Wind Turbine Cog Belt Fatigue Detection from Pitch Angle Signals
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Solution Overview
Problem
The cog belt in wind power generator sets experiences significant fatigue due to long-term operation, leading to potential failure and loss of control, necessitating an effective detection method to prevent accidents.
Innovation Solution
A method and apparatus for detecting cog belt fatigue by acquiring pitch angles, signal characteristic values, and performing statistical analysis to determine if the cog belt is in a fatigue state, using a proximity switch to feed back signal values and compare them to predetermined thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional detection methods are used for cog belt fatigue, then detection accuracy may be improved, but detection cost and system complexity increase
Solution Approach 1:
The cog belt's own operational parameters (pitch angles, signal characteristic values) are used for self-diagnosis of fatigue state. The system monitors the cog belt's inherent operational data without requiring external specialized sensors or complex detection equipment, enabling the component to detect its own condition through its normal operational signatures.
Solution Approach 2:
The patent uses pitch angles and signal characteristic values as intermediary parameters to indirectly assess cog belt fatigue. Instead of directly measuring fatigue or using complex vibration analysis, the system employs these readily available operational parameters as mediators to infer the fatigue state, simplifying the detection mechanism while maintaining effectiveness.
2Reliability
If advanced detection systems are implemented, then reliability of cog belt monitoring is improved, but cost of implementation increases
Solution Approach 1:
The detection system utilizes existing operational parameters (pitch angles and signal characteristic values) that serve multiple functions in the wind power generator's normal operation. By repurposing these existing data streams for fatigue detection, the system achieves reliable monitoring without requiring specialized expensive equipment, making the solution economically viable while maintaining high reliability.
Solution Approach 2:
The system continuously monitors pitch angles and signal characteristic values, compares them against threshold values, and provides real-time feedback on the cog belt's fatigue state. This continuous feedback mechanism ensures reliable detection of fatigue conditions, enabling timely maintenance decisions while using simple, cost-effective comparison logic rather than complex analysis algorithms.
3Reliability
If real-time monitoring is implemented, then safety of wind power generator set is improved, but operational complexity increases
Solution Approach 1:
The system provides real-time safety monitoring by continuously comparing current pitch angles and signal characteristic values against predetermined threshold values. When thresholds are exceeded, the system immediately indicates potential fatigue issues, enabling timely safety interventions. This simple feedback mechanism achieves effective real-time safety monitoring without requiring complex operational procedures or manual analysis.
Solution Approach 2:
The monitoring system operates autonomously by automatically collecting pitch angle data, calculating signal characteristic values, comparing them against thresholds, and generating fatigue assessments without requiring manual intervention. This self-service operation maintains high safety standards through continuous real-time monitoring while keeping operational complexity low through automated decision-making logic.
Data Source
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AI summary
A method for detecting fatigue state of cog belt of wind power generator set is provided, including acquiring pitch angles satisfying preset condition, acquiring signal characteristic values corresponding to the pitch angles, selects from the pitch angles according to acquisition timing sequence of signal characteristic values pitch angles at which signal characteristic value changes, performing characteristic statistics on selected pitch angles to acquire characteristic statistic value and determining whether the cog belt is in fatigue state by comparing characteristic statistic value with predetermined threshold. The method can achieve detection of fatigue state of cog belt in service without auxiliary detection device and hardware measure, with stronger instantaneity and low cost. The method is easily implemented with low-complexity algorithm and thus better applicability. An apparatus and system for detecting fatigue state of cog belt of wind power generator set are further provided to ensure application and achievement of above method practically.