Metal Detection of Wood Based on Thermal Signal Reconstruction Algorithm | Zendy

Hong Zhang | Zendy; Ruizhen Yang | Zendy; Wenhui Chen | Zendy; Ruikun Wu | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Metal Detection of Wood Based on Thermal Signal Reconstruction Algorithm

Author(s) -

Hong Zhang,

Ruizhen Yang,

Wenhui Chen,

Ruikun Wu

Publication year - 2021

Publication title -

journal of sensors

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.399

H-Index - 43

eISSN - 1687-7268

pISSN - 1687-725X

DOI - 10.1155/2021/7492813

Subject(s) - thermography , eddy current , nondestructive testing , thermal , signal (programming language) , algorithm , metal , computer science , materials science , current (fluid) , process engineering , acoustics , electronic engineering , engineering , optics , metallurgy , infrared , electrical engineering , physics , meteorology , quantum mechanics , programming language

In this paper, eddy current thermography is used to detect metal in wood materials, and thermal signal reconstruction (TSR) algorithm has been proposed to solve the problem of low resolution of metal detection. The basic principle of current nondestructive testing technologies for wood materials has been briefly reviewed, and the advantages and disadvantages have been analyzed. TSR algorithm can significantly enhance the contrast ration between metal and surrounding areas, different quantities of metal can be effective identified, and metal positions can be accurately realized. The experimental results show that the proposed eddy current thermography technology can quickly detect metal in wood materials and improve the efficiency and accuracy. The size and quantity of metal can be intuitively observed through thermal images.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research