Time domain load extrapolation method for CNC machine tools based on GRA-POT model

He, Jialong; Zhao, Xinyue; Li, Guofa; Chen, Chuanhai; Yang, Zhaojun; Hu, Liang; Zhang, Xinge

doi:10.1007/s00170-019-03774-3

Cited by 17 publications

(6 citation statements)

References 19 publications

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“…A computer numerical control machine tool load extrapolation method based on the GRA-POT model (Gray relational analysis-peak over threshold mode) is proposed, which can obtain a POT extrapolation model with high fitting accuracy. In addition, the accuracy of the load spectrum of CNC (computerized numerical control) machine tools is improved [8]. Yang et al studied the time-domain extrapolation method of tractor drive shaft load under static working conditions and proposed a time-domain extrapolation method of tractor drive shaft load based on the MCMC-POT (Markov chain Monte Carlo-peak over threshold) model [9].…”

Section: Introductionmentioning

confidence: 99%

“…(2) Using the averaging method to 𝑓𝑓 ̂(𝑥𝑥 𝑖𝑖 ) perform dimensionless processing on the load sample data 𝑓𝑓(𝑥𝑥 𝑖𝑖 ) and fitting data, as shown in (8). Grey correlation analysis is a common threshold selection method.…”

mentioning

confidence: 99%

“…(2) Using the averaging method to f (x i ) perform dimensionless processing on the load sample data f (x i ) and fitting data, as shown in (8).…”

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confidence: 99%

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Extrapolation of Tractor Traction Resistance Load Spectrum and Compilation of Loading Spectrum Based on Optimal Threshold Selection Using a Genetic Algorithm

et al. 2023

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To obtain the load spectrum of the traction resistance of the three-point suspension device under tractor-plowing conditions, a load spectrum extrapolation method based on a genetic algorithm optimal threshold selection is proposed. This article first uses a pin force sensor to measure the plowing resistance of the tractor’s three-point suspension device under plowing conditions and preprocesses the collected load signal. Next, a genetic algorithm is introduced to select the threshold based on the Peak Over Threshold (POT) extremum extrapolation model. The Generalized Pareto Distribution (GPD) fits the extreme load distribution that exceeds the threshold range, generating new extreme points that follow the GPD distribution to replace the extreme points in the original data, achieving the extrapolation of the load spectrum. Finally, the loading spectrum that can be achieved on the test bench is obtained based on the miner fatigue theory and accelerated life theory. The results show that the upper threshold of the time-domain load data obtained by the genetic algorithm is 10.975 kN, and the grey correlation degree is 0.7249. The optimal lower threshold is 8.5455 kN, the grey correlation degree is 0.7722, and the fitting effect of the GPD distribution is good. The plowing operation was divided into five stages: plowing tool insertion, acceleration operation, constant speed operation, deceleration operation, and plowing tool extraction. A traction resistance loading spectrum that can be achieved on the test bench was developed. The load spectrum extrapolation method based on the genetic algorithm optimal threshold selection can improve the accuracy of threshold selection and achieve the extrapolation and reconstruction of the load spectrum. After processing the extrapolated load spectrum, it can be transformed into a load spectrum that can be recognized by the test bench.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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Extrapolation of Tractor Traction Resistance Load Spectrum and Compilation of Loading Spectrum Based on Optimal Threshold Selection Using a Genetic Algorithm

et al. 2023

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“…Wang [13] aimed at the periodic relationship between the transformation of cutting force and spindle speed in the cutting process of an NC machine tool; a BMM model was used for time-domain extrapolation. He [15] proposed a pot extrapolation method based on improved time-domain load expansion for the relatively stable cutting force load of NC machine tools in the process of constant speed cutting. When the load shows obvious periodicity and stability, the time-domain extrapolation method will have a good effect.…”

Section: Introductionmentioning

confidence: 99%

Compilation of Load Spectrum of PHEV Transmission Assembly and Its Simulation Application

Han

et al. 2022

Machines

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This paper presents a method for compiling the load spectrum of the transmission assembly of plug-in hybrid electric vehicles (PHEVs). Based on the analysis of the control strategy of the test vehicle, the power flow transmission route in the transmission assembly is different under different operation modes, so it is necessary to divide different load spectrum blocks according to the operation mode. Based on the big data survey of China’s national standard, it is determined that the typical working conditions are urban road working conditions, high-speed road working conditions, provincial road working conditions and poor road conditions. The mileage proportion of the various working conditions is 55:30:10:5, and the mileage of one cycle is 300 km. A total of three cycles are collected. After data processing and time-domain verification, based on the principle of maximum damage, the cycle with the largest pseudo damage is selected as the sample load data for load spectrum extrapolation. The rain flow counting method is used to count the sample load, and a two-dimensional kernel density estimation mathematical model with adaptive bandwidth is established to estimate the probability density function of the data. The extrapolated rain flow matrix is obtained through Monte Carlo simulation. The load spectrum of the two-dimensional rain flow matrix is transformed into a one-dimensional eight-stage program load spectrum by using a variable mean method, Goodman equation and equal damage principle theory. Finally, the fatigue life of the transmission assembly is simulated and calculated under the environment of Romax Designer simulation software. The two-dimensional kernel density estimation model with adaptive bandwidth is used to fit and extrapolate the load rain flow matrix of each hybrid mode of the PHEV, which solves the problem wherein the shape of the rain flow matrix of each hybrid mode of the hybrid electric vehicle is complex and difficult to fit. Finally, taking the after-sales maintenance data of this model from 2020 to the present as auxiliary proof, the failure components and the failure mileage life of the simulation test results are consistent with the results used by the actual users. This shows that the kernel density estimation model proposed in this paper can well fit the rain flow matrix of the PHEV load spectrum. The extrapolated load spectrum based on this model has high accuracy and authenticity. The method of compiling the load spectrum of the transmission assembly of a hybrid electric vehicle in this paper is effective.

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“…It shows the relationship between the load and the occurrence frequency or applied time [1]. Load spectrum can reflect the distribution law of random load, so it is widely used in reliability test of component structure [9,30], fatigue life prediction [5,8,10,31], reliability design [2,27], accelerated test [3] and other aspects. Compiling a scientific and reasonable load  Jialong He hejl@jlu.edu.cn  Guofa Li ligf@jlu.edu.cn spectrum of CNC machine tools can provide basic data for the reliability design, reliability tests and reliability evaluation of key components [23,24].…”

Section: Introductionmentioning

confidence: 99%

Compilation method of CNC lathe cutting force spectrum based on kernel density estimation of G-SCE

Wang

et al. 2021

Int J Adv Manuf Technol

Self Cite

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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. According to the measured dynamic cutting force, the KDE is used to establish the dynamic cutting force distribution of the CNC lathe. For the rule of thumb method (ROT) based on the mean integrated square error and the least squares cross-validation method (LCV) based on the integrated square error does not take into account the influence of different bandwidths on the goodness estimation and the smoothness of the estimated curve. The estimation accuracy test method based on multiple goodness-of-fit tests, and the smoothness test method based on the envelope curve are proposed. The entropy method is used to comprehensively calculate the estimated goodness index and the smoothness index to determine the optimal bandwidth. The case analysis shows that the method proposed can solve the problem of too large estimation error of parameter distribution for multimodal distribution. At the same time, it can better comprehensively evaluate the KDE under different bandwidths. In short, a new method of optimal bandwidth selection is proposed in the original method.

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Time domain load extrapolation method for CNC machine tools based on GRA-POT model

Cited by 17 publications

References 19 publications

Extrapolation of Tractor Traction Resistance Load Spectrum and Compilation of Loading Spectrum Based on Optimal Threshold Selection Using a Genetic Algorithm

Extrapolation of Tractor Traction Resistance Load Spectrum and Compilation of Loading Spectrum Based on Optimal Threshold Selection Using a Genetic Algorithm

Compilation of Load Spectrum of PHEV Transmission Assembly and Its Simulation Application

Compilation method of CNC lathe cutting force spectrum based on kernel density estimation of G-SCE

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