Cloud Field Device Data Logging for Unified Diagnosis and Calibration
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Solution Overview
Problem
Current methods for storing and evaluating data related to device state, diagnosis, and calibration of field devices in automation technology lack an integrated and efficient way to combine internal and external data for comprehensive representation and evaluation.
Innovation Solution
A method that involves both internal and external data registration and transfer of field device data to a cloud, allowing for the storage and evaluation of device state, diagnosis, and calibration data, enabling a unified overview by combining device-internal self-monitoring data with external service computer data, and providing tools for graphical representation and statistical analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If device-internal self-monitoring functionality is used to register first data, then device operation monitoring is improved, but data completeness for comprehensive evaluation is insufficient
Solution Approach 1:
The patent combines device-internal self-monitoring data (first data) with external service computer data (second data) by transferring both to a centralized cloud platform. This merging of data sources from different monitoring locations creates a complete data set that preserves the reliability benefits of self-monitoring while achieving comprehensive data completeness for evaluation.
2Loss of information
If external service computer is used to register second data, then data completeness is improved, but integration with device-internal data is lacking
Solution Approach 1:
The patent introduces a cloud platform as an intermediary that receives data from both the field device (first data) and the external service computer (second data). This intermediary consolidates data from multiple sources into a single centralized location, achieving data completeness while simplifying integration by providing a unified access point rather than requiring direct complex connections between all data sources.
3Ease of operation
If data is stored locally in field device, then data availability is improved, but comprehensive evaluation capability is limited
Solution Approach 1:
The patent transitions data storage and processing from a single-dimensional local device level to a multi-dimensional architecture that includes both local availability (field device) and centralized analysis (cloud platform). This dimensional change allows data to be accessible locally for immediate operations while simultaneously being available in the cloud for comprehensive cross-device and cross-environment evaluation, thus achieving both data availability and enhanced evaluation capability.
4Device complexity
If self-test and calibration data are stored separately, then data management simplicity is improved, but systematic issue detection is hindered
Solution Approach 1:
The patent merges self-test data and calibration data (both first data from device and second data from external service) into a unified cloud-based data structure. This consolidation maintains simple data management through centralized storage while enabling systematic issue detection by allowing cross-referencing and pattern analysis across all data types from multiple devices in a unified environment.
Data Source
AI summary
A method for storing data for at least one of a device state, device diagnosis and calibration of a field device in a cloud, with the field device having a self-monitoring functionality. The method includes device-internal registering of first data for at least one of a device state, device diagnosis and calibration by the field device and transfer of the device-internally registered first data from the field device to the cloud. Moreover, the method includes registering second data for at least one of a device state, device diagnosis and calibration of the field device using an external service computer and transferring the second data from the external service computer to the cloud. Both the first data as well as also the second data are stored in the cloud.