Arc Fault Detection Using Signal-to-Noise Ratio Analysis
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Solution Overview
Problem
Existing arc fault detection technologies in electrical switch apparatuses are inadequate in accurately distinguishing between signal and noise components of electrical current, leading to potential false positives and inefficiencies in interrupting hazardous arcs.
Innovation Solution
An electrical switch apparatus equipped with a current sensor and controller that computes an estimated signal-to-noise ratio by sampling current, identifying the fundamental frequency, and activating the switch when the ratio falls below a predetermined threshold, using a method that iteratively narrows frequency ranges and employs Golden ratio sub-bands to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional arc fault detection methods are used, then arc faults can be detected, but false positives occur due to inability to distinguish signal from noise components
Solution Approach 1:
The current signal is segmented into distinct components: fundamental frequency component, harmonic components, and noise component. This segmentation allows the system to analyze each component separately and compute signal-to-noise ratios for accurate arc fault detection without false positives from noise interference.
Solution Approach 2:
A signal-to-noise ratio computation mechanism serves as an intermediary between raw current measurements and arc fault detection decisions. This intermediary process separates signal components from noise components through spectral analysis and computes their ratio, providing a reliable basis for detection that eliminates false positives.
2Measurement precision
If signal-to-noise ratio computation with iterative frequency narrowing is used, then detection accuracy improves, but processing time increases
Solution Approach 1:
The system performs preliminary action by pre-identifying the fundamental frequency of the electrical current before conducting the full signal-to-noise ratio computation. This preliminary frequency identification narrows the search range for harmonic components, reducing the computational burden and processing time while maintaining detection accuracy.
Solution Approach 2:
The frequency analysis is segmented into iterative stages with narrowing bandwidths. The system first identifies the fundamental frequency, then progressively narrows the frequency range in iterations to locate harmonic components. This segmented approach reduces the total computational scope compared to analyzing the entire frequency spectrum at once.
Data Source
AI summary
The present disclosure relates to arc fault detection in an electrical switch apparatus. In aspects of the present disclosure, an arc fault electrical switch apparatus includes a conductive path, a switch configured to interrupt electrical current in the conductive path, a current sensor in electrical communication with the conductive path and configured to measure the electrical current to provide current measurements, and a controller. The controller is configured to execute instructions to sample the current measurements to provide current samples, computing an estimated signal-to-noise ratio of the electrical current based on at least a portion of the current samples, determine whether the signal-to-noise ratio is less than a predetermined threshold, and activate the switch to interrupt the electrical current in the conductive path, if the signal-to-noise ratio is less than the predetermined threshold.