Monitoring System with Dynamic Model Selection for Equipment Condition
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Solution Overview
Problem
Existing monitoring systems face challenges in accurately determining the condition of equipment due to changes in the state of detectors and environmental conditions, leading to incorrect evaluations and unnecessary model updates.
Innovation Solution
A monitoring system that uses a processor to perform first and second determinations based on different models, where the choice of model is decided by the state of the detector or environment, reducing calculation for model updates and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single model is used for equipment condition determination, then the system is simple to operate, but accuracy decreases when detector state or environment changes
Solution Approach 1:
The system dynamically selects between multiple models based on the current state of the detector or environment. Instead of using a fixed single model, the system adapts the model choice to match current operating conditions, thereby maintaining high accuracy across varying states without requiring a complex manual configuration system
Solution Approach 2:
The system changes the model parameter (which model to use) based on detected state parameters. When the detector state or environment changes, the system switches to an appropriate model that is optimized for those conditions, effectively using parameter changes to resolve the accuracy-complexity contradiction
2Measurement precision
If multiple models are maintained for different states, then determination accuracy improves, but calculation load and update frequency increase
Solution Approach 1:
The system segments the operating space into distinct states (e.g., normal detector state, degraded detector state, different environmental conditions) and assigns specific models to each segment. This segmentation allows the system to use multiple specialized models only when needed for specific states, rather than continuously processing with all models, thereby reducing overall calculation load while maintaining high accuracy for each state
Solution Approach 2:
The system applies partial action by selecting and using only the necessary model for the current state rather than continuously updating and processing with all possible models. This selective approach reduces calculation resource consumption while maintaining determination accuracy by using the appropriate model for each specific condition
Data Source
AI summary
According to one embodiment, a monitoring system includes a processor. The processor accepts first data output from a first detector. The first detector detects a signal caused by equipment. The processor performs a first determination when a first value is in a first state. The first value indicates a state of the first detector or an environment where the equipment is provided. The first determination determines a condition of the equipment by using a first model and the first data. The processor performs a second determination when the first value is in a second state different from the first state. The second determination determines the condition of the equipment by using a second model and the first data. The second model is different from the first model.