ROV Component Image Inspection for Accurate Rail Shuttle Maintenance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing automated storage and retrieval systems face challenges in accurately determining the condition of components, leading to inadequate maintenance practices that can result in system downtime, increased costs, and potential component damage due to incomplete or inaccurate maintenance schedules.
Innovation Solution
A method and system for determining the condition of remotely operated vehicle components using image recording, identification, and analysis, potentially leveraging machine learning to recognize patterns and schedule maintenance optimally, reducing operator involvement and ensuring standardized inspections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection methods are used to determine component condition, then operator flexibility is maintained, but measurement precision and consistency deteriorate due to subjective assessment variations
Solution Approach 1:
The patent replaces manual visual inspection with automated image capture devices (cameras) and computational analysis. The system uses digital images processed by algorithms to objectively assess component conditions such as wear, damage, and maintenance needs, eliminating subjective human assessment while maintaining operational flexibility.
2Reliability
If comprehensive component inspection is performed frequently, then maintenance accuracy improves, but system downtime increases due to more frequent inspections
Solution Approach 1:
The patent implements periodic automated inspections where image capture devices take pictures of components at scheduled intervals during normal operations. The system analyzes images periodically to track component degradation over time, enabling maintenance to be performed only when actually needed rather than on fixed schedules, thus minimizing downtime while maintaining reliability.
Solution Approach 2:
The inspection system is designed to operate autonomously during vehicle operations, capturing and analyzing component images without requiring system shutdown. The automated image processing and maintenance scheduling functions serve themselves, eliminating the need for manual inspection intervention and reducing overall system downtime.
3Measurement precision
If detailed component analysis is conducted, then diagnostic accuracy improves, but data processing complexity increases
Solution Approach 1:
The patent segments the image analysis process into distinct functional modules: image capture, pre-processing (enhancement, noise reduction), feature extraction (identifying specific component characteristics), and condition assessment. This modular approach allows detailed analysis of individual components while managing overall system complexity through organized, reusable processing routines.
Solution Approach 2:
The system creates digital copies (images) of physical components for analysis, allowing detailed examination without physically manipulating or disassembling the actual components. Multiple image copies can be processed simultaneously through automated algorithms, enabling comprehensive analysis while keeping the physical system operational and reducing processing complexity through parallel computation.
Data Source
AI summary
The invention relates to a method for determining a condition of a component of a remotely operated vehicle (501) operating on a rail system (108) of an automated storage and retrieval system (1) for goods holders (106). The method comprises selecting the component of the remotely operated vehicle (501), recording an image of the component. identifying the component on the basis of the recorded image and determining condition of the identified component using the recorded image. The invention further relates to a system (510) for determining a condition of a component and an automated storage and retrieval system (1) comprising said system (510).