Classification-driven model selection approach of genetic programming in modelling of turning process

Turning is a widely used machining process, but the process complexity and uncertainty lead to empirical modelling techniques being preferred over physics-based models for predicting the process performance. The literature reveals that empirical methods such as artificial neural networks (ANN), support vector regression (SVR), regression analysis and fuzzy logic have been extensively applied in the modelling of turning process. The present work introduces genetic programming (GP) for the modelling of turning, but it is observed that the optimal models selected from the GP population based on training and validation errors do not perform well on testing data (unseen samples). Selecting the best GP model from the population of models is therefore a vital step. In view of this, the classification-driven model selection approach of GP (C-GP) is proposed in this paper. In this methodology, potential classification techniques such as Bayes multinomial, partitioning and regression trees, classification and regression trees and decision trees are integrated with GP to predict the class (best or bad) of the GP models. The model that is classified as the “best” by the most number of classification techniques is selected, and its performance is compared to those from ANN and SVR. It is found that the C-GP model has accuracy on par with ANN and gives satisfactory performance on testing data.     

沙生灌木纤维在沥青混和料中的应用

通过对掺加沙生灌木纤维沥青混合料进行研究,确定出沙生灌木纤维最佳掺量和最佳沥青用量,并系统分析了沙生灌木纤维增强沥青混合料的高温稳定性、低温抗裂性、水稳定性及耐疲劳性。研究结果表明,在沥青混合料中掺入沙生灌木纤维,可以显著提高沥青混合料高温抗车辙性和抵抗裂缝的能力,从而使沥青混合料具有良好的抗剪强度和抗拉强度;同时,由于沙生灌木纤维的掺入,使沥青混合料具有较强的抗水损坏能力与耐疲劳性能,从而延长了沥青路面的使用寿命。     

基于非线性连续疲劳损伤的再制造毛坯剩余寿命评估

在考虑裂纹闭合效应对疲劳损伤影响的情况下,对Chaboche提出的非线性连续疲劳累积损伤模型进行了修正,得到了疲劳累积损伤及再制造毛坯剩余寿命评估模型,并由对称循环拉压疲劳试验数据得出了修正模型的相关参数。通过二级加载(高低加载和低高加载)拉压疲劳试验对再制造毛坯剩余寿命评估模型进行了验证,结果表明模型计算值和试验值吻合良好,证明修正后的模型能够准确预测再制造毛坯的剩余寿命。     

应力场强法在多轴疲劳寿命估算中的应用

将预测疲劳寿命的方法－－应力场强法理论初步应用到单轴加载和多轴加载下的疲劳寿命估算。同时，对于单轴加载和多轴比例加载给出预测算例，并与其试验结果进行对比，结果表明应力场强法是一种较好的预测多轴疲劳寿命的方法。     

垂尾与机身连接接头拉伸角盒疲劳寿命分析

为了更好地观测垂尾与机身连接接头拉伸角盒的疲劳裂纹产生、扩展,设计出更加符合要求的试验夹具,一般会在试验前对试件的破坏部位及寿命进行预估.本文采用工程法和有限元法相结合的手段对角盒结构进行了疲劳寿命预估分析,给出了其危险部位及预估寿命.此外,根据该盒段试验测量数据,对所预估的疲劳寿命进行了对比分析,阐明了所预估结果的可...     

A study on fatigue damage modeling using neural networks

Fatigue crack growth and life have been estimated based on established empirical equations. In this paper, an alternative method using artificial neural network (ANN) -based model developed to predict fatigue damages simultaneously. To learn and generalize the ANN, fatigue crack growth rate and life data were built up using in-plane bending fatigue test results. Single fracture mechanical parameter or nondestructive parameter can’t predict fatigue damage accurately but multiple fracture mechanical parameters or nondestructive parameters can. Existing fatigue damage modeling used this merit but limited real-time damage monitoring. Therefore, this study shows fatigue damage model using backpropagation neural networks on the basis of X-ray half breadth ratioB/B ₀ , fractal dimensionD _f and fracture mechanical parameters can estimate fatigue crack growth rateda/dN and cycle ratioN/N _f at the same time withinengineering limit error (5%).     

旋转压实方法在沥青混合料配合比设计中的试验研究

分别采用马歇尔击实方法和旋转压实方法进行AC-13沥青混合料体积设计,并对两种方法得到的指标进行对比分析。结果表明,旋转压实方法所确定的最佳沥青用量比马歇尔击实方法所确定的最佳沥青用量明显降低,而且其动稳定度（次/mm）、冻融劈裂抗拉强度比、残留稳定度等路用性能都得到了很大的提高。     

基于改进BP神经网络的焦炭塔热机械疲劳剩余寿命预测

焦炭塔热机械疲劳剩余寿命的分析对于保证焦炭塔的正常运行、防止事故的发生有着十分重要的意义。结合人工神经网络技术,提出了根据有限的材料热机械疲劳试验结果,用改进的BP神经网络预测焦炭塔热机械疲劳剩余寿命的方法,编制了相应的程序,并在实际应用中证明了此方法的有效性。这为研究焦炭塔热机械疲劳剩余寿命提供了一种新的方法。     

Reevaluation of Rolling Element Bearing Load-Life Equation Based on Fatigue Endurance Data

The load-life exponents used in the modified life rating equation for rolling element bearings were determined by statistical analysis of the experimental data generated in the 1940s, following Lundberg and Palmgren's seminal work. Based on fracture mechanics arguments, the fatigue life is known to be inversely proportional to the square root of the size of the nonmetallic inclusions. However, modern high-performance vacuum induction melt–vacuum arc remelt (VIMVAR) bearing steels are clean and nonmetallic inclusions are no longer the weak link. Fatigue life predictions (L₁₀ life) for modern bearings using the modified load-life relations greatly underpredict observed life. Hence, there is a need to update parameters of these equations using more recent life data. Based on the endurance data reported in Harris and McCool (1), validation analysis of the modified life rating equation was performed to reevaluate the values of load-life exponent for both ball and cylindrical roller bearings. The results from this study indicate that the load-life exponent for ball bearings should be 4.1, instead of 3, and for roller bearings it should be 5.5, instead of 3.33. Bearing L₁₀ life calculated using the corrected load-life exponents values shows better agreement with observed life. Details of the sampling technique used for reducing epistemic uncertainty in experimental data and the process of statistical reevaluation using Bayesian updating are discussed in detail. The accuracy of reevaluated results is presented using logarithmic plots of the ratio of predicted to actual fatigue lives for all data samples.     

Multiaxial stress-strain modeling and effect of additional hardening due to nonproportional loading

Most engineering components are subjected to multiaxial rather than uniaxial cyclic loading, which causes multiaxial fatigue. The pre-requisite to predict the fatigue life of such components is to determine the multiaxial stressstrain relationship. In this paper the multiaxial cyclic stress-strain model under proportional loading is derived using the modified power law stress-strain relationship. The equivalent strain amplitude consisted of the normal strain excursion and maximum shear strain amplitude is used in the proportional model to include the additional hardening effect due to nonproportional loading. Therefore a new multiaxial cyclic stress-strain relationship is devised for out of phase nonproportional loading. The model is applied to the nonproportional loading case and the results are compared with the other researchers’ experimental data published in the literature, which are in a reasonable agreement with the experimental data. The relationship presented here is convenient for the engineering applications.     

基于多重因素的滚动轴承寿命计算新方法

基于L-P轴承寿命理论,对当前滚动轴承主要的寿命预测模型进行了定性分析。通过经验公式整理、试验数据总结和图形数据处理等方法,重点研究失效概率系数、材料系数、润滑系数、负荷系数、温度系数和清洁系数对轴承疲劳寿命的影响,并建立了多重因素作用下轴承寿命预估模型。基于此模型,利用Matlab和VB的混合编程,开发了轴承疲劳寿命图谱软件,实现了轴承寿命与影响因素的四维可视化显示,并分析各修正系数对滚动轴承寿命的影响规律,确保轴承处于最佳工作状态。     

Fatigue life prediction of turbine blades based on a modified equivalent strain model

Mean stress is known to exert significant effects on fatigue life prediction. Although numerous adjustments have been developed to explain the influence of mean stress, only a few of such adjustments account for mean stress sensitivity. The Smith-Watson-Topper (SWT) model is one of the most widely used models that can provide satisfactory predictions. It is regarded as a case of a Walker model when the material parameter γ = 0.5. The Walker equation considers the mean stress effect and sensitivity, and it can generate accurate predictions in many fatigue programs. In this work, a modified model that accounts for the mean stress effect and sensitivity is proposed to estimate fatigue life. Several sets of experimental data are used to validate the applicability of the proposed model. The proposed model is also compared with the SWT model and the Morrow model. Results show that the proposed model yields more accurate predictions than the other models. The proposed model is applied to predict the fatigue life of a low-pressure turbine blade.     

一种基于参数影响的数据驱动下的疲劳寿命预测方法

金属构件的主要失效方式是在循环载荷作用下的疲劳破坏,因此金属构件的疲劳寿命预测对于保证结构安全性和可靠性十分必要。能量法是一种既能用于低周疲劳寿命预测,也能用于高周疲劳寿命预测的方法,其以寻找有效的显式能量损伤参量为手段,结合适当的损伤积累方式进行寿命评估。针对材料疲劳寿命预测问题,提出一个基于能量法和人工神经网络算法的疲劳寿命预测方法。为了达到反映不同加载路径影响的目的,从转动惯量的角度引入两个路径相关参量。使用基于应变控制的九种材料的疲劳试验数据对提出的神经网络模型进行训练、测试。结果显示模型对训练数据和测试数据均有良好的预测精度,并可对单轴加载、多轴加载、高周疲劳和低周疲劳寿命进行有效预测,表明本模型在多轴疲劳寿命预测方面具有较广泛的适用性。     

LCF behavior and life prediction method of a single crystal nickel-based superalloy at high temperature

Low cycle fatigue tests were conducted on the single crystal nickel-based superalloy, DD6, with different crystallographic orientations (i.e., [001], [011], and [111]) and strain dwell types (i.e., tensile, compressive, and balanced types) at a certain high temperature. Given the material anisotropy and mean stress, both orientation factor and stress range were introduced to the Smith, Watson, and Topper (SWT) stress model to predict the fatigue life. Experimental results indicated that the fatigue properties of DD6 depend on both crystallographic orientation and loading types. The fatigue life of the tensile, compressive, and balanced strain dwell tests are shorter than those of continuous cycling tests without strain dwell because of the important creep effect. The predicted results of the proposed modified SWT stress method agree well with the experimental data.     

铝合金压铸模具热疲劳寿命试验研究

压铸模具是压铸的关键部件之一,其经受周期性的加热与冷却,易产生热疲劳。针对这种现象,研究压铸模具热疲劳的过程,不同工艺对热疲劳寿命的影响规律,探索预测压铸模具热疲劳寿命的方法。研究开发自约束冷热疲劳方法的热疲劳试验机,试样在铝液中加热,在脱模剂中冷却,试样内部通冷却水冷却,实现在压铸条件下的模具热疲劳试验。采用开发的热疲劳试验机对H13钢试样进行热疲劳寿命试验研究,在试验过程中测量试样的温度变化,每隔3 000～4 000次测量残余应力,观察裂纹,经过几万次的循环后可以得到应力变化曲线和基于温差的模具热疲劳寿命曲线。研究水冷对试样的温度、应力、裂纹以及热疲劳寿命的影响。同时,针对试验过程进行传热数值模拟,得到不同工艺条件下的模具温差。试验和数值模拟相结合讨论如何提高模具的热疲劳寿命。     

Rolling element bearings absolute life prediction using modal analysis

In this paper, the authors introduce an experimental procedure for predicting the fatigue life of each individual rolling element bearing separately using vibration modal analysis. The experimental procedure was developed based on a statistical analysis. A statistical analysis was performed to find an empirical model that correlates the dynamic load capacity of rolling bearings to their dynamic characteristics (Natural frequencies and damping). These dynamic characteristics are obtained from the frequency response function of each individual bearing that results from vibration modal analysis. A modified formula to the already known Lundberg-Palmgren life formula is proposed for rolling element bearings. Given the modified formula, one can predict the fatigue life of each individual rolling element bearing based on its dynamic characteristics. The paper compares the results from the modified formula with those from Lundberg-Palmgren formula. The modified formula provides an accurate prediction for the fatigue life of each individual bearing based on its dynamic characteristics. The experimental validation of the modified formula is considered for future work. Therefore, it can be used in various applications of rolling element bearings in machinery systems.     

On modeling of tool wear using sensor fusion and polynomial classifiers

With increased global competition, the manufacturing sector is vigorously working on enhancing the efficiency of manufacturing processes in terms of cost, quality, and environmental impact. This work presents a novel approach to model and predict cutting tool wear using statistical signal analysis, pattern recognition, and sensor fusion. The data are acquired from two sources: an acoustic emission sensor (AE) and a tool post dynamometer. The pattern recognition used here is based on two methods: Artificial Neural Networks (ANN) and Polynomial Classifiers (PC). Cutting tool wear values predicted by neural network (ANN) and polynomial classifiers (PC) are compared. For the case study presented, PC proved to significantly reduce the required training time compared to that required by an ANN without compromising the prediction accuracy. The predicted results compared well with the measured tool wear values.     

活塞销疲劳寿命预测的研究

疲劳破坏是活塞销的主要失效形式。对活塞销进行了载荷分析、利用APDL语言建立了有限元分析模型。理论计算了活塞销的疲劳安全系数。基于有限元结果结合Goodman单轴、Sinse多轴修正的名义应力算法,计算预测了活塞销的疲劳寿命。进一步利用FE-SEFE软件进行了单轴、多轴两种方法的疲劳寿命预测,验证该活塞销满足疲劳设计要求,理论验证了FE-SEFE软件在预测高周疲劳寿命的可行性。