Industrial Machine Data Parsing by Collection Setting Identification
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Solution Overview
Problem
Current data collection systems for industrial machines lack efficient methods to identify and execute parse processing on collected data based on specific collection settings, leading to inefficiencies in data analysis and traceability.
Innovation Solution
A data collection system that includes circuitry to collect data from industrial machines, identify collection settings using machine IDs and topic IDs, and execute parse processing on the collected data to convert it into a usable format for analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is collected from industrial machines without structured identification and parse processing, then data collection is simple, but data analysis efficiency and traceability deteriorate
Solution Approach 1:
The patent segments data processing by introducing collection setting identification information that divides data into distinct categories based on machine type, collection purpose, and data format. This segmentation enables targeted parse processing for different data types, improving analysis efficiency without requiring a completely complex system architecture.
Solution Approach 2:
The patent applies preliminary action by performing parse processing immediately after data collection, converting raw data into structured formats before storage or analysis. This preliminary structuring of data with identification information embedded makes subsequent analysis more efficient while keeping the overall system manageable.
2Measurement precision
If generic data collection is performed without specific collection settings identification, then system operation is simple, but measurement precision and data usability deteriorate
Solution Approach 1:
The system implements self-service by automatically identifying the appropriate collection settings based on embedded identification information in the data packets. This automatic identification and selection of parse processing methods maintains ease of operation while achieving precise, targeted data collection without requiring manual configuration for each data type.
Solution Approach 2:
The patent changes the parameter of data structure by embedding collection setting identification information within the data packets themselves. This parameter change enables the system to distinguish between different data types and apply appropriate processing methods, improving measurement precision while maintaining operational simplicity through automatic recognition.
3Loss of information
If data is collected and stored without parse processing, then data storage is efficient, but data traceability and analytical value deteriorate
Solution Approach 1:
The patent extracts essential identification information from collection settings and embeds it directly into data packets during the collection process. This extraction of key identifiers enables traceability without requiring separate metadata storage systems, improving data traceability while minimizing additional processing energy requirements.
Data Source
AI summary
A data collection system for an industrial machine, the data collection system comprising circuitry configured to: collect collection data relating to the industrial machine based on a predetermined collection setting; identify the predetermined collection setting based on identification information associated with the collection data; and execute parse processing relating to the collection data based on the identified predetermined collection setting.