Wind Turbine Component Self-Identification and Automatic Parameter Update
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Solution Overview
Problem
Current wind turbine systems lack an effective means to track and update data on specific components, particularly after replacement or maintenance, which affects efficient operation and maintenance scheduling.
Innovation Solution
A method and system that utilize identification sensors to transmit configuration data to a turbine controller, allowing for comparison with last-known data to determine component replacements and automatically update operational parameters and maintenance schedules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tracking methods are used for wind turbine components, then system complexity is reduced, but component identification accuracy and maintenance scheduling efficiency deteriorate
Solution Approach 1:
The identification sensor attached to each component enables the component to self-identify itself automatically. When the sensor is read by the control system, it provides component identification data without requiring manual intervention, achieving self-service tracking that improves accuracy while keeping the system simple
Solution Approach 2:
The patent replaces manual mechanical tracking methods with an automated sensing system. The identification sensor and reading mechanism substitute for manual record-keeping, providing automatic component identification that enhances precision without significantly increasing overall system complexity
2Reliability
If component replacement is not tracked, then operational continuity is maintained, but maintenance scheduling reliability deteriorates
Solution Approach 1:
The identification sensor provides continuous feedback to the control system about component status and replacement events. This automatic feedback mechanism ensures maintenance scheduling reliability by immediately notifying the system when components are replaced, eliminating delays associated with manual tracking
Solution Approach 2:
The system performs preliminary action by automatically detecting and recording component replacements before maintenance scheduling is affected. The control system proactively identifies replaced components through the sensor data, allowing maintenance schedules to be updated in advance rather than waiting for manual reports
3Productivity
If automated identification sensors are deployed, then component tracking accuracy improves, but device complexity and cost increase
Solution Approach 1:
The system segments the wind turbine into individual components, each with its own identification sensor. This segmentation allows targeted tracking of only critical components rather than the entire system, improving maintenance efficiency while limiting the increase in overall system complexity to essential areas only
Solution Approach 2:
The identification sensor serves multiple functions: it identifies the component type, tracks replacement events, and provides data for maintenance scheduling. This multi-functionality increases productivity by consolidating multiple tracking tasks into a single sensor system, offsetting the complexity increase through functional integration
Data Source
AI summary
A method for automatically updating data associated with a wind turbine based on component self-identification may generally include providing instructions for transmitting a polling signal to an identification sensor associated with a wind turbine component and, in response to the transmission of the polling signal, receiving current configuration data for the wind turbine component from the identification sensor. The method may also include comparing the current configuration data received from the identification sensor to last-known configuration data for the wind turbine component and automatically updating one or more parameter settings associated with operating the wind turbine based on any differences identified between the current configuration data and the last-known configuration data.