms quantitatively with the Holder Exponent (HE) index. The probability density distribution and statistical analysis were adopted to extract effective HE features from the HE indexes to correlate with the different tool conditions. The mutual information method was adopted to rank the discriminability of the HE statistical parameters. Then, several machine learning (ML) models were established with the screened HE features. Finally, the results of the experiments indicate that the Support Vector Machine (SVM) model has the highest classification accuracy and can provide practical guides on the tool changes.INDEX TERMS Tool tipping, titanium alloys, vibrations, Holder Exponents, support vector machine. I. INTRODUCTION

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Section: Results and Discussion A He Estimation Proceduresmentioning

confidence: 99%

Section: B Holder Exponentmentioning

confidence: 99%

mentioning

confidence: 99%

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The Monitoring of Milling Tool Tipping by Estimating Holder Exponents of Vibration

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“…Saini and Yu et al [3,4] sudied the influence of tool cutting performance on vibration problems for different materials. Zhou et al [5] presented an approach for systematic singularity analysis of cutting force and vibration in feature extraction. Li et al [6] developed a single-degree of freedom chatter model by taking the nonlinear hysteretic and exciting force into account.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Vibration Reduction Mechanism for Variable-pitch End Mills in Hardened Steel

Nie

Zheng

et al. 2021

Preprint

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The development of the machining technology is restricted by the problems of serious vibration and low system stability. The variable-pitch mill has certain vibration reduction property due to the unequal pitch angles. In this work, firstly, according to the features of the structure of the variable-pitch end mill, the cutting mechanism is analyzed, and a theoretical model of the dynamic cutting force is developed. Secondly, the cutting force coefficients of the model are determined based on the test of hardened steel for verifying the significance of the theoretical model. Then, the time-frequency characteristics and vibration reduction mechanism of variable-pitch mills are analyzed. The frequency characteristics of different types of pitch angle mills are also explored by the spectrum analysis. Finally, based on the energy and variance methods of the amplitude, the multi-objective optimization of the pitch angle is carried out, where the spectrum lines are found evenly distributed, and the optimal result is 80°-97°-100°-83°. For satisfying the machining requirements, the pitch angle of the variable-pitch end mill is reasonably selected to reduce the amplitude of the forced vibration, which can play an important role in reducing the vibration of the tool and improving its cutting stability.

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“…Cutting tool plays a vital role in the cutting process, whose abnormal changes directly affect the machining accuracy and workpiece surface quality [1]- [3]. Thus, monitoring the tool cutting conditions, such as cutting force [4], torque [5], vibration [6], and temperature [7], is becoming particularly important, and thus has recently aroused great concerns from both academia and industry.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Wireless Power and Data Transmission Over One Pair of Coils for Sensor-Integrated Rotating Cutter

Zhu

Tao

2020

IEEE Access

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Tool condition monitoring is becoming particularly important in the cutting process. More and more researchers start to integrate the sensors into the tool holder due to its convenient use and wide applicability. However, it is difficult to transmit out the condition data and supply stable power to the sensor-integrated systems through the traditional wired way as the tool holder is under high-speed rotation in milling or drilling process. In this paper, a novel simultaneous wireless power and data transfer system over one pair of coils for sensor-integrated rotating cutter is presented, and the eddy effect caused by the metal handle that impacts the system performance is solved with ferrite shielding. To transmit out the cutting condition data wirelessly, the synchronous detection and envelope detection technology are employed. Meanwhile, the synchronous rectification technology is adopted to improve the performance of the wireless power transfer. Eventually, the experimental platform has been set up and the cutting tests have also been carried out. The results show that the designed new wireless power and data transfer system over one pair of coils is stable and practical to track and transmit out the condition data of the rotating cutter. INDEX TERMS Tool condition monitoring, rotating cutter, simultaneous wireless power and data transfer, one pair of coils, ferrite shielding.

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Singularity Analysis of Cutting Force and Vibration for Tool Condition Monitoring in Milling

Cited by 36 publications

References 42 publications

The Monitoring of Milling Tool Tipping by Estimating Holder Exponents of Vibration

The Monitoring of Milling Tool Tipping by Estimating Holder Exponents of Vibration

Analysis of Vibration Reduction Mechanism for Variable-pitch End Mills in Hardened Steel

Simultaneous Wireless Power and Data Transmission Over One Pair of Coils for Sensor-Integrated Rotating Cutter

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