Electric Arc Detection Using Frequency Band Segmentation
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Solution Overview
Problem
Existing electric arc detection systems in solar power generation systems often erroneously detect pseudo electric arcs, which are noise-like phenomena occurring at low currents, leading to incorrect arc fault detection.
Innovation Solution
An electric arc detection apparatus comprising a current sensor, power spectrum conversion, an electric arc detection portion for high-frequency components, a pseudo electric arc determining portion for low-frequency components, and an electric arc presence/absence determining portion to differentiate between true and pseudo arcs, reducing erroneous detections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If electric arc detection is performed using power spectrum analysis of current flowing through the solar power generation system, then electric arcs can be detected, but pseudo electric arcs (noise-like phenomena at low currents) cause erroneous detections
Solution Approach 1:
The patent divides the power spectrum analysis into two distinct frequency bands: low-frequency band (20-2000 Hz) for detecting pseudo electric arcs and high-frequency band (2000-20000 Hz) for detecting true electric arcs. This segmentation allows the system to differentiate between noise-like phenomena and actual electric arc faults by analyzing different frequency characteristics separately, thereby resolving the contradiction between detection reliability and measurement precision.
2Measurement precision
If the power spectrum is divided into multiple bands for analysis, then detection accuracy improves, but device complexity increases
Solution Approach 1:
The patent implements frequency band segmentation using simple band-pass filters to divide the power spectrum into low-frequency and high-frequency bands. This segmentation approach improves detection precision by analyzing different frequency characteristics separately while maintaining relatively simple device structure through the use of standard filter components and sequential processing logic.
Solution Approach 2:
The patent dynamically adjusts the detection strategy based on the operating conditions of the solar power generation system. The control unit selectively applies different detection thresholds and analysis methods depending on whether the system is operating at high or low current levels, thereby improving detection precision without requiring permanently complex hardware for all operating conditions.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system accurately detects electric arcs while minimizing false alarms caused by pseudo electric arcs, enhancing the reliability of solar power generation system safety by distinguishing between actual and pseudo electric arcs.
Implementation Method 1
a current sensor that detects an electric current flowing through a power line
Implementation Method 2
a power spectrum conversion portion that generates a power spectrum from an output signal of the current sensor
Implementation Method 3
an electric arc detection portion that detects a suspected electric arc based on a high-frequency component of the power spectrum
Data Source
AI summary
An electric arc detection apparatus includes: a current sensor; a first filter; a second filter; an FFT processing portion that generates a high-frequency power spectrum and a low-frequency power spectrum; an electric arc detection portion that detects an electric arc by using the high-frequency power spectrum; a pseudo electric arc mask portion that determines a pseudo electric arc by using the low-frequency power spectrum; and an electric arc presence/absence determining portion.