Power Converter Parameter Tuning via Remote Usage Analysis
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Solution Overview
Problem
Industrial automation devices, such as frequency converters, face challenges in optimizing control parameters due to limitations in local computational power and the need for remote reprogramming, which restricts real-time data processing and feedback for efficient operation.
Innovation Solution
A method and system for communicating automation device data between local and remote network nodes, enabling data processing and feedback to optimize device usage, where data is sent from the device to a server, processed, and optimal parameters are sent back for local implementation, using wireless communication systems like LTE, Bluetooth, or WiFi, allowing for remote optimization algorithm updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If data processing is performed locally in the industrial automation device, then real-time optimization is improved, but the device complexity and computational requirements increase
Solution Approach 1:
The system divides data processing into two segments: local real-time processing for immediate optimization needs, and remote cloud-based processing for comprehensive analysis. This segmentation allows the device to maintain real-time responsiveness while offloading complex computational tasks to reduce local device complexity.
Solution Approach 2:
A communication interface acts as an intermediary between the industrial automation device and the cloud server. This intermediary manages data exchange, allowing the device to access remote processing capabilities without directly integrating complex computational infrastructure, thus reducing device complexity while maintaining real-time optimization.
2Ease of repair
If optimization algorithms are updated remotely, then ease of maintenance is improved, but reliability of parameter optimization may be worsened due to communication dependencies
Solution Approach 1:
The system downloads and stores optimization algorithms and parameter sets in advance during periods when the device is not in critical operation. This preliminary action ensures that updated algorithms are available locally for immediate execution, maintaining reliability even when communication with the remote server is interrupted during operation.
Solution Approach 2:
The device is designed to autonomously execute stored optimization algorithms and adjust parameters without requiring continuous remote verification. This self-service capability ensures that parameter optimization continues reliably even when communication dependencies prevent real-time updates, while still allowing easy maintenance through remote algorithm distribution.
3Measurement precision
If more data is transmitted to the server, then measurement precision is improved, but loss of information due to transmission constraints is worsened
Solution Approach 1:
The system extracts and transmits only the most critical and relevant data parameters to the remote server for analysis, rather than transmitting all available data. This selective extraction maintains measurement precision for key parameters while reducing overall data transmission volume, thereby minimizing information loss due to transmission constraints.
Solution Approach 2:
Different data processing strategies are applied to different types of data based on their importance. Critical operational parameters are transmitted with high precision to the server, while less critical data is processed locally or transmitted with reduced precision. This local quality approach optimizes the balance between measurement precision and transmission efficiency.
Data Source
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AI summary
A method comprises storing (201), in an automated power conversion device (101), operational information on the usage of the automated power conversion device (101), and information on user-adjustable parameter settings of the automated power conversion device (101). A local terminal device (105) receives (203) the operational information and the information on the user-adjustable parameter settings from the automated power conversion device (101), and forwards (204) said information to a remote network node (109) via a communications network. The received information is analyzed (205) in the remote network node (109), and based on the analysis the remote network node generates (205) a recommendation on an optimal set of user-adjustable parameters regarding the automated power conversion device (101). The generated recommendation is transmitted (206) from the remote network node (109) and received (207) in the local terminal device (209).