Patents by Inventor Hongkun ZHU

Hongkun ZHU has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Quaternion multi-degree-of-freedom neuron-based multispectral welding image recognition method
    Patent number: 11651481
    Abstract: Disclosed is a quaternion multi-degree-of-freedom neuron-based multispectral welding image recognition method, comprising: using three cameras having different wavebands to obtain multispectral weld pool images, and respectively performing pre-processing and edge extraction on the weld pool images having the different wavebands obtained at a same moment by the three cameras; establishing a quaternion-based multispectral weld pool image edge model; extracting low-frequency features after a quaternion discrete cosine transform; using a quaternion-based multi-degree-of-freedom neuron network to perform classification, training and recognition on edge features of the multispectral weld pool images. Compared to traditional means, the present invention has multiple recognition information sources, strong anti-interference capabilities and high recognition accuracy.
    Type: Grant
    Filed: October 28, 2020
    Date of Patent: May 16, 2023
    Assignee: NANTONG UNIVERSITY
    Inventors: Liang Hua, Hongkun Zhu, Yuqing Liu, Ling Jiang, Ran Chen, Kexin Shi
  • QUATERNION MULTI-DEGREE-OF-FREEDOM NEURON-BASED MULTISPECTRAL WELDING IMAGE RECOGNITION METHOD
    Publication number: 20220414857
    Abstract: Disclosed is a quaternion multi-degree-of-freedom neuron-based multispectral welding image recognition method, comprising: using three cameras having different wavebands to obtain multispectral weld pool images, and respectively performing pre-processing and edge extraction on the weld pool images having the different wavebands obtained at a same moment by the three cameras; establishing a quaternion-based multispectral weld pool image edge model; extracting low-frequency features after a quaternion discrete cosine transform; using a quaternion-based multi-degree-of-freedom neuron network to perform classification, training and recognition on edge features of the multispectral weld pool images. Compared to traditional means, the present invention has multiple recognition information sources, strong anti-interference capabilities and high recognition accuracy.
    Type: Application
    Filed: October 28, 2020
    Publication date: December 29, 2022
    Inventors: Liang HUA, Hongkun ZHU, Yuqing LIU, Ling JIANG, Ran CHEN, Kexin SHI