资源类型

期刊论文 543

会议视频 8

年份

2024 1

2023 38

2022 38

2021 47

2020 23

2019 32

2018 44

2017 43

2016 17

2015 21

2014 25

2013 13

2012 14

2011 20

2010 24

2009 19

2008 32

2007 27

2006 14

2005 9

展开 ︾

关键词

过程强化 6

优化 4

不确定性 3

人工智能 3

智能制造 3

DSM（设计结构矩阵） 2

三峡工程 2

催化剂 2

催化裂化 2

凝固过程 2

可视化仿真 2

层次分析法 2

废水 2

智能优化制造 2

机器学习 2

流程工业 2

绿色制造 2

绿色化工 2

过程模拟 2

展开 ︾

检索范围：

排序： 展示方式：

Inverse Gaussian process-based corrosion growth modeling and its application in the reliability analysis

Hao QIN, Shenwei ZHANG, Wenxing ZHOU

《结构与土木工程前沿（英文）》 2013年 第7卷 第3期   页码 276-287 doi: 10.1007/s11709-013-0207-9

摘要： This paper describes an inverse Gaussian process-based model to characterize the growth of metal-loss corrosion defects on energy pipelines. The model parameters are evaluated using the Bayesian methodology by combining the inspection data obtained from multiple inspections with the prior distributions. The Markov Chain Monte Carlo (MCMC) simulation techniques are employed to numerically evaluate the posterior marginal distribution of each individual parameter. The measurement errors associated with the ILI tools are considered in the Bayesian inference. The application of the growth model is illustrated using an example involving real inspection data collected from an in-service pipeline in Alberta, Canada. The results indicate that the model in general can predict the growth of corrosion defects reasonably well. Parametric analyses associated with the growth model as well as reliability assessment of the pipeline based on the growth model are also included in the example. The proposed model can be used to facilitate the development and application of reliability-based pipeline corrosion management.

关键词： pipeline     metal-loss corrosion     inverse Gaussian process     measurement error     hierarchical Bayesian     Markov Chain Monte Carlo (MCMC)    

HTML PDF 收藏

Determination of effective stress parameter of unsaturated soils: A Gaussian process regression approach

Pijush Samui, Jagan J

《结构与土木工程前沿（英文）》 2013年 第7卷 第2期   页码 133-136 doi: 10.1007/s11709-013-0202-1

摘要： This article examines the capability of Gaussian process regression (GPR) for prediction of effective stress parameter ( ) of unsaturated soil. GPR method proceeds by parameterising a covariance function, and then infers the parameters given the data set. Input variables of GPR are net confining pressure ( ), saturated volumetric water content ( ), residual water content ( ), bubbling pressure ( ), suction ( ) and fitting parameter ( ). A comparative study has been carried out between the developed GPR and Artificial Neural Network (ANN) models. A sensitivity analysis has been done to determine the effect of each input parameter on . The developed GPR gives the variance of predicted . The results show that the developed GPR is reliable model for prediction of of unsaturated soil.

关键词： unsaturated soil     effective stress parameter     Gaussian process regression (GPR)     artificial neural network (ANN)     variance    

HTML PDF 收藏

prediction method for remaining useful life of lithium-ion batteries based on a neural network and Gaussianprocess regression

《能源前沿（英文）》 doi: 10.1007/s11708-023-0906-4

摘要： Lithium-ion batteries (LIBs) are widely used in transportation, energy storage, and other fields. The prediction of the remaining useful life (RUL) of lithium batteries not only provides a reference for health management but also serves as a basis for assessing the residual value of the battery. In order to improve the prediction accuracy of the RUL of LIBs, a two-phase RUL early prediction method combining neural network and Gaussian process regression (GPR) is proposed. In the initial phase, the features related to the capacity degradation of LIBs are utilized to train the neural network model, which is used to predict the initial cycle lifetime of 124 LIBs. The Pearson coefficient’s two most significant characteristic factors and the predicted normalized lifetime form a 3D space. The Euclidean distance between the test dataset and each cell in the training dataset and validation dataset is calculated, and the shortest distance is considered to have a similar degradation pattern, which is used to determine the initial Dual Exponential Model (DEM). In the second phase, GPR uses the DEM as the initial parameter to predict each test set’s early RUL (ERUL). By testing four batteries under different working conditions, the RMSE of all capacity estimation is less than 1.2%, and the accuracy percentage (AP) of remaining life prediction is more than 98%. Experiments show that the method does not need human intervention and has high prediction accuracy.

关键词： lithium-ion batteries     RUL prediction     double exponential model     neural network     Gaussian process regression (GPR)    

HTML PDF 收藏

operation in the presence of different random noises and uncertainty: Implementation of generalized Gaussianprocess regression machine

Nasser L. AZAD,Ahmad MOZAFFARI

《机械工程前沿（英文）》 2015年 第10卷 第4期   页码 405-412 doi: 10.1007/s11465-015-0354-x

摘要：

The main scope of the current study is to develop a systematic stochastic model to capture the undesired uncertainty and random noises on the key parameters affecting the catalyst temperature over the coldstart operation of automotive engine systems. In the recent years, a number of articles have been published which aim at the modeling and analysis of automotive engines’ behavior during coldstart operations by using regression modeling methods. Regarding highly nonlinear and uncertain nature of the coldstart operation, calibration of the engine system’s variables, for instance the catalyst temperature, is deemed to be an intricate task, and it is unlikely to develop an exact physics-based nonlinear model. This encourages automotive engineers to take advantage of knowledge-based modeling tools and regression approaches. However, there exist rare reports which propose an efficient tool for coping with the uncertainty associated with the collected database. Here, the authors introduce a random noise to experimentally derived data and simulate an uncertain database as a representative of the engine system’s behavior over coldstart operations. Then, by using a Gaussian process regression machine (GPRM), a reliable model is used for the sake of analysis of the engine’s behavior. The simulation results attest the efficacy of GPRM for the considered case study. The research outcomes confirm that it is possible to develop a practical calibration tool which can be reliably used for modeling the catalyst temperature.

关键词： automotive engine     calibration     coldstart operation     Gaussian process regression machine (GPRM)     uncertainty and random noises    

HTML PDF 收藏

Simulation and analysis of grinding wheel based on Gaussian mixture model

Yulun CHI, Haolin LI

《机械工程前沿（英文）》 2012年 第7卷 第4期   页码 427-432 doi: 10.1007/s11465-012-0350-3

摘要：

This article presents an application of numerical simulation technique for the generation and analysis of the grinding wheel surface topographies. The ZETA 20 imaging and metrology microscope is employed to measure the surface topographies. The Gaussian mixture model (GMM) is used to transform the measured non-Gaussian field to Gaussian fields, and the simulated topographies are generated. Some numerical examples are used to illustrate the viability of the method. It shows that the simulated grinding wheel topographies are similar with the measured and can be effective used to study the abrasive grains and grinding mechanism.

关键词： grinding wheel     3D topographies measurement     Gaussian mixture model     simulation    

HTML PDF 收藏

基于混合驱动高斯过程学习的强机动多目标跟踪方法 Research Article

国强1,滕龙1,2,尹天祥3,郭云飞3,吴新良2,宋文明2

《信息与电子工程前沿（英文）》 2023年 第24卷 第11期   页码 1647-1656 doi: 10.1631/FITEE.2300348

摘要： 现有机动目标跟踪方法在杂波环境中强机动目标的跟踪性能并不令人满意。本文提出一种混合驱动方法，利用数据驱动和基于模型算法的优点跟踪多个高机动目标。将时变恒速（CV）模型集成到在线学习的高斯过程（GP）中，提高高斯过程的预测性能。进一步与广义概率数据关联（GPDA）算法相结合，实现多目标跟踪。通过仿真实验可知，与广泛使用的机动目标跟踪算法如交互式多模型（IMM）和数据驱动的高斯过程运动跟踪器（GPMT）相比，提出的混合驱动方法具有显著的性能优势。

关键词： 目标跟踪；高斯过程；数据驱动；在线学习；模型驱动；概率数据关联    

HTML PDF 收藏

Interfacial heat transfer coefficient between metal and die during high pressure die casting process

GUO Zhipeng, XIONG Shoumei, CHO SangHyun, CHOI JeongKil

《机械工程前沿（英文）》 2007年 第2卷 第3期   页码 283-287 doi: 10.1007/s11465-007-0049-z

摘要： The present work focused on the determination of the interfacial heat transfer coefficient (IHTC) between metal and die during the high pressure die casting (HPDC) process. Experiments were carried out on an aluminum alloy, ADC12Z, using step shape casting so-called because of its shape. The IHTC was successfully determined by solving one of the inverse heat problems using the nonlinear estimation method first used by Beck. The calculation results indicated that the IHTC immediately increased after liquid metal was brought into the cavity by the plunger and decreased as the solidification process of the liquid metal proceeded. The liquid metal eventually solidified completely, a condition when the IHTC tended to be stable. Casting thickness played an important role in affecting the IHTC between the metal and die not only in terms of its value but also in terms of its change tendency. Also, under the test conditions, different change tendencies of the metal solid fraction were found between castings with different thicknesses and the die.

关键词： so-called     calculation     inverse     interfacial     aluminum    

HTML PDF 收藏

一种基于高斯过程与粒子群算法的CNN超参数自动搜索混合模型优化算法 Research Article

闫涵,仲崇权,吴玉虎,张立勇,卢伟

《信息与电子工程前沿（英文）》 2023年 第24卷 第11期   页码 1557-1573 doi: 10.1631/FITEE.2200515

摘要： 卷积神经网络（CNN）在许多实际应用领域中有着快速发展。然而，CNN性能很大程度上取决于其超参数，而为CNN配置合适的超参数通常面临着以下3个挑战：（1）不同类型CNN超参数的混合变量编码问题；（2）评估候选模型的昂贵计算成本问题；（3）确保搜索过程中收敛速率和模型性能问题。针对上述问题，提出一种基于高斯过程（GP）和粒子群优化算法（PSO）的混合模型优化算法（GPPSO），用于自动搜索最优的CNN超参数配置。首先，设计一种新的编码方法高效编码CNN中不同类型的超参数。其次，提出一种混合代理辅助（HSA）模型降低评估候选模型的高计算成本。最后，设计一种新的激活函数改善模型性能并确保收敛速率。在图像分类基准数据集上进行了大量实验，验证GPPSO优于最先进的方法。以金属断口诊断为例，验证GPPSO算法在实际应用中的有效性。实验结果表明，GPPSO仅需0.04和1.70 GPU天即可在CIFAR-10和CIFAR-100数据集上实现95.26％和76.36％识别准确率。

关键词： 卷积神经网络；高斯过程；混合模型；超参数优化；混合变量；粒子群优化    

HTML PDF 收藏

Performance of inverse fluidized bed bioreactor in treating starch wastewater

M. RAJASIMMAN, C. KARTHIKEYAN

《化学科学与工程前沿（英文）》 2009年 第3卷 第3期   页码 235-239 doi: 10.1007/s11705-009-0020-0

摘要： Aerobic digestion of starch industry wastewater was carried out in an inverse fluidized bed bioreactor using low-density (870 kg/m ) polypropylene particles. Experiments were carried out at different initial substrate concentrations of 2250, 4475, 6730, and 8910 mg COD/L and for various hydraulic retention times (HRT) of 40, 32, 24, 16, and 8 h. Degradation of organic matter was studied at different organic loading rates (OLR) by varying the HRT and the initial substrate concentration. From the results it was observed that the maximum COD removal of 95.6% occurred at an OLR of 1.35 kg COD/(m ·d) and the minimum of 51.8% at an OLR of 26.73 kg COD/(m ·d). The properties of biomass accumulation on the surface of particles were also studied. It was observed that constant biomass loading was achieved over the entire period of operation.

关键词： inverse fluidization     low-density particles     polypropylene     starch     biofilm    

HTML PDF 收藏

Performance monitoring of non-gaussian chemical processes with modes-switching using globality-locality

Xin Peng, Yang Tang, Wenli Du, Feng Qian

《化学科学与工程前沿（英文）》 2017年 第11卷 第3期   页码 429-439 doi: 10.1007/s11705-017-1675-6

摘要： In this paper, we propose a novel performance monitoring and fault detection method, which is based on modified structure analysis and globality and locality preserving (MSAGL) projection, for non-Gaussian processes with multiple operation conditions. By using locality preserving projection to analyze the embedding geometrical manifold and extracting the non-Gaussian features by independent component analysis, MSAGL preserves both the global and local structures of the data simultaneously. Furthermore, the tradeoff parameter of MSAGL is tuned adaptively in order to find the projection direction optimal for revealing the hidden structural information. The validity and effectiveness of this approach are illustrated by applying the proposed technique to the Tennessee Eastman process simulation under multiple operation conditions. The results demonstrate the advantages of the proposed method over conventional eigendecomposition-based monitoring methods.

关键词： non-Gaussian processes     subspace projection     independent component analysis     locality preserving projection     finite mixture model    

HTML PDF 收藏

Efficient conversion of lignin to alkylphenols over highly stable inverse spinel MnFeO catalysts

《化学科学与工程前沿（英文）》 2023年 第17卷 第8期   页码 1085-1095 doi: 10.1007/s11705-022-2236-1

摘要： The aromatic properties of lignin make it a promising source of valuable chemicals and fuels. Developing efficient and stable catalysts to effectively convert lignin into high-value chemicals is challenging. In this work, MnFe2O4 spinel catalysts with oxygen-rich vacancies and porous distribution were synthesized by a simple solvothermal process and used to catalyze the depolymerization of lignin in an isopropanol solvent system. The specific surface area was 110.5 m2∙g–1, which substantially increased the active sites for lignin depolymerization compared to Fe3O4. The conversion of lignin reached 94%, and the selectivity of alkylphenols exceeded 90% after 5 h at 250 °C. Underpinned by characterizations, products, and density functional theory analysis, the results showed that the catalytic performance of MnFe2O4 was attributed to the composition of Mn and Fe with strong Mn–O–Fe synergy. In addition, the cycling experiments and characterization showed that the depolymerized lignin on MnFe2O4 has excellent cycling stability. Thus, our work provides valuable insights into the mechanism of lignin catalytic depolymerization and paves the way for the industrial-scale application of this process.

关键词： lignin depolymerization     spinel     catalysts     hydrogenation    

HTML PDF 收藏

Research on Anthropomorphic Obstacle Avoidance Trajectory Planning for Adaptive Driving Scenarios Based on Inverse

Jian Wu,Yang Yan,Yulong Liu,Yahui Liu,

《工程（英文）》 doi: 10.1016/j.eng.2023.07.018

摘要： The forward design of trajectory planning strategies requires preset trajectory optimization functions, resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajectories that conform to real driver behavior habits. In addition, owing to the strong time-varying dynamic characteristics of obstacle avoidance scenarios, it is necessary to design numerous trajectory optimization functions and adjust the corresponding parameters. Therefore, an anthropomorphic obstacle-avoidance trajectory planning strategy for adaptive driving scenarios is proposed. First, numerous expert-demonstrated trajectories are extracted from the HighD natural driving dataset. Subsequently, a trajectory expectation feature-matching algorithm is proposed that uses maximum entropy inverse reinforcement learning theory to learn the extracted expert-demonstrated trajectories and achieve automatic acquisition of the optimization function of the expert-demonstrated trajectory. Furthermore, a mapping model is constructed by combining the key driving scenario information that affects vehicle obstacle avoidance with the weight of the optimization function, and an anthropomorphic obstacle avoidance trajectory planning strategy for adaptive driving scenarios is proposed. Finally, the proposed strategy is verified based on real driving scenarios. The results show that the strategy can adjust the weight distribution of the trajectory optimization function in real time according to the “emergency degree” of obstacle avoidance and the state of the vehicle. Moreover, this strategy can generate anthropomorphic trajectories that are similar to expert-demonstrated trajectories, effectively improving the adaptability and acceptability of trajectories in driving scenarios.

关键词： Obstacle avoidance trajectory planning     Inverse reinforcement theory     Anthropomorphic     Adaptive driving scenarios    

HTML PDF 收藏

非线性计数系统的关键因子辨识方法 Research Article

张新民,王静波,魏驰航,宋执环

《信息与电子工程前沿（英文）》 2022年 第23卷 第1期   页码 123-133 doi: 10.1631/FITEE.2000324

摘要： 从数据中识别对系统输出产生较大影响的关键因子是科学和工程领域最具挑战性的任务之一。本文针对非线性计数系统，提出基于敏感性分析的广义高斯过程回归（SA-GGPR）建模方法，以识别影响系统输出的关键因子。SA-GGPR采用具有泊松似然的GGPR模型描述非线性计数系统。GGPR模型继承了非参数核学习和泊松分布的优点，可处理复杂非线性计数系统。然而，由于GGPR模型的非参数核学习架构，难以理解GGPR模型中输入和输出之间的关系。SA-GGPR方法通过定量评估不同输入对系统输出的影响来辨识影响系统输出的关键因子。在模拟非线性计数系统和实际钢铁轧制过程的应用结果表明，SA-GGPR方法在识别精度方面优于几种先进方法。

关键词： 关键因子；非线性计数系统；广义高斯过程回归；敏感性分析；钢铁轧制过程    

HTML PDF 收藏

Precise semi-analytical inverse kinematic solution for 7-DOF offset manipulator with arm angle optimization

《机械工程前沿（英文）》 2021年 第16卷 第3期   页码 435-450 doi: 10.1007/s11465-021-0630-x

摘要： Seven-degree-of-freedom redundant manipulators with link offset have many advantages, including obvious geometric significance and suitability for configu-ration control. Their configuration is similar to that of the experimental module manipulator (EMM) in the Chinese Space Station Remote Manipulator System. However, finding the analytical solution of an EMM on the basis of arm angle parameterization is difficult. This study proposes a high-precision, semi-analytical inverse method for EMMs. Firstly, the analytical inverse kinematic solution is established based on joint angle parameterization. Secondly, the analytical inverse kinematic solution for a non-offset spherical–roll–spherical (SRS) redundant manipulator is derived based on arm angle parameterization. The approximate solution of the EMM is calculated in accordance with the relationship between the joint angles of the EMM and the SRS manipulator. Thirdly, the error is corrected using a numerical method through the analytical inverse solution based on joint angle parameterization. After selecting the stride and termination condition, the precise inverse solution is computed for the EMM based on arm angle parameterization. Lastly, case solutions confirm that this method has high precision, and the arm angle parameterization method is superior to the joint angle parameterization method in terms of parameter selection.

关键词： 7-DOF redundant manipulator     inverse kinematics     semi-analytical     arm angle     link offset    

HTML PDF 收藏

Inverse identification of the mechanical parameters of a pipeline hoop and analysis of the effect of

Ye GAO, Wei SUN

《机械工程前沿（英文）》 2019年 第14卷 第3期   页码 358-368 doi: 10.1007/s11465-019-0539-9

摘要： To create a dynamic model of a pipeline system effectively and analyze its vibration characteristics, the mechanical characteristic parameters of the pipeline hoop, such as support stiffness and damping under dynamic load, must be obtained. In this study, an inverse method was developed by utilizing measured vibration data to identify the support stiffness and damping of a hoop. The procedure of identifying such parameters was described based on the measured natural frequencies and amplitudes of the frequency response functions (FRFs) of a pipeline system supported by two hoops. A dynamic model of the pipe-hoop system was built with the finite element method, and the formulas for solving the FRF of the pipeline system were provided. On the premise of selecting initial values reasonably, an inverse identification algorithm based on sensitivity analysis was proposed. A case study was performed, and the mechanical parameters of the hoop were identified using the proposed method. After introducing the identified values into the analysis model, the reliability of the identification results was validated by comparing the predicted and measured FRFs of the pipeline. Then, the developed method was used to identify the support stiffness and damping of the pipeline hoop under different preloads of the bolts. The influence of preload was also discussed. Results indicated that the support stiffness and damping of the hoop exhibited frequency-dependent characteristics. When the preloads of the bolts increased, the support stiffness increased, whereas the support damping decreased.

关键词： inverse identification     pipeline hoop     frequency response function     mechanical parameters     preload    

HTML PDF 收藏

标题 作者 时间 类型 操作

Inverse Gaussian process-based corrosion growth modeling and its application in the reliability analysis

Hao QIN, Shenwei ZHANG, Wenxing ZHOU

期刊论文

Determination of effective stress parameter of unsaturated soils: A Gaussian process regression approach

Pijush Samui, Jagan J

期刊论文

prediction method for remaining useful life of lithium-ion batteries based on a neural network and Gaussianprocess regression

期刊论文

operation in the presence of different random noises and uncertainty: Implementation of generalized Gaussianprocess regression machine

Nasser L. AZAD,Ahmad MOZAFFARI

期刊论文

Simulation and analysis of grinding wheel based on Gaussian mixture model

Yulun CHI, Haolin LI

期刊论文

基于混合驱动高斯过程学习的强机动多目标跟踪方法

国强1,滕龙1,2,尹天祥3,郭云飞3,吴新良2,宋文明2

期刊论文

Interfacial heat transfer coefficient between metal and die during high pressure die casting process

GUO Zhipeng, XIONG Shoumei, CHO SangHyun, CHOI JeongKil

期刊论文

一种基于高斯过程与粒子群算法的CNN超参数自动搜索混合模型优化算法

闫涵,仲崇权,吴玉虎,张立勇,卢伟

期刊论文

Performance of inverse fluidized bed bioreactor in treating starch wastewater

M. RAJASIMMAN, C. KARTHIKEYAN

期刊论文

Performance monitoring of non-gaussian chemical processes with modes-switching using globality-locality

Xin Peng, Yang Tang, Wenli Du, Feng Qian

期刊论文

Efficient conversion of lignin to alkylphenols over highly stable inverse spinel MnFeO catalysts

期刊论文

Research on Anthropomorphic Obstacle Avoidance Trajectory Planning for Adaptive Driving Scenarios Based on Inverse

Jian Wu,Yang Yan,Yulong Liu,Yahui Liu,

期刊论文

非线性计数系统的关键因子辨识方法

张新民,王静波,魏驰航,宋执环

期刊论文

Precise semi-analytical inverse kinematic solution for 7-DOF offset manipulator with arm angle optimization

期刊论文

Inverse identification of the mechanical parameters of a pipeline hoop and analysis of the effect of

Ye GAO, Wei SUN

期刊论文