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.
Patent No.:
Date of Patent:
Oct. 17, 2023
Filed:
Jun. 24, 2021
Identification of defect types in liquid pipelines for classification and computing severity thereof
Tata Consultancy Services Limited, Mumbai, IN;
Jayavardhana Rama Gubbi Lakshminarasimha, Bangalore, IN;
Mahesh Rangarajan, Bangalore, IN;
Rishin Raj, Bangalore, IN;
Vishnu Hariharan Anand, Bangalore, IN;
Vishal Bajpai, Bangalore, IN;
Vishwa Chethan Dandenahalli Venkatappa, Bangalore, IN;
Pradeep Kumar Mishra, Bangalore, IN;
Gourav Singh Jat, Bangalore, IN;
Meghala Mani, Bangalore, IN;
Gangadhar Shankarappa, Bangalore, IN;
Dinesh Sasidharan Nair, Bangalore, IN;
Shashank Lipate, Bangalore, IN;
Vineet Lall, Bangalore, IN;
Kavita Sara Mathew, Bangalore, IN;
Karthik Seemakurthy, Bangalore, IN;
Balamuralidhar Purushothaman, Bangalore, IN;
Tata Consultancy Services Limited, Mumbai, IN;
Abstract
Current inspection processes employed for pipeline networks data acquisition aided with manually locating and recording defects/observations, thus leading labor intensive, prone to error and a time-consuming task thereby resulting in process inefficiencies. Embodiments of the present disclosure provide systems and methods for that leverage artificial intelligence/machine learning models and image processing techniques to automate log and data processing, reports and insights generation thereby reduce dependency on manual analysis, improve annual productivity of survey meterage and bring in process and cost efficiencies into overall asset health management for utilities, thereby enhancing accuracy in defect identification, analysis, classification thereof.