Results 301 to 310 of about 3,415,717 (388)

A Multistep Sequence-to-Sequence Model With Attention LSTM Neural Networks for Industrial Soft Sensor Application

IEEE Sensors Journal, 2023
Soft sensor technology is widely used in industries to handle highly nonlinear, dynamic, time-dependent sequence data of industrial processes for predicting the key variables associated with auxiliary process variables.
Lianwei Ma, Yuan Zhao, Bin Wang, Feifan Shen   +3 more
semanticscholar   +1 more source

ConvLSTM and Self-Attention Aided Canonical Correlation Analysis for Multioutput Soft Sensor Modeling

IEEE Transactions on Instrumentation and Measurement, 2023
The polymerization process produces industrially important products; hence, its monitoring and control are of paramount importance. However, the nonavailability of real-time (on-demand) measurement of quality variables gives rise to difficulties in ...
Xiuli Zhu, S. Damarla, K. Hao, Biao Huang, Hongtian Chen, Yicun Hua   +5 more
semanticscholar   +1 more source

Novel Feature-Disentangled Autoencoder Integrating Residual Network for Industrial Soft Sensor

IEEE Transactions on Industrial Informatics, 2023
In order to overcome the low robustness and weak generalization in existing deep autoencoder (AE) for soft sensor modeling, a novel feature-disentangled AE (FDAE) integrating residual network (Resnet) (FDAE-Resnet) is proposed in this article.
Hao Wu, Yongming Han, Qunxiong Zhu, Zhiqiang Geng   +3 more
semanticscholar   +1 more source

A Zero-Shot Soft Sensor Modeling Approach Using Adversarial Learning for Robustness Against Sensor Fault

IEEE Transactions on Industrial Informatics, 2023
Soft sensors are widely used in many industrial systems to monitor key variables that are difficult to measure, using measurements from other available physical sensors.
Z. Y. Ding, J. Loo, S. Nurzaman, Chee Pin Tan, Vishnu Monn Baskaran   +4 more
semanticscholar   +1 more source

Bidirectional Minimal Gated Unit-Based Nonlinear Dynamic Soft Sensor Modeling Framework for Quality Prediction in Process Industries

IEEE Transactions on Instrumentation and Measurement, 2023
Quality prediction plays a crucial role in improving the product quality and economic benefit for modern process industries. The high-dimensional characteristics of process variables and the nonlinear dynamic behaviors of sequential data make the ...
Liang Ma, Mengwei Wang, Kai-xiang Peng
semanticscholar   +1 more source

Soft microflow sensors

Lab on a Chip, 2009
We present a rapid prototyping method for integrating functional components in conventional PDMS microfluidic devices. We take advantage of stop-flow lithography (D. Dendukuri, S. S. Gu, D. C. Pregibon, T. A. Hatton and P. S. Doyle, Lab Chip, 2007, 7, 818)(1) to achieve the in situ fabrication of mobile and deformable elements with a controlled ...
Rafaele, Attia, Daniel C, Pregibon, Patrick S, Doyle, Jean-Louis, Viovy, Denis, Bartolo   +4 more
openaire   +2 more sources

Machine-Learning-Assisted Recognition on Bioinspired Soft Sensor Arrays.

ACS Nano, 2022
Soft interfaces with self-sensing capabilities play an essential role in environment awareness and reaction. The growing overlap between materials and sensory systems has created a myriad of challenges for sensor integration, including the design of a ...
Yang Luo, Xiao Xiao, Jun Chen, Qian Li, H. Fu   +4 more
semanticscholar   +1 more source

FIGAN: A Missing Industrial Data Imputation Method Customized for Soft Sensor Application

IEEE Transactions on Automation Science and Engineering, 2022
Missing data is quite common in the industrial field, resulting in problems in downstream applications, as most data driven methods used in these applications rely on complete and high-quality dataset to build a high-quality model.
Zoujing Yao, Chunhui Zhao
semanticscholar   +1 more source

Disruptive, Soft, Wearable Sensors

Advanced Materials, 2019
AbstractThe wearable industry is on the rise, with a myriad of technical applications ranging from real‐time health monitoring, the Internet of Things, and robotics, to name but a few. However, there is a saying “wearable is not wearable” because the current market‐available wearable sensors are largely bulky and rigid, leading to uncomfortable wearing
Yunzhi Ling, Tiance An, Lim Wei Yap, Bowen Zhu, Shu Gong, Wenlong Cheng   +5 more
openaire   +2 more sources

A Novel Soft Sensor Modeling Approach Based on Difference-LSTM for Complex Industrial Process

IEEE Transactions on Industrial Informatics, 2022
The main purpose of soft sensor modeling is to capture the dynamic nonlinear features between the easy-to-measure auxiliary variables and the difficult-to-measure key variables.
Jiayi Zhou, Xiaoli Wang, Chunhua Yang, Wei Xiong   +3 more
semanticscholar   +1 more source