Compilation of drilling load spectrum based on the characteristics of drilling force

Jin, Tongtong; Yan, Chuliang; Guo, Jinyan; Chen, Chuanhai; Zhu, Dong

doi:10.1007/s00170-022-08977-9

Cited by 4 publications

(3 citation statements)

References 25 publications

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“…Currently, load spectrum extrapolation methods can be primarily categorized into three main approaches: parametric extrapolation, nonparametric extrapolation, and timedomain extrapolation [11,12]. Both parametric and nonparametric methods rely on statistical rainflow matrices [13].…”

Section: Load Extrapolationmentioning

confidence: 99%

A Novel Load Extrapolation Method for Multiple Non-Stationary Loads on the Drill Pipe of a Rotary Rig

Wang,

Zhang,

Zhang

et al. 2024

Machines

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The drill pipe of a rotary rig is subject to the dynamic influence of non-stationary loads, including rotation torque and applied force. In order to address the challenge of simultaneously extrapolating multiple non-stationary loads, a novel extrapolation framework is proposed. This framework utilizes rainflow counting to obtain mean and amplitude sequences of the loads. The extreme values of the amplitude sequence are fitted using the Generalized Pareto Distribution (GPD), while the median values are fitted using the Double Kernel Density Estimation (DKDE). By extrapolating the Inverse Cumulative Distribution Function (ICDF) based on the fitted distribution, a new amplitude sequence can be derived. The combination of this extrapolated amplitude sequence with the original mean sequence forms a new load spectrum. The results of applying the proposed extrapolation method to the drill pipe of a rotary rig demonstrate the ability of the method to yield conservative extrapolation results and accurately capture the variations in damage under the original working conditions.

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Section: Load Extrapolationmentioning

confidence: 99%

A Novel Load Extrapolation Method for Multiple Non-Stationary Loads on the Drill Pipe of a Rotary Rig

Wang,

Zhang,

Zhang

et al. 2024

Machines

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“…Extensive research has shown that there are several different methods of torque extrapolation and their applications in various fields. The torque of the machining center 15 and drilling pipe 16 were extrapolated by the parametric method, and the time-domain approach extrapolated the torque of tractor power take-off. 17 However, these methods lack accuracy in the fitted distribution or consider only extreme loads.…”

Section: Introductionmentioning

confidence: 99%

An extrapolation framework for torque spectrum of excavator internal combustion engine via bivariate diffusion-based kernel density estimation

Shen

Wang

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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The torque extrapolation of the excavator internal combustion engine (ICE) is unknown and challenging. In this paper, an extrapolation framework for ICE torque of excavator is proposed. Data pre-processing, distribution estimation, load extrapolation, and damage evaluation are included in the framework. In estimating measurements, bivariate diffusion-based kernel density estimation is used to obtain the probability density. The cumulative cycle frequency and pseudo damage are compared with the results obtained by the other extrapolation methods. The results show that the proposed method can realize reasonable extrapolation. This extrapolation process can provide a reference for other engineering equipment in cyclic operation.

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“…The operation of a hole machining tool is a unique process different to any other by the prevailing axial force on the structure [1][2][3]. As a result, this opens up a great opportunity for the technique of sharpening the working surfaces of the drill.…”

Section: Introductionmentioning

confidence: 99%

New image processing algorithm to control the accuracy of sharpening drills

Pivkin

Гречишников

Ershov

et al. 2022

Emerging Imaging and Sensing Technologies for Security and Defence VII

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The geometric parameters of sharpening the rake surface are very important for the efficient use of the drill. Therefore, it is important to know the correct sharpening angle of the drill in the radial direction. This is especially important at the stage of regrinding the drill, due to the incorrect installation of the drill into the fixture. In this paper, a new image processing algorithm is proposed that allows you to set indicators and factors that determine the correct choice of the angular position of the drill after regrinding. This algorithm can be of great industrial use due to the simplicity of implementation and minimization of the necessary equipment for setting up the measuring station. The presented model has an important application value and differs from the existing ones in that it can be applied for regrinding of drills with curvilinear cutting edges. This advantage is achieved by using a simpler construction of the drill’s flank surfaces. The proposed design ensures a rational distribution of the clearance angle value along the cutting part regardless of the original shape of the flank surface before the regrinding. Taking into account the limitations of the image processing algorithm and the theoretical model of the cutting part of a tri-flute drill, a rational ratio of the rake and clearance angles obtained by simulating the edge movement in cutting process. This approach allows a radical revision of the traditional recommendations for regrinding process of tri-flute drills. This is becomes possible to solve problems associated with regrinding drills with involute and multi-level flat flank surface. However, the validity of our work still needs to be carefully checked.

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Compilation of drilling load spectrum based on the characteristics of drilling force

Cited by 4 publications

References 25 publications

A Novel Load Extrapolation Method for Multiple Non-Stationary Loads on the Drill Pipe of a Rotary Rig

A Novel Load Extrapolation Method for Multiple Non-Stationary Loads on the Drill Pipe of a Rotary Rig

An extrapolation framework for torque spectrum of excavator internal combustion engine via bivariate diffusion-based kernel density estimation

New image processing algorithm to control the accuracy of sharpening drills

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