DC Arc Detection Using Spectral Clustering and Noise Extraction

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Solution Overview

Problem

Existing DC arc detection techniques in photovoltaic power generation systems face challenges in accurately identifying arcs due to noise interference, variable attenuation in DC cables, and environmental factors, which can lead to false positives and missed detections.

Innovation Solution

A computationally inexpensive method that combines spectral and temporal characteristics of the arc signal, using an analog-to-digital converter, comb filter, and Fast Fourier Transform to generate frequency-domain representations, and adaptive decision-making parameters to improve detection accuracy, while integrating arc detection and plant profiling within the inverter system.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional arc detection techniques are used, then arc detection is performed, but noise interference from inverters causes false positives and missed detections

Engineering Contradiction:

Improvearc detection accuracyVSAvoidnoise interference

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The patent extracts and removes the inverter switching noise component from the detected signal by identifying and subtracting the known switching frequency and its harmonics, thereby isolating the arc fault signal from the dominant noise source

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent changes the detection parameters by using multiple frequency bins and evaluating spectral characteristics across different frequency ranges, allowing the system to distinguish arc signals from noise based on their different spectral distributions

Inventive Principle:

Principle #35Parameter changes

2Adaptability or versatility

If arc detection is performed in variable environmental conditions, then arc detection capability is maintained, but detection accuracy deteriorates due to environmental changes

Engineering Contradiction:

Improveenvironmental adaptabilityVSAvoiddetection accuracy

Core Design Contradiction:

Adaptability or versatilityVSMeasurement precision

Solution Approach 1:

The patent implements dynamic threshold adjustment where the detection threshold is adapted based on the detected noise level and spectral characteristics, allowing the system to maintain optimal detection performance across varying environmental conditions

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system uses feedback from the detected signal characteristics to continuously adjust detection parameters and thresholds, improving adaptability to changing environmental conditions while maintaining detection accuracy

Inventive Principle:

Principle #23Feedback

3Ease of operation

If DC cable attenuation varies, then signal transmission is maintained, but arc detection precision deteriorates due to variable attenuation

Engineering Contradiction:

Improvesignal transmissionVSAvoidarc detection precision

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent performs preliminary characterization of the system's frequency response and attenuation characteristics during installation, storing this information for use in subsequent arc detection to compensate for variable attenuation effects

Inventive Principle:

Principle #10Preliminary action

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

This approach enhances the detection of arc faults by reducing noise interference and adapting to environmental changes, leading to improved accuracy and reliability in identifying arcs, even in the presence of noise, and prevents false positives.

Implementation Method 1

sampling, by an analog-to-digital converter, a first signal on a first power line to generate a plurality of first digital samples

Methodology Applied

Scientific EffectAnalog-to-digital conversion:

Implementation Method 2

filtering, using a comb filter, the plurality of digital samples to remove a switching noise frequency of the inverter from the first digital samples

Methodology Applied

Scientific EffectFiltering: Filter (electronic)

Implementation Method 3

transforming, using a Fast Fourier Transform ("FFT") module, for example, a first window of the first digital samples to a first frequency-domain representation

Methodology Applied

Scientific EffectFast Fourier Transform:

Data Source

PatentUS10985695B2DC arc detection and photovoltaic plant profiling system

Publication Date: 2021.04.20 ANALOG DEVICES INT UNLTD CO

AI summary

An arc detection method includes classifying whether an arc fault is present in the power system by, for each of a plurality of bins of a current frame of a signal, marking the bin as a candidate bin if a magnitude spectrum of the bin meets first criteria; determining a number of candidate bins in the current frame; marking the number of candidate bins as candidate cluster bins if the number of candidate bins exceeds a minimum cluster size; for each of the candidate cluster bins, determining whether the candidate cluster bin is also a candidate cluster bin of a previous frame of the first signal and if so, identifying the current frame as a candidate frame and incrementing a candidate frame count; and if the candidate frame count exceeds a candidate frame count threshold, determining that an arc fault is present in the power system.