Cross-section geometry prediction for laser metal deposition layer-based on multi-mode convolutional neural network and multi-sensor data fusion

Dong, Fangyu; Kong, Lingchao; Wang, Hedong; Chen, Yongxiong; Liang, Xiubing

doi:10.1016/j.jmapro.2023.11.036

Journal of Manufacturing Processes

2023

DOI: 10.1016/j.jmapro.2023.11.036

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Cross-section geometry prediction for laser metal deposition layer-based on multi-mode convolutional neural network and multi-sensor data fusion

Fangyu Dong,

Lingchao Kong,

Hedong Wang

et al.

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2024

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Cited by 2 publications

References 35 publications

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Thermo-Structural Coupled Finite Element Analysis of Repair Process for Steam Turbine Blade Using Laser-Directed Energy Deposition Method

Arai,

Fujita,

Meng

et al. 2024

J Therm Spray Tech

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This study presents a numerical additive manufacturing simulation aimed at simulating the shape recovery process of a steam turbine blade damaged by corrosion, using laser-directed energy deposition (LDED). The simulation integrates the finite element (FE) method with heat conduction and thermo-elastoplastic constitutive equations, incorporating phase transformation. The additive manufacturing process by LDED was modeled using the death-birth algorithm, wherein a deposition layer is defined as a virtual element. Its stiffness and thermal properties activated when the laser irradiation regions overlapped. In this study, the shape of the virtual element was determined based on the cross-sectional shape of the deposition layer manufactured under various laser conditions. To validate the numerical simulation results, additive manufacturing was conducted for one pass deposition in the width direction at the center of a cantilever-supported plate made of SUS304 steel, and the changes in displacement at the free edges with respect to the process time were compared. The obtained FE results are in good agreement with the experimental results. Finally, an FE simulation was performed for the shape recovery of a steam turbine blade thinned due to corrosion damage. The results revealed that the residual stress component becomes more compressive as the laser output decreases and scanning speed increases, which is advantageous for improving the fatigue strength of steam turbine blades.

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Thermo-Structural Coupled Finite Element Analysis of Repair Process for Steam Turbine Blade Using Laser-Directed Energy Deposition Method

Arai,

Fujita,

Meng

et al. 2024

J Therm Spray Tech

View full text Add to dashboard Cite

show abstract

RETRACTED: Research on application of multimodal data fusion in intelligent building environment perception

Wang,

Guo

2024

IFS

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With the rapid development of the building industry, intelligent buildings benefit from its safety, energy saving, environmental protection and integration and other advantages have been widely loved by people, most operators also realize the importance of intelligent buildings to bring people humanized and customized services, and in order to realize the personalized service of the building, multi-modal data fusion is an effective method. On the other hand, in today’s Internet of Things society, many practical applications need to deploy a large number of sensing equipment for data collection and processing, so as to carry out high-quality monitoring of the physical world, but due to the inherent limitations of these hardware equipment and the influence of factors such as the environment, single mode data often cannot be completely and comprehensively monitored to the physical world’s changing characteristics. In this development context, multi-modal data fusion has become a research hotspot in the field of machine learning. Based on this, this paper proposes a one-stage fast object detection model with multi-level fusion of multi-modal features and end-to-end characteristics for building indoor environment perception, and conducts experimental analysis on the performance of the model. The verification results show that the accuracy of the proposed method is 50.7% and the running speed is 0.107 s, which has better performance than the existing detection methods.

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Cross-section geometry prediction for laser metal deposition layer-based on multi-mode convolutional neural network and multi-sensor data fusion

Cited by 2 publications

References 35 publications

Thermo-Structural Coupled Finite Element Analysis of Repair Process for Steam Turbine Blade Using Laser-Directed Energy Deposition Method

Thermo-Structural Coupled Finite Element Analysis of Repair Process for Steam Turbine Blade Using Laser-Directed Energy Deposition Method

RETRACTED: Research on application of multimodal data fusion in intelligent building environment perception

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