Process Value Archiving with Tolerance Band Filtering
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Solution Overview
Problem
Current methods for archiving process values in process automation are storage-intensive and inefficient, as they require large storage spaces and slow down during data retrieval due to the use of either lossy compression methods that lose information or lossless methods that are computationally intensive, making it difficult to achieve both loss-free storage and fast data access.
Innovation Solution
A method that records process values as raw data and checks them against a tolerance band, storing only data within that band in its original format, compressing it later with a time delay, allowing for lossless compression and fast unpacking, using a history server with real-time functions and a caching system to optimize storage and retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If lossless compression methods are used to preserve all original information, then data integrity is improved, but decompression speed deteriorates and becomes too slow for many process automation applications
Solution Approach 1:
The patent changes the parameter of compression approach by applying lossless compression selectively only to data exceeding the tolerance band, while data within the band is handled through tolerance-based filtering. This parameter change in compression strategy resolves the contradiction by making compression optional rather than universal, thereby improving both data integrity for critical values and processing speed for normal variations.
Solution Approach 2:
The patent applies different quality levels of data processing to different portions of the data stream. Data within the tolerance band is processed with tolerance-based filtering (lower quality requirement), while data exceeding the band undergoes lossless compression (higher quality requirement). This local differentiation resolves the contradiction by applying compression only where necessary for data integrity, improving overall decompression speed while maintaining integrity where needed.
2Productivity
If lossy compression methods are used to achieve fast decompression, then decompression speed is improved, but data accuracy deteriorates and information is lost
Solution Approach 1:
The patent introduces a tolerance band parameter that defines the acceptable range for data approximation. By changing the compression parameter from fixed lossy or lossless modes to a dynamic tolerance-based approach, the system achieves fast decompression for data within the tolerance band while preserving accuracy for data exceeding it, thus resolving the contradiction between speed and accuracy.
Solution Approach 2:
The patent applies partial compression action by using tolerance-based filtering for data within the acceptable range and reserving lossless compression only for data exceeding the tolerance band. This partial application of compression strategies resolves the contradiction by achieving fast processing for the majority of data points while maintaining accuracy for critical outliers.
3Speed
If raw data is stored in uncompressed format to enable fast reading, then data access speed is improved, but storage space requirements deteriorate and become excessively large
Solution Approach 1:
The patent changes the storage parameter from uncompressed raw format to a hybrid format where data within the tolerance band is stored in a compressed representation while only exceeding values are stored in full lossless format. This parameter change resolves the contradiction by reducing storage space requirements through selective compression while maintaining fast access capability for the majority of data points.
Solution Approach 2:
The patent discards redundant information by not storing data points that fall within the tolerance band in full detail, instead representing them through the tolerance threshold. The full precision is recovered only for data points exceeding the tolerance band. This discarding and selective recovery approach resolves the contradiction between storage space and access speed.
4Quantity of substance
If tolerance band filtering is applied to reduce storage needs, then storage efficiency is improved, but data precision deteriorates for billing-relevant calculations
Solution Approach 1:
The patent applies different precision levels locally to different data portions. Data within the tolerance band is stored with reduced precision (through tolerance-based representation), while data exceeding the band is stored with full precision using lossless compression. This local quality differentiation resolves the contradiction by improving storage efficiency for normal variations while maintaining billing-relevant precision for critical values.
Solution Approach 2:
The patent changes the precision parameter dynamically based on whether data points fall within or exceed the tolerance band. This parameter change resolves the contradiction by allowing reduced precision storage for the majority of data while ensuring full precision is maintained for billing-relevant calculations that involve data exceeding the tolerance threshold.
Data Source
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AI summary
The invention relates to a method and a system for the loss-free processing of process values which are integrated into a process control system of a technical installation or of a technical process. The method and system according to the invention are characterized in that the process values are acquired as raw data by means of an acquisition unit. A physical unit and a measuring range are associated with the respective process value and the acquired raw data are used to generate archivable data. The archivable data in a predetermined tolerance range are selected by means of an archive function and are stored in a history server in a raw data format.