Vision Teaching Device With Conditional History Storage
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Solution Overview
Problem
The existing vision detection systems face challenges in efficiently storing history information without excessive memory consumption and cycle time increase, necessitating a flexible storage solution.
Innovation Solution
A teaching device with a determination unit to assess storage conditions and a history storage unit to store vision detection results only when these conditions are met, utilizing a storage device for efficient data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all vision detection results are stored as history information, then complete historical data is available for analysis, but memory capacity consumption increases and cycle time increases
Solution Approach 1:
The patent extracts and stores only specific types of vision detection results that meet predetermined storage conditions (e.g., detection failures, abnormal cases, or statistically significant patterns) rather than all detection results. This selective extraction reduces memory capacity consumption while preserving the most valuable history information for analysis and improvement.
Solution Approach 2:
The system dynamically adjusts storage conditions based on detection accuracy metrics, time patterns, and error rates. By changing the parameters that determine what gets stored (such as storing only when detection accuracy falls below a threshold or when unusual patterns emerge), the system optimizes between data completeness and memory usage.
2Reliability
If all vision detection results are stored as history information, then complete historical data is available for analysis, but cycle time increases
Solution Approach 1:
By extracting only the most significant detection results based on predetermined conditions (such as detection failures, abnormal objects, or statistically relevant cases), the system reduces the amount of data processing required for storage operations, thereby reducing cycle time while maintaining the quality of historical data.
Solution Approach 2:
The system performs partial storage action by selectively storing only necessary history information rather than all detection results. This partial action approach suffices for achieving the goal of having useful historical data for analysis while avoiding the excessive time cost of storing and processing every single detection result.
3Quantity of substance
If storage conditions are made flexible for selective storage, then memory capacity consumption is reduced, but storage flexibility and adaptability must be managed
Solution Approach 1:
The system manages storage condition complexity by dynamically adjusting storage parameters based on detection performance metrics, time patterns, and error rates. This automated parameter adjustment reduces the need for manual configuration and management of storage conditions while achieving optimal memory usage.
Solution Approach 2:
The system uses feedback from detection results (such as accuracy metrics, error patterns, and statistical analysis) to automatically adjust storage conditions. This feedback mechanism allows the system to adapt storage strategies based on actual performance data, reducing memory consumption without requiring complex manual management of storage parameters.
Data Source
AI summary
Provided is a teaching device comprising a determination unit that determines whether or not a storage condition relating to the result of processing a designated object by a visual sensor is satisfied, and a history storage unit that stores history information indicating the result of processing into a storage device if the storage condition is determined to be satisfied.