Wireline Cable Defect Detection with 360° Imaging and Machine Learning
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Solution Overview
Problem
Visual inspections of wireline cables are error-prone, subjective, and inconsistent, often failing to detect defects due to the speed of cable insertion and retrieval, leading to potential catastrophic failures and costly disruptions in gas and oil supply chains.
Innovation Solution
An automated system using a combination of imaging and laser subsystems, equipped with trained machine learning models, provides a 360° view and dimensional analysis to detect defects in wireline cables, including type, severity, and location, generating real-time notifications and datasets for improved maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual inspection by operators is used to detect defects in wireline cables, then the inspection process is simple and low-cost, but the detection accuracy is low and results are error-prone and inconsistent
Solution Approach 1:
The patent replaces manual visual inspection with an automated imaging system that captures images of wireline cables using cameras or other imaging devices. The system then uses machine learning models (such as convolutional neural networks) to automatically analyze the images and detect defects, substituting human operators with automated optical and computational systems to achieve higher detection accuracy and consistency.
2Productivity
If manual visual inspection is performed on wireline cables, then the equipment cost is low, but the inspection speed is insufficient to keep up with cable insertion and retrieval speeds
Solution Approach 1:
The system performs preliminary actions by continuously capturing images of the wireline cable as it moves through the imaging area, storing these images for later analysis. The machine learning models are pre-trained on defect data to enable rapid automated analysis, allowing the system to inspect cables at speeds matching cable insertion and retrieval rates without requiring manual inspection during high-speed operations.
3Reliability
If automated imaging systems with multiple sensors are deployed to achieve 360° coverage, then the detection coverage is improved, but the device complexity and cost increase
Solution Approach 1:
The patent divides the inspection task into multiple segments by using several imaging devices positioned at different locations around the wireline cable path. Each imaging device captures images of a specific segment or angle of the cable, and the system integrates these segmented views to achieve comprehensive 360° coverage and improved detection reliability without requiring a single overly complex imaging system.
Data Source
AI summary
Disclosed examples generally relate to automated monitoring of defects in wireline cables. In at least one examples, the method for automated detection of defects in wireline cables includes inputting one or more image frames, captured of a wireline cable portion at a given time instance using an imaging subsystem, into a trained image analysis model, wherein the model is trained to predict the presence of defects in imaged wireline cables; based on an output of the trained image analysis model, determining the presence of one or more defects in the imaged wireline cable portion; and if one or more defects are detected, generating an output.