Automated Underwater Flow Analysis Using Texture Prediction
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Solution Overview
Problem
Current methods for monitoring underwater fluid flow during deep-sea drilling are prone to human error and inefficiency, leading to inconsistent and potentially catastrophic observations due to the reliance on manual review of video footage by human supervisors.
Innovation Solution
A system comprising a user device, video acquisition processor, and a server with texture prediction, fluid motion estimation, object detection, and fusion algorithms to analyze underwater fluid flow, comparing current images to historical data and generating alerts for deviations, thereby automating the analysis process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual review of video footage by human supervisors is used, then the system is simpler to operate, but the analysis speed is slow and human error occurs
Solution Approach 1:
The patent replaces the mechanical system of manual video review with an automated computer-based analysis system that uses image processing algorithms to detect fluid flow patterns, eliminating the need for human supervisors to manually examine footage while significantly improving analysis speed
Solution Approach 2:
The system performs self-service by automatically analyzing video footage without human intervention, using pre-programmed algorithms to detect deviations in fluid flow patterns and generate alerts, thereby maintaining operational simplicity while eliminating human error and improving productivity
2Device complexity
If manual review of video footage by human supervisors is used, then the system is simpler, but measurement accuracy is reduced due to human error
Solution Approach 1:
The patent replaces the human supervisor's manual review process with an automated computer-based system that uses consistent, objective algorithms to analyze video footage, eliminating human error and improving measurement accuracy while maintaining reasonable system complexity
Solution Approach 2:
The system incorporates feedback mechanisms by continuously comparing detected fluid flow patterns against established baseline data, automatically identifying deviations and providing corrective alerts, thereby ensuring high measurement precision through systematic verification
3Use of energy by moving object
If manual review of video footage is used, then the system requires less computational resources, but response time is delayed
Solution Approach 1:
The system performs preliminary action by pre-processing video footage in real-time as it is captured, continuously analyzing fluid flow patterns and comparing them against baseline data before deviations become critical, thereby reducing response time without requiring excessive computational resources
Solution Approach 2:
The system applies partial action by focusing computational resources only on detecting specific fluid flow deviations rather than analyzing every aspect of the video footage, achieving rapid response times while maintaining efficient use of computational resources
Data Source
AI summary
This invention relates generally to analyzing fluid flow and calculating significant deviations in fluid flow. There is a system and a method. The system includes a user device, a video acquisition processor, a server, and a database. Generally, the method includes recording underwater fluid flow, analyzing the fluid flow using fluid flow and object detection algorithms, checking for deviations in recent fluid flow, and alerting a user.