.png){kind=icon}
返回
Noncontact thermal mapping method based on local temperature data using deep neural network regression
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ijheatmasstransfer.2021.122236.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Temperature monitoring of electronic devices is important to prevent the active components from overheating. In this study, a novel method to obtain the overall temperature map of electronic modules with limited local temperature data was suggested using a deep-neural-network-based multi-output regression model. To predict the entire temperature distribution with minimum data, one to six random inputs considering their diverse arrangements were applied and compared by calculating the mean absolute error. In addition, the temperature prediction accuracy of the heating element was considered as an important parameter for the performance score. Consequently, a temperature prediction accuracy of-96.7% was realized using three input local data points close to the heat source. Furthermore, with the other three temperature data points away from the heat source, the score increased by-11.6% (-79.9 to-89.2%) after the hyperparameter tuning processes. These results support the precise noncontact virtual sensing technology of temperature monitoring methods for various industries, such as electric vehicles, cold-chain warehouses, and robotics. (c) 2021 Elsevier Ltd. All rights reserved.
Keyword:
Thermal imaging
Temperature mapping
Virtual sensors
Deep neural network
Thermal management
期刊
IF:
5.8
论文数:
2.6W
被引数:
10.2W
机构
引用论文
分享收藏Deep Learning-Based Regression and Classification for Automatic Landmark Localization in Medical Images基于深度学习回归和分类的医学图像自动界标定位
OAAI
OAAI分享收藏Taking the Human Out of the Loop: A Review of Bayesian Optimization将人类带出循环: 贝叶斯优化的回顾.png)
PROCEEDINGS OF THE IEEE
PROCEEDINGS OF THE IEEEIF25.9
PREAI
分享收藏A novel recurrent neural network soft sensor via a differential evolution training algorithm for the tire contact patchNEUROCOMPUTING
NEUROCOMPUTINGIF6.5
PREAI
分享收藏
查看更多内容