Rotary Shaft Coupling Slip Classification for False Alarm Reduction
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Solution Overview
Problem
Current wind turbine systems require visual inspection to diagnose slip faults in shaft couplings, leading to unnecessary shutdowns and significant losses due to high false alarm rates, with approximately 80% of triggered slip faults being non-actual slip events.
Innovation Solution
A method and system utilizing a controller to monitor sensor signals for faults in the shaft coupling, employing classification parameters to differentiate between actual slip and no-slip events, estimating slip magnitude, and implementing control actions based on the actual slip detected, using machine learning algorithms and sensor data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If visual inspection is used to diagnose slip faults, then fault detection is performed, but false alarm rate increases and unnecessary shutdowns occur
Solution Approach 1:
The patent replaces manual visual inspection with an automated sensor-based detection system. Multiple sensors monitor coupling conditions and feed data to a controller that automatically determines slip events, eliminating the need for manual inspection and reducing false alarms that cause unnecessary shutdowns.
Solution Approach 2:
The system enables self-diagnosis of slip faults through automated sensor monitoring and controller analysis. The controller independently evaluates sensor data to detect actual slip events, allowing the system to self-identify problems without requiring external inspection, thereby reducing false alarms and maintaining productivity.
2Measurement precision
If automated sensor monitoring is implemented, then detection accuracy improves, but system complexity increases
Solution Approach 1:
The patent divides the detection system into separate functional components: multiple sensors monitor different aspects of coupling conditions, and a controller processes this segmented data to determine slip events. This modular segmentation improves measurement precision while managing system complexity through functional separation.
Solution Approach 2:
The controller serves multiple functions: it receives data from various sensors, processes the information, determines slip events, and can trigger appropriate responses. This multi-functionality consolidates complexity into a single component that handles multiple tasks, improving detection accuracy without proportionally increasing overall system complexity.
Data Source
AI summary
A method for detecting actual slip in a coupling of a rotary shaft, for example, in a wind turbine power system, includes monitoring, via a controller, a plurality of sensor signals relating to the coupling for faults. In response to detecting a fault in the plurality of sensor signals relating to the coupling, the method includes determining, via the controller, whether the fault is indicative of an actual slip or a no-slip event of the coupling using one or more classification parameters. When the fault is indicative of the actual slip, the method includes estimating, via the controller, a magnitude of the actual slip using the plurality of sensor signals and a time duration of the actual slip. Further, the method includes implementing, via the controller, a control action based on the magnitude of the actual slip in the coupling.