Flow Path Sensor Data Reduction Through Time-Series Similarity
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Solution Overview
Problem
Current data management systems in industrial plants face challenges in efficiently reducing data volume for target sensors without compromising data integrity, especially when measurement data from upstream or downstream sensors shows similarity, leading to unnecessary data storage and processing burdens.
Innovation Solution
A data management system that acquires and records measurement data from multiple sensors, reduces data volume by comparing time-series changes between sensors, and selectively deletes or reduces data based on similarity, ensuring efficient storage and real-time control capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If measurement data from all sensors is recorded without reduction, then data integrity is maintained, but storage burden and processing time increase significantly
Solution Approach 1:
The patent creates a virtual copy of sensor data through estimation algorithms. When upstream or downstream sensor data shows similar time-series patterns, the system generates estimated data copies that replicate the characteristics of target sensor data without requiring actual storage of all raw measurements, thus reducing storage burden while maintaining analytical integrity
Solution Approach 2:
The system changes the parameter representation of sensor data by transforming raw measurement data into estimated data through mathematical modeling. This parameter transformation allows the system to represent the same physical phenomena using computed values that occupy less storage space while preserving the essential information needed for process analysis
2Productivity
If data volume reduction is applied to all sensors, then storage efficiency improves, but data quality and control accuracy may deteriorate
Solution Approach 1:
The patent applies data reduction selectively rather than uniformly across all sensors. The system evaluates the similarity between upstream/downstream sensor data and target sensor data on a case-by-case basis, applying estimation-based reduction only when similarity thresholds are met, thereby maintaining high data quality for critical measurements while achieving storage efficiency for redundant data
Solution Approach 2:
The system applies partial data reduction by maintaining full-resolution data for certain critical time periods or sensor types while applying compression and estimation techniques for other data sets. This partial action approach ensures that sufficient data quality is preserved for control decisions while achieving overall storage efficiency improvements
3Quantity of substance
If similar data from upstream or downstream sensors is used for reduction, then storage requirements decrease, but complexity of data processing increases
Solution Approach 1:
The patent performs preliminary similarity assessment between upstream/downstream sensor data and target sensor data before committing to data reduction strategies. By pre-evaluating time-series pattern matching and correlation metrics, the system determines which data sets are suitable for estimation-based reduction, thereby managing processing complexity through structured preliminary analysis rather than ad-hoc processing
Data Source
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AI summary
Provided a data management system which includes a data acquisition unit that acquires measurement data obtained by measuring a fluid flowing in a flow path from each of a plurality of sensors, a data recording unit that records the acquired measurement data, and a data volume reduction unit that reduces a data volume to be recorded for a target sensor based on the measurement data acquired from another sensor installed in either an upstream or a downstream from itself in the flow path among the plurality of sensors.