Article
Engineering, Mechanical
Jinhui Wu, Dequan Zhang, Chao Jiang, Xu Han, Qing Li
Summary: The proposed rotational sparse grid (R-SPGR) method aims to enhance accuracy and efficiency in statistical moment evaluation and structural reliability analysis. By optimizing the rotational angle based on discrepancy between calculated marginal moments and exact values, the R-SPGR nodes capture more information of the exact probability distribution for accurate statistical moment calculation.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Engineering, Mechanical
Peng Huang, Hong-Zhong Huang, Yan-Feng Li, He Li
Summary: This study proposes a new method for positioning accuracy reliability analysis based on differential kinematics and saddle-point approximation, which is demonstrated to outperform existing methods in terms of accuracy and efficiency through comparative analysis.
MECHANISM AND MACHINE THEORY
(2021)
Article
Automation & Control Systems
Xi-Nong En, Yi-Min Zhang, Xian-Zhen Huang
Summary: This paper investigates the chatter stability and reliability of a turning tool system. It establishes a dynamic model and a chatter stability model, and verifies the accuracy of the models using experimental data. Additionally, it proposes an efficient method for solving the high nonlinear reliability problem and demonstrates its feasibility and effectiveness through experiments.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Automation & Control Systems
Xi-Nong En, Yi-Min Zhang, Xian-Zhen Huang
Summary: Turning is a common cutting method in metal machining, but chatter caused by self-excited vibration can occur. It is necessary to analyze the chatter stability and reliability of the turning tool system to predict and prevent chatter. This paper establishes dynamic and chatter stability models, conducts tests to determine dynamic parameters, considers parameter randomness, and analyzes their distributions and characteristics. Furthermore, a chatter reliability model is established using an efficient method for solving the high nonlinear reliability problem.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Engineering, Industrial
Lochana K. Palayangoda, Hon Keung Tony Ng
Summary: The paper focuses on developing semiparametric and nonparametric approaches to model bivariate degradation processes. Various methods are proposed to estimate the first-passage time distribution of dependence bivariate degradation data, using saddlepoint approximation and bootstrap methods for empirical estimation of marginal FPT distributions, and empirical copula for nonparametric estimation of joint distribution. Monte-Carlo simulation study demonstrates the effectiveness and robustness of the proposed approaches, with a numerical example provided to illustrate the methodologies.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Engineering, Multidisciplinary
Rui Li, Ning Ding, Yang Zhao, He Liu
Summary: This paper studied the real-time compensation method of robot trajectory error using laser tracker to measure the end position of the robot in real-time, in order to meet the requirements of high positioning accuracy and trajectory accuracy in high-precision operation. The continuous dynamic time warping method was used to determine the position error of the robot trajectory at each moment, and the PID parameter tuning technology based on gray analysis was researched to obtain a real-time compensation method. The compensation value was fed back to the robot for motion compensation in real-time through KUKA RSI. Finally, the influence of compensation parameters and period was analyzed, and error compensation experiments for positioning, linear trajectory, and arc trajectory were carried out. After compensation, the absolute positioning error of the robot was less than 0.06 mm and the trajectory position error was less than 0.15 mm, greatly improving the position accuracy of the robot.
Article
Automation & Control Systems
Helmut Harbrecht, Ilja Kalmykov
Summary: The paper investigates the sparse grid approximation of the Riccati operator P in closed loop parabolic control problems, focusing on linear quadratic regulator (LQR) problems. By expressing P in terms of an integral kernel p, the weak form of the algebraic Riccati equation leads to a nonlinear partial integro-differential equation for the kernel p.
SIAM JOURNAL ON CONTROL AND OPTIMIZATION
(2021)
Article
Mathematics, Applied
Byeongseon Jeong, Scott N. Kersey, Jungho Yoon
Summary: This study introduces a new class of quasi-interpolation schemes for approximating multivariate functions on sparse grids, utilizing shifted kernels from one-dimensional radial basis functions. The schemes achieve high convergence order and reduce data requirements compared to full grid methods. Single-level and multilevel implementations show similar performance with reduced computation time, providing significantly better approximation rates than existing methods.
SIAM JOURNAL ON SCIENTIFIC COMPUTING
(2021)
Article
Computer Science, Interdisciplinary Applications
Shuai Li, Zhencai Zhu, Hao Lu, Gang Shen
Summary: This paper presents a dynamic reliability model of scraper chains based on fretting wear process and proposes a reasonable structural optimization method. The correlation between wear and dynamic tension of scraper conveyor is observed, and the scraper chain's reliability estimation using TMSA method with incomplete probability information is discussed. The innovative aspect lies in establishing a physical model of scraper chain wear based on the dynamic analysis of scraper conveyor, and conducting time-dependent reliability and optimal design of scraper chains.
ENGINEERING COMPUTATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Haibo Liu, Ming Chen, Chong Du, Jiachang Tang, Chunming Fu, Guilin She
Summary: A copula-based uncertainty propagation method is proposed to accurately perform uncertainty propagation analysis with correlated parametric probability-boxes.
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
(2021)
Article
Mathematics
Carlos Llopis-Albert, Francisco Rubio, Francisco Valero
Summary: This research aims to design an efficient algorithm for multi-objective optimization in autonomous industrial systems to minimize task time and costs, improve productivity, and enhance performance and reliability by modeling industrial robots, providing collision-free trajectories, and using adaptive fuzzy sliding mode control. Results showed enhanced stability and robustness, overcoming limitations of traditional PID controllers, and analyzing trade-offs between economic issues and optimal time trajectories using Pareto fronts.
Article
Materials Science, Multidisciplinary
Xianzhen Huang, Chunmei Lv, Changyou Li, Yimin Zhang
Summary: This paper examines the reliability analysis of structures with multiple failure modes using a genetic memetic animal migration optimization algorithm for detecting optimum points, multi-point first-order reliability method for estimating failure probabilities, and saddlepoint approximation based second-order reliability method for system reliability analysis to enhance system reliability prediction accuracy.
MECHANICS OF ADVANCED MATERIALS AND STRUCTURES
(2022)
Article
Engineering, Civil
Xinpeng Wei, Daoru Han, Xiaoping Du
Summary: An accurate method is proposed to evaluate high-dimensional normal probabilities by first converting them into the cumulative distribution function of the extreme value and then employing the series expansion method for approximation. Experimental results show that the proposed method is generally more accurate and robust compared to the widely used methods.
Article
Computer Science, Information Systems
Shintaro Iwamura, Yoshiki Mizukami, Takahiro Endo, Fumitoshi Matsuno
Summary: An efficient optimization method for automating cable path design for industrial robotic arms is proposed, which reduces computation time and satisfies stress constraints.
Article
Automation & Control Systems
Henghua Shen, Wen-Fang Xie, Jianyu Tang, Tao Zhou
Summary: In this article, a novel manipulability-based optimal rapidly exploring random tree (RRT*) path planning strategy is proposed for industrial robot manipulators. The strategy imposes two constraints, path length and manipulability measure, when sampling in the search space to find the minimal-cost path connecting the start and goal points. The proposed path planning methods are demonstrated to be efficient through simulation analysis and experimental results of a six-degree-of-freedom FANUC-M-20iA industrial robot.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Meide Yang, Dequan Zhang, Xu Han
Summary: An enriched single-loop approach based on enhanced advanced mean value (ESLA-EAMV) is proposed to improve the convergence performance of the original single-loop approach (SLA) for complex nonlinear reliability-based design optimization (RBDO) problems.
ENGINEERING WITH COMPUTERS
(2022)
Article
Engineering, Mechanical
Dequan Zhang, Yunfei Liang, Lixiong Cao, Jie Liu, Xu Han
Summary: An efficient reliability analysis method based on the active learning Kriging model is proposed to improve the practicality of evidence theory in engineering structures. The method establishes a Kriging model through identifying sample points and solving univariate root-finding problems, efficiently deriving belief and plausibility measures.
JOURNAL OF MECHANICAL DESIGN
(2022)
Article
Engineering, Multidisciplinary
Meide Yang, Dequan Zhang, Fang Wang, Xu Han
Summary: This study proposes an efficient local adaptive Kriging approximation method (LAKAM-SLS) to enhance the computational efficiency of Kriging-based RBDO methods. By using Kriging models to replace objective and constraint functions, and developing two criteria to determine their active status, efficient calculations for complex RBDO problems are achieved. Experimental results show that the proposed method substantially reduces computational expenses.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Mechanical
Jinhui Wu, Dequan Zhang, Xu Han
Summary: This study proposes an efficient computational method for reliability sensitivity analysis, achieving high accuracy and efficiency. The method utilizes the LM iterative algorithm to calculate coordinates of points on the limit state function and establishes mapping relations using RBFNN. It successfully screens failure samples from the MCS sample set and calculates reliability sensitivity and failure probability.
JOURNAL OF MECHANICAL DESIGN
(2022)
Article
Computer Science, Interdisciplinary Applications
Dequan Zhang, Jingke Zhang, Meide Yang, Rong Wang, Zeping Wu
Summary: This study addresses the inefficiency of the finite step length (FSL) method in dealing with complex nonlinear problems and proposes an enhanced finite step length (EFSL) method, which is applied to reliability-based design optimization (RBDO). By introducing an iterative control criterion and a comprehensive step length adjustment formula, the EFSL method achieves fast convergence for limit state functions with varying degrees of nonlinearity. The proposed method is combined with the double loop method (DLM) to improve efficiency and robustness in solving complex RBDO problems.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Engineering, Multidisciplinary
Dequan Zhang, Shuoshuo Shen, Chao Jiang, Xu Han, Qing Li
Summary: This study proposes a new moment-based method for reliability analysis of complex mechanical systems, which can effectively handle multivariate correlations and achieve a balance between statistical moments and probability distribution evaluations.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Mechanical
Lixiong Cao, Jie Liu, Jinhe Zhang, Chao Jiang, Dequan Zhang
Summary: In this study, a reliability analysis method based on evidence theory is proposed to analyze the influence of uncertainties in modeling parameters on the positioning accuracy of robotic end effector. A generalized evidence theory model based on parallelotope frame is developed to quantify epistemic uncertainty and correlation of modeling parameters. An efficient space affine collocation method is further proposed to overcome the contradiction between analysis efficiency and accuracy for industrial robot positioning. A six degrees-of-freedom industrial robot is showcased to demonstrate the effectiveness and advantages of the proposed method.
JOURNAL OF MECHANICAL DESIGN
(2023)
Article
Acoustics
Dequan Zhang, Xing-ao Li, Meide Yang, Fang Wang, Xu Han
Summary: Vibration analysis remains a challenge in the industry due to the persistent problem of vibration in rotate vector (RV) reducers, which affects transmission accuracy and service life. This study proposes a non-random vibration analysis method for RV reducers that overcomes the need for a significant amount of experimental data. It introduces an interval process model to establish the non-random vibration analysis model and combines deterministic vibration analysis with interval process theory to propose the non-random vibration analysis method. The method is exemplified with a RV-20E reducer and compared with Monte Carlo simulation, showing efficient evaluation of core component vibration under uncertain excitation while complying with specific design guidance.
JOURNAL OF SOUND AND VIBRATION
(2023)
Article
Engineering, Multidisciplinary
Guosheng Li, Jiawei Yang, Zeping Wu, Weihua Zhang, Patrick Okolo, Dequan Zhang
Summary: This article proposes a sequential recursive evolution Latin hypercube design (RELHD) method to improve the computational efficiency and space-filling performance of LHD using a permutation inheritance algorithm and a recursive split algorithm. Numerical experiments show that RELHD is more efficient than ESE in dealing with complex problems with high dimensions and large samples.
ENGINEERING OPTIMIZATION
(2022)
Article
Engineering, Mechanical
Dequan Zhang, Zida Zhao, Heng Ouyang, Zeping Wu, Xu Han
Summary: This paper presents an efficient reliability analysis method using an improved radial basis function neural network (RBFNN) to enhance the accuracy and efficiency of structural reliability analysis. The proposed method improves the RBFNN by transferring the Latin hypercube sampling (LHS) center from the mean values of random variables to the most probable point (MPP) during the sampling step. The optimized RBFNN model is evaluated using the cross-validation method and Monte Carlo simulation (MCS) for reliability analysis, demonstrating its higher accuracy and efficiency compared to other methods.
JOURNAL OF MECHANICAL DESIGN
(2023)
Article
Computer Science, Interdisciplinary Applications
Dequan Zhang, Junkai Jia, Zhonghao Han, Heng Ouyang, Jie Liu, Xu Han
Summary: In this study, a derivative lambda probability density function (lambda-PDF) is proposed for quantifying the uncertainties in structural uncertainty problems with nonconventional distributions. An efficient uncertainty propagation approach based on the improved derivative lambda-PDF and dimension reduction method (DRM) is developed. The proposed method shows superiority over reference methods in terms of effectiveness and accuracy.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2023)
Article
Engineering, Multidisciplinary
Dapeng Wang, Dequan Zhang, Yuan Meng, Meide Yang, Chuizhou Meng, Xu Han, Qing Li
Summary: With the increasing complexity of engineering problems, traditional reliability analysis methods face challenges in terms of computational efficiency and accuracy. The Kriging model, a surrogate model, has been widely used in reliability analysis due to its advantages in computational efficiency and numerical accuracy. However, there are still significant issues with the Kriging model-assisted reliability analysis, such as the need for a large candidate sample pool and excessive local prediction accuracy. To address these issues, a new method called AK-HRn, which combines adaptive Kriging and n-hypersphere rings, is proposed in this study. The AK-HRn method demonstrates high efficiency and robustness in solving complex reliability analysis problems.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2023)
Review
Computer Science, Interdisciplinary Applications
Jiawei Yang, Zeping Wu, Zhixiang Wang, Dequan Zhang, Wenjie Wang, Qian Wen, Weihua Zhang
Summary: This paper proposes an enhanced anisotropic radial basis function (RBF) metamodeling algorithm by incorporating recursive evolution Latin hypercube design and fast K-fold cross-validation method. The proposed approach splits the large-sample design into smaller ones to reduce computation cost and naturally splits the training samples for cross-validation. The anisotropic RBF model is built by considering the sensitivity of the model to each dimension, and the hyperparameters are optimized using an evolutionary algorithm and fast K-fold cross-validation. Results show that the proposed method is competitive with other popular metamodel methods and can effectively handle practical engineering problems.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2023)
Article
Engineering, Multidisciplinary
Meide Yang, Dequan Zhang, Chao Jiang, Fang Wang, Xu Han
Summary: Time-dependent reliability-based design optimization has been the focus of intensive research in recent years. However, existing methods are too complex and computationally expensive for practical engineering applications. This study proposes an innovative solution framework that transforms the original problem into a more computationally efficient RBDO problem. The framework is demonstrated to have superior computational performance through numerical examples and engineering applications.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Industrial
Mateusz Oszczypala, Jakub Konwerski, Jaroslaw Ziolkowski, Jerzy Malachowski
Summary: This article discusses the issues related to the redundancy of k-out-of-n structures and proposes a probabilistic and simulation-based optimization method. The method was applied to real transport systems, demonstrating its effectiveness in reducing costs and improving system availability and performance.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Wencheng Huang, Haoran Li, Yanhui Yin, Zhi Zhang, Anhao Xie, Yin Zhang, Guo Cheng
Summary: Inspired by the theory of degree entropy, this study proposes a new node identification approach called Adjacency Information Entropy (AIE) to identify the importance of nodes in urban rail transit networks (URTN). Through numerical and real-world case studies, it is found that AIE can effectively identify important nodes and facilitate connections among non-adjacent nodes.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Hongyan Dui, Yaohui Lu, Liwei Chen
Summary: This paper discusses the four phases of the system life cycle and the different costs associated with each phase. It proposes an improvement importance method to optimize system reliability and analyzes the process of failure risk under limited resources.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Xian Zhao, Chen Wang, Siqi Wang
Summary: This paper proposes a new rebalancing strategy for balanced systems by switching standby components. Different switching rules are provided based on different balance conditions. The system reliability is derived using the finite Markov chain imbedding approach, and numerical examples and sensitivity analysis are presented for validation.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Fengyuan Jiang, Sheng Dong
Summary: Corrosion defects are the primary causes of pipeline burst failures. The traditional methodologies ignore the effects of random morphologies on failure behaviors, leading to deviations in remaining strength estimation and reliability analysis. To address this issue, an integrated methodology combining random field, non-linear finite element analysis, and Monte-Carlo Simulation was developed to describe the failure behaviors of pipelines with random defects.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Guoqing Cheng, Jiayi Shen, Fang Wang, Ling Li, Nan Yang
Summary: This paper investigates the optimal joint inspection and mission abort policies for a multi-component system with failure interaction. The proportional hazards model is used to characterize the effect of one component's deterioration on other components' hazard rates. The optimal policy is studied to minimize the expected total cost, and some structural properties of the optimal policy are obtained.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Hongyan Dui, Yaohui Lu, Shaomin Wu
Summary: A new resilience model is proposed in this paper for systems under competing risks, and related indices are introduced for evaluating the system's resilience. The model takes into account the degradation process, external shocks, and maintenance interactions of the system, and its effectiveness is demonstrated through a case study.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yang Li, Jun Xu
Summary: This paper proposes a translation model based on neural network for simulating non-Gaussian stochastic processes. By converting the target non-Gaussian power spectrum to the underlying Gaussian power spectrum, non-Gaussian samples can be generated.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yanyan Liu, Keping Li, Dongyang Yan
Summary: This paper proposes a new random walk method, CBDRWR, to analyze the potential risk of railway accidents. By combining accident causation network, we assign different restart probabilities to each node and improve the transition probabilities. In the case study, the proposed method effectively quantifies the potential risk and identifies key risk sources.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Nan Hai, Daqing Gong, Zixuan Dai
Summary: The current risk management of utility tunnel operation and maintenance is of low quality and efficiency. This study proposes a theoretical model and platform that offer effective decision support and improve the safety of utility tunnel operation and maintenance.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Tomoaki Nishino, Takuya Miyashita, Nobuhito Mori
Summary: A novel modeling methodology is proposed to simulate cascading disasters triggered by tsunamis considering uncertainties. The methodology focuses on tsunami-triggered oil spills and subsequent fires and quantitatively measures the fire hazard. It can help assess and improve risk reduction plans.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Mingjiang Xie, Yifei Wang, Jianli Zhao, Xianjun Pei, Tairui Zhang
Summary: This study investigates the effect of rockfall impact on the health management of pipelines with fatigue cracks and proposes a crack propagation prediction algorithm based on rockfall impact. Dynamic SIF values are obtained through finite element modeling and a method combining multilayer perceptron with Paris' law is used for accurate crack growth prediction. The method is valuable for decision making in pipeline reliability assessment and integrity management.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Saeed Jamalzadeh, Lily Mettenbrink, Kash Barker, Andres D. Gonzalez, Sridhar Radhakrishnan, Jonas Johansson, Elena Bessarabova
Summary: This study proposes an integrated epidemiological-optimization model to quantify the impacts of weaponized disinformation on transportation infrastructure and supply chains. Results show that disinformation targeted at transportation infrastructure can have wide-ranging impacts across different commodities.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Jiaxi Wang
Summary: This paper investigates the depot maintenance packet assignment and crew scheduling problem for high-speed trains. A mixed integer linear programming model is proposed, and computational experiments show the effectiveness and efficiency of the improved model compared to the baseline one.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yuxuan Tian, Xiaoshu Guan, Huabin Sun, Yuequan Bao
Summary: This paper proposes a DFMs searching algorithm based on the graph neural network (GNN) to improve computational efficiency and adaptively identify DFMs. The algorithm terminates prematurely when unable to identify new DFMs.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
