Dynamic Sampling Rate Adjustment for Industrial Controllers
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Solution Overview
Problem
Conventional industrial controllers have static sampling rates that fail to adapt to changing conditions in manufacturing processes, leading to delayed detection of malfunctions and inefficiencies.
Innovation Solution
Implement a system that dynamically determines and adjusts sampling rates based on real-time data analysis and historical data mining, using I/O ports and controllers to monitor conditions and update sampling rates automatically, allowing for more accurate data retention and simulation improvements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a static sampling rate is used in conventional industrial controllers, then device complexity is reduced and ease of operation is improved, but measurement precision deteriorates and reliability worsens when process conditions change
Solution Approach 1:
The patent implements dynamic sampling rate adjustment where the controller automatically modifies sampling rates based on real-time process conditions. The system transitions from static pre-defined sampling rates to dynamic adaptive sampling rates that respond to process changes, thereby maintaining measurement precision without compromising ease of operation.
Solution Approach 2:
The system employs feedback mechanisms by continuously monitoring process data and using this information to adjust sampling rates. The controller analyzes process variability and feedback signals to determine when increased sampling is necessary, enabling automatic adaptation to changing conditions while maintaining operational simplicity.
2Device complexity
If a static sampling rate is used, then device complexity is reduced, but reliability deteriorates when process conditions alter drastically
Solution Approach 1:
The controller dynamically adjusts sampling rates based on process conditions, transitioning from fixed static rates to adaptive dynamic rates. This enables the system to maintain reliability during drastic process changes by increasing sampling frequency when needed, while keeping the overall device architecture relatively simple through automated decision-making.
Solution Approach 2:
The system performs self-adjustment by automatically monitoring process conditions and modifying sampling rates without external intervention. The controller serves itself by making real-time decisions about data acquisition strategies, thereby maintaining reliability during process upsets without requiring complex external control systems.
3Adaptability or versatility
If manual determination of sampling rates is used, then adaptability is reduced, but ease of operation is improved
Solution Approach 1:
The system automatically determines and adjusts sampling rates based on process conditions without requiring manual operator intervention. The controller self-manages the sampling rate configuration by analyzing process data and making adaptive decisions, thereby achieving both high adaptability to changing conditions and ease of operation through automation.
Solution Approach 2:
The system uses feedback from process monitoring to automatically adjust sampling rates. By continuously analyzing process variability and condition changes, the controller adapts sampling strategies in real-time, achieving adaptability to diverse process conditions while maintaining ease of operation through automated decision-making rather than manual configuration.
Data Source
AI summary
A system that facilitates determination of a sampling rate to utilize in connection with sampling data in an industrial environment comprises a receiver component that receives data from an I/O port of a controller. An analysis component automatically and dynamically determines a rate at which data associated with the I/O port is to be sampled based at least in part upon the received data. The system can further comprise a sampling component that samples data at the rate determined by the analysis component.