Cloud Storage of Field Device Status and Calibration Data
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Solution Overview
Problem
Current methods for storing and evaluating data related to device status, diagnosis, and calibration of field devices in automation technology lack an efficient and integrated approach for combining internal and external data for comprehensive monitoring and documentation.
Innovation Solution
A method that involves field devices acquiring and transmitting internal data on device status, diagnosis, and calibration, while external service computers also record and transmit related data, with both types of data being stored and merged in the cloud for joint display and evaluation, using identifiers for field devices to facilitate data association and retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If field devices independently transmit application information and parameter sets to the cloud, then optimal parameter sets can be created using big data algorithms, but the data completeness is insufficient without external service data
Solution Approach 1:
The patent combines internally acquired device data with externally acquired service data into a unified cloud-based data structure. Both data sources are merged in the cloud, allowing comprehensive device monitoring while distributing the complexity across multiple independent data collection channels rather than requiring a single complex integrated system at the device level.
Solution Approach 2:
The cloud serves as an intermediary that receives and integrates data from both the field device and external service computers. This mediator approach allows data from different sources to be combined without requiring direct integration between the device and external services, simplifying the overall system architecture.
2Measurement precision
If only internal self-monitoring data is used, then the system is simple to operate, but the credibility and accuracy of device status assessment is limited
Solution Approach 1:
The system implements feedback by comparing internally acquired device data with externally acquired service data. This cross-validation feedback mechanism enhances the accuracy and credibility of device status assessments, while the automated nature of the feedback process maintains operational simplicity.
3Reliability
If comprehensive data from multiple sources is collected and stored in the cloud, then chronological documentation and cross-site evaluation are enabled, but the system complexity and data management burden increase
Solution Approach 1:
The cloud-based data structure is designed to serve multiple functions: storing device data, storing service data, enabling chronological documentation, supporting cross-site evaluation, and facilitating device identification through unique identifiers. This universal data structure handles diverse data management needs through a single integrated system.
Data Source
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AI summary
The invention relates to a method for storing data relating to at least one of device status, device diagnosis and calibration of a field device in a cloud. The field device (8, 9, 10) comprises a self-monitoring functionality. The method comprises the local-mode detection of first data relating to at least one of device status, device diagnosis and calibration by the field device itself, and the transmission of the local-mode-detected first data from the field device to the cloud (13). The method also comprises the detection of second data relating to at least one of device status, device diagnosis and calibration of the field device by means of an external service computer (16), and the transmission of the second data from the external service computer to the cloud. Both the first data and the second data are stored in the cloud.