Turbine Generator Fault Detection via Synchronous Sampling
Solution Overview
Problem
Existing fault detection methods for wind turbine generators face challenges in accurately identifying faults due to varying shaft rotating frequencies and low signal-to-noise ratios in current measurements, making it difficult to extract fault signatures using traditional frequency spectrum analysis.
Innovation Solution
The method involves synchronously sampling current signals to convert variable fault characteristic frequencies into constant values, using frequency and amplitude demodulation, and impulse detection to identify faults in the frequency spectrum, allowing for the detection of faults such as blade imbalances and bearing defects without additional sensors or data acquisition devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional frequency spectrum analysis is used to detect faults in wind turbine generators, then the analysis method is simple and well-developed, but the varying shaft rotating frequency causes fault characteristic frequencies to vary, making it difficult to extract fault signatures
Solution Approach 1:
The patent transforms the non-stationary current signal into a stationary signal by changing the parameter of signal representation. Specifically, it uses synchronous sampling to resample the current signal at rates synchronized with the shaft rotating frequency, converting variable fault characteristic frequencies into constant frequencies in the resampled domain, enabling effective fault signature extraction
Solution Approach 2:
The patent introduces an intermediary transformation process between the original current signal and frequency spectrum analysis. The synchronous sampling acts as an intermediary that converts the non-stationary signal into a stationary form, allowing traditional frequency analysis methods to effectively detect faults in variable-speed operating conditions
2Reliability
If sensors and data acquisition devices are installed to monitor wind turbine operation for fault detection, then fault detection capability is improved, but the sensors are subject to failure due to poor working conditions, causing additional problems with system reliability and maintenance costs
Solution Approach 1:
The patent applies the self-service principle by using the wind turbine generator's own current signal for fault detection. The existing current measurements, which are already part of the generator's operation, are analyzed to detect faults in the generator itself, eliminating the need for separate sensors and data acquisition devices that would be exposed to harsh working conditions
Solution Approach 2:
The patent makes the current measurement system multi-functional by using it both for its original purpose (monitoring generator operation) and for fault detection. The current signal serves dual functions: controlling generator operation and providing fault signature information, thereby eliminating the need for additional dedicated fault detection sensors
3Measurement precision
If synchronous sampling is used to convert variable fault characteristic frequencies into constant values, then fault detection accuracy under non-stationary conditions is improved, but the signal processing complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the signal processing into distinct stages: first estimating the shaft rotating frequency, then using this estimation to determine synchronous sampling rates, and finally performing frequency spectrum analysis on the resampled signal. This segmented approach manages complexity by breaking down the overall processing task into manageable steps
Data Source
AI summary
Turbine generator faults can be detected by receiving a current signal from the turbine generator, and synchronously sampling the current signal to obtain a set of current signal samples that are evenly spaced in the phase domain, in which phase differences between adjacent current signal samples in the set of current signal samples are substantially the same. The process includes generating a frequency spectrum of the current signal samples, identifying one or more excitations in the frequency spectrum, and detecting a fault in the turbine generator based on the one or more excitations in the frequency spectrum.