2021
DOI: 10.1007/s00170-021-07541-1
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Compilation method of CNC lathe cutting force spectrum based on kernel density estimation of G-SCE

Abstract: The cutting force spectrum of the CNC lathe is the basic data for the reliability design, reliability test and reliability evaluation of the CNC lathe and its components. Due to the complex and changeable turning conditions and different cutting processes, the cutting load presents multi-peak characteristic. In order to compile the CNC lathe cutting force spectrum accurately, a compilation method based on kernel density estimation (KDE) of goodnesssmoothness comprehensive evaluation (G-SCE) is proposed. Accord… Show more

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Cited by 12 publications
(3 citation statements)
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References 33 publications
(48 reference statements)
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“…The parametric method requires the frequency and level of extrapolation, 29 while the non-parametric approach extrapolates the load by Monte Carlo simulation. 3032 However, for the demands of the drill pipe load spectrum, none of the above extrapolation methods are applicable.…”
Section: Related Workmentioning
confidence: 99%
“…The parametric method requires the frequency and level of extrapolation, 29 while the non-parametric approach extrapolates the load by Monte Carlo simulation. 3032 However, for the demands of the drill pipe load spectrum, none of the above extrapolation methods are applicable.…”
Section: Related Workmentioning
confidence: 99%
“…Based on artificial neural networks, Ramirez IS [22] proposed a new method for signal processing, fault detection, and diagnosis that combines statistical analysis and advanced algorithms. In addition, Abid M [23] studied the oil pipeline flange connection surface and bolt connection of fastening optimization strategy. Ibai Coria [24] proposed a new optimization method for fastening of bolt sequence for ring joints.…”
Section: Introductionmentioning
confidence: 99%
“…At present, methods for monitoring and diagnosing condition of rotating machinery can be divided into two types: the modelbased approaches [2,3] and the data-driven approaches. The model-based approaches such as POS-SQP [4] and kernel density estimation [5] are widely used in recent years. The data-driven methods based on time-frequency analysis are also an effective tool for extracting mechanical health information from nonstationary signals [6].…”
Section: Introductionmentioning
confidence: 99%