Optimization of lapping process parameters of CP-Ti based on PSO with mutation and BPNN

Ye, Kaiqiang; Wang, Jianbin; Gao, Hong; Liu, Yang; Ping, Xiao

doi:10.1007/s00170-021-07862-1

Cited by 5 publications

(3 citation statements)

References 21 publications

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“…The differential feature extraction network was composed of three fully connected layers ( fc 1 , fc 2 , and fc 3 ). The range of the numbers in the hidden layer of the differential feature extraction network was determined by empirical formulas and Kolmogorov theorem [ 38 ]. The number of nodes was set to 150, 100, and 1, respectively.…”

Section: Experiments and Discussionmentioning

confidence: 99%

A Change Detection Method for Remote Sensing Images Based on Coupled Dictionary and Deep Learning

Yang

Song

et al. 2022

Computational Intelligence and Neuroscience

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With the rapid development of remote sensing technology, change detection (CD) methods based on remote sensing images have been widely used in land resource planning, disaster monitoring, and urban expansion, among other fields. The purpose of CD is to accurately identify changes on the Earth’s surface. However, most CD methods focus on changes between the pixels of multitemporal remote sensing image pairs while ignoring the coupled relationships between them. This often leads to uncertainty about edge pixels with regard to changing objects and misclassification of small objects. To solve these problems, we propose a CD method for remote sensing images that uses a coupled dictionary and deep learning. The proposed method realizes the spatial-temporal modeling and correlation of multitemporal remote sensing images through a coupled dictionary learning module and ensures the transferability of reconstruction coefficients between multisource image blocks. In addition, we constructed a differential feature discriminant network to calculate the dissimilarity probability for the change area. A new loss function that considers true/false discrimination loss, classification loss, and cross-entropy loss is proposed. The most discriminating features can be extracted and used for CD. The performance of the proposed method was verified on two well-known CD datasets. Extensive experimental results show that the proposed method is superior to other methods in terms of precision, recall, F1-score, IoU , and OA .

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Section: Experiments and Discussionmentioning

confidence: 99%

A Change Detection Method for Remote Sensing Images Based on Coupled Dictionary and Deep Learning

Yang

Song

et al. 2022

Computational Intelligence and Neuroscience

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“…For thermal optimization of plate‐fin heat exchangers, Turgut [ 38 ] took the Hybrid Chaotic Quantum behaved Particle Swarm Optimization (HCQPSO) algorithm as a method. Wang et al [ 39 ] studied the surface quality of CP‐Ti lapped with free abrasive with process parameter. Then, a neural network with the particle swarm optimization (PSO) algorithm was used to optimize parameters.…”

Section: Introductionmentioning

confidence: 99%

Structural design optimization of CFRP/Al hybrid co‐cured high‐speed flywheel with the particle swarm optimization algorithm

Zhong

Cai

et al. 2023

Polymer Composites

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With the development of CFRP materials and co‐cured structure, CFRP/Al hybrid co‐cured materials have been widely used for high‐speed energy storage flywheels. Therefore, it has become a hot research topic, which is to design a CFRP/Al hybrid co‐cured flywheel with a reasonable structure. In this paper, a particle swarm optimization algorithm is presented for improving the energy storage density to optimize the structure of the CFRP/Al hybrid co‐cured high‐speed flywheel. First, the stress and structural analysis of the flywheel are carried out based on energy storage. The inner‐radius‐to‐outer‐radius λ and the radial wall thickness h are chosen as the objective function because the λ and h are the factors which influence the energy storage density of the flywheel. Based the Tsai‐Hill criterion, the assembly interference t is the constraint condition which is the factor to meet the stress of design requirements. Then, the mathematical model of the flywheel is established by the objective function and the restriction with the particle swarm optimization algorithm (PSO). Finally, a specific CFRP/Al hybrid co‐cured flywheel is presented for the structural optimization with PSO by improving the energy storage density. In addition, the optimized flywheel is carried out to examine the static and dynamic requirements by the finite element method. The results indicate the PSO can be effectively used to optimize the structure of the CFRP/Al hybrid co‐cured high‐speed flywheel.

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“…In the field of machining processes, back-propagation (BP) neural networks [ 14 , 15 , 16 , 17 , 18 , 19 , 20 ] have been widely used to predict the value of machining quality. During the above training process, problems of over fitting and gradient disappearance [ 21 , 22 ] are encountered with the increasing of hidden layers.…”

Section: Introductionmentioning

confidence: 99%

Lapping Quality Prediction of Ceramic Fiber Brush Based on Gaussian-Restricted Boltzmann Machine

Yuan

Wang

et al. 2022

Materials

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Although ceramic fiber brushes have been widely used for deburring and surface finishing, the associated relationship between process parameters and lapping quality is still unclear. In order to optimize the lapping process of ceramic fiber brushes, this paper proposes a multi-layer neural network based on the Gaussian-restricted Boltzmann machine (GRBM), and verified its prediction effectiveness. Compared with a traditional back-propagation neural network, its prediction error was reduced from 7.6% to 4.5%, and the determination coefficient was increased from 0.96 to 0.98, respectively. The comparison results showed that the proposed model can better grasp the relationship between process parameters and machining quality, which can be used as a decision-making foundation for lapping-process optimization.

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Optimization of lapping process parameters of CP-Ti based on PSO with mutation and BPNN

Cited by 5 publications

References 21 publications

A Change Detection Method for Remote Sensing Images Based on Coupled Dictionary and Deep Learning

A Change Detection Method for Remote Sensing Images Based on Coupled Dictionary and Deep Learning

Structural design optimization of CFRP/Al hybrid co‐cured high‐speed flywheel with the particle swarm optimization algorithm

Lapping Quality Prediction of Ceramic Fiber Brush Based on Gaussian-Restricted Boltzmann Machine

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