Turbine Farm Data Visualization and Normalization
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Solution Overview
Problem
Wind turbine farm operators face difficulties in extracting and visualizing key information from the large amounts of data collected, particularly in identifying the health of turbines and their components, due to issues with false alarms from vibration analysis and lack of discrimination between indicative and non-indicative vibrations.
Innovation Solution
A system comprising a computing device and a computer-readable medium that normalizes and arranges operational data into arrays for graphical representation, allowing for visualization of turbine performance over time, with features like radar and polar plots, and the use of pattern recognition algorithms to generate alarms and identify potential issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vibration threshold is set low to detect damage, then measurement precision improves, but false alarms increase
Solution Approach 1:
The patent applies local quality by normalizing vibration data individually for each turbine based on its specific operational characteristics and historical patterns, rather than applying a uniform threshold across all turbines. This allows each turbine to have its own optimized detection sensitivity while maintaining overall system reliability.
Solution Approach 2:
The system performs preliminary action by establishing baseline vibration patterns and normalizing thresholds for each turbine before actual damage detection begins. This preliminary characterization of normal operation allows the system to distinguish between normal variations and actual damage indicators, reducing false alarms while maintaining sensitivity.
2Loss of information
If data collection is comprehensive to capture all operational parameters, then information completeness improves, but data processing complexity increases
Solution Approach 1:
The patent extracts and visualizes only the key information that wind farm operators need - specifically normalized operational parameters and deviation patterns - while filtering out the vast amount of raw data. This extraction of essential information maintains completeness of relevant data while dramatically reducing processing complexity through focused visualization of normalized arrays.
3Reliability
If traditional vibration thresholding is used to minimize false alarms, then reliability improves, but measurement precision deteriorates
Solution Approach 1:
The system performs preliminary normalization of vibration data for each turbine based on its operational history and characteristics before damage detection. This preliminary action establishes turbine-specific baseline patterns that enable both high reliability in distinguishing normal from abnormal vibrations and high precision in detecting actual damage conditions.
Solution Approach 2:
The patent changes the parameter used for vibration assessment from fixed absolute thresholds to normalized relative measures that account for each turbine's operational state. By transforming the vibration parameter into a normalized deviation from expected patterns, the system achieves both high reliability in false alarm reduction and high precision in damage detection.
Data Source
AI summary
A system for operating a wind or water turbine farm comprising a plurality of turbines comprising: a computing device; means for providing operational data relating to the plurality of turbines to the computing device; a computer-readable medium coupled to the computing device and having instructions stored thereon which, when executed by the computing device, causes the computing device to: arrange the operational data for each turbine into an array comprising operational data and having a first dimension corresponding to the plurality of turbines; generate a graphical user interface; generate within the graphical user interface a graphical representation of the array.