The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 27, 2025

Filed:

Apr. 27, 2022
Applicant:

Wipro Limited, Bangalore, IN;

Inventors:

Shiny Manasseh Chilakabathini, Khammam, IN;

Sujatha Jagannath, Bangalore, IN;

Ramachandram Vedula, Bangalore, IN;

Assignee:

Wipro Limited, Bangalore, IN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G01N 33/46 (2006.01); G01N 29/04 (2006.01); G01N 29/07 (2006.01); G01N 29/34 (2006.01); G01N 29/36 (2006.01); G01N 29/44 (2006.01);
U.S. Cl.
CPC ...
G01N 33/46 (2013.01); G01N 29/048 (2013.01); G01N 29/07 (2013.01); G01N 29/343 (2013.01); G01N 29/36 (2013.01); G01N 29/4445 (2013.01); G01N 2291/0238 (2013.01);
Abstract

Present disclosure discloses method and system for assessing health of a wood specimen. Method receives ultrasonic data for each of a plurality of alignments of a transmitter and associated receiver across a cross-section of one or more cross-sections along a length of the wood specimen. The ultrasonic data comprises a pulse velocity, a transit time and a distance travelled by an ultrasonic pulse between the transmitter and the associated receiver. Thereafter, method measures relative features of the wood specimen using the ultrasonic data. Subsequently, method identifies a condition of the cross-section of the wood specimen based on the relative features using a trained ML model. Upon identifying the condition of the cross-section to be defective, method determines a position of a defect in the cross-section of the wood specimen using the relative features and determines a severity of the defect using the trained ML model and the relative features.


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