Analysis Apparatus Self-Diagnostics Between Observation Periods
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Solution Overview
Problem
Existing systems for monitoring analysis apparatuses only share information without analyzing or examining it, making it difficult to maintain the state of the apparatus effectively.
Innovation Solution
A monitoring method and apparatus that acquire self-diagnostic data during periods when the analysis apparatus is not observing a target object, diagnose the state based on this data, and output a diagnostic result, allowing for easy maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If self-diagnostic data is acquired during observation period, then monitoring can be performed continuously, but observation results will be affected by diagnostic operations
Solution Approach 1:
The patent segments the operational timeline into distinct observation periods and self-diagnostic periods. The analysis apparatus alternates between these two modes, acquiring self-diagnostic data during intervals when observation is not occurring. This temporal segmentation allows both monitoring reliability and observation quality to be maintained without interference.
Solution Approach 2:
The system performs self-diagnostic data acquisition in advance during idle periods before observation begins. By completing diagnostic operations beforehand, the apparatus ensures that no diagnostic interference occurs during the actual observation period, thus maintaining observation result integrity while still achieving continuous monitoring capability.
2Device complexity
If information is only shared without analysis, then system complexity is reduced, but maintenance effectiveness deteriorates
Solution Approach 1:
The analysis apparatus performs self-diagnosis by automatically acquiring self-diagnostic data and generating diagnostic results without requiring external intervention. This self-service capability maintains system simplicity while significantly improving maintenance effectiveness, as the apparatus monitors its own state and provides actionable diagnostic information for maintenance decisions.
Solution Approach 2:
The system implements a feedback loop where self-diagnostic data is continuously collected, analyzed, and used to generate diagnostic results that inform maintenance actions. This feedback mechanism transforms raw operational data into actionable insights, enhancing maintenance effectiveness while keeping the system architecture relatively simple through automated processing.
Data Source
AI summary
A monitoring method for monitoring an analysis apparatus configured to observe a target object includes acquiring self-diagnostic data on the analysis apparatus outside an observation period of the target object by the analysis apparatus, diagnosing the state of the analysis apparatus based on the self-diagnostic data, and outputting a diagnostic result of the state of the analysis apparatus.


