Abnormal Condition Diagnosis Using Boolean Logic and Acquisition Difficulty
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Solution Overview
Problem
Existing sequential diagnosis techniques for complex systems like nuclear power plants struggle to accurately diagnose abnormal conditions under advanced control environments due to masking effects and interactions, as they do not consider Boolean logic and face acquisition difficulties with varying symptom complexities across multiple layers of computer screens.
Innovation Solution
An apparatus and method that quantify acquisition difficulties of abnormal symptoms using excess entropy techniques, calculate distinctiveness, and apply Boolean logic to diagnose conditions efficiently, even in advanced control environments where symptoms are displayed on multiple layers of a computer screen.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sequential diagnosis technique is used without considering Boolean logic, then the diagnosis sequence can be determined, but the correct picture of abnormal symptoms is distorted due to masking effects and interactions
Solution Approach 1:
The patent applies feedback by continuously updating the diagnosis process based on observed abnormal symptoms and their Boolean relationships. The system monitors the system state, compares it with the binary tree diagnosis model, and adjusts the diagnosis path based on feedback from symptom observations, thereby resolving masking effects and improving diagnosis accuracy while maintaining efficiency.
Solution Approach 2:
The patent performs preliminary action by pre-establishing a binary tree diagnosis model that incorporates Boolean logic relationships between abnormal symptoms before actual diagnosis occurs. This pre-prepared diagnostic framework allows the system to quickly evaluate multiple symptom combinations and identify the correct abnormal condition without being distorted by masking effects during the diagnosis process.
2Adaptability or versatility
If all measuring devices are displayed at the same physical level in conventional control environment, then the diagnosis technique can be applied, but it cannot be applied in advanced control environment where devices are on various layers of computer screen with different acquisition difficulties
Solution Approach 1:
The patent applies parameter changes by introducing a new parameter called 'acquisition difficulty' that quantifies the complexity of observing abnormal symptoms in advanced control environments. This parameter varies based on the screen configuration, layer depth, and visual distinctiveness of measuring devices. By incorporating this parameter into the diagnosis model, the system adapts to different control environments while accounting for the varying complexity of symptom acquisition.
3Loss of information
If too many entities are displayed on a single screen or there are colors, flashing lights on the screen, then the user feels higher demand due to acquisition difficulty of information
Solution Approach 1:
The patent introduces and applies the 'acquisition difficulty' parameter that specifically measures how hard it is for users to observe abnormal symptoms given the screen configuration. This parameter captures the impact of multiple entities, colors, and flashing lights on information acquisition. By using this parameter in the diagnosis model, the system compensates for the increased acquisition difficulty and maintains accurate diagnosis even in complex visual environments.
Data Source
AI summary
The present invention discloses an apparatus and a method for diagnosing abnormal conditions, that quantitatively considers acquisition difficulties between abnormal symptoms provided on a computer screen and quantifies acquisition difficulties of the abnormal symptoms through distinctiveness of measuring devices to exactly diagnose the abnormal conditions even under an improved control environment, making it possible for a user to rapidly and easily diagnose the abnormal conditions that may be generated from a complicated device.With the present invention, the abnormal conditions are diagnosed using the sequential diagnosis technique and the Boolean logic between the abnormal symptoms, making it possible to effectively diagnose the abnormal conditions even under masking effects that may be generated between the abnormal symptoms.