Chun-Hung Weng

Title: Chun-Hung Weng and a Deep-Learning Method for Measuring Physical Properties.

Introduction

Chun-Hung Weng is an inventor associated with Taoyuan, Taiwan, and National Central University. His patent work describes a method that uses deep learning to estimate physical properties of a measured fluid from mass-flow data. The available information lists 1 patent for him.

Latest Patents

“Method of Measuring Physical Properties” outlines a process for estimating a fluid’s physical-property parameters. A computing unit generates simulated mass-flow-rate data from training parameter sets and vessel-shape information. A processor then trains a deep-learning model using the simulated data as input features and the corresponding physical-property parameters as output features.

During measurement, fluid enters a vessel through an opening and is received by a loader. A scale records the loader’s accumulated weight over time, producing measured mass-flow-rate data. The trained model uses those measurements to determine a physical-property parameter set for the fluid.

Career Highlights

Weng’s listed patent connects computational modeling, deep learning, and physical measurement. The method uses vessel geometry and weight measurements to infer properties of a fluid, offering a data-driven approach to measurement.

Collaborations

Wei-Xu Cai is identified as Weng’s coworker. The available information does not specify their roles or describe a particular joint project.

Conclusion

Chun-Hung Weng’s listed invention applies deep learning to fluid measurement by translating mass-flow data into estimated physical properties.