High-Speed Arcing Fault Detection: Using the Light Spectrum

Zhao, Long; Zhou, Yuhao; Chen, Kun‐Long; Rau, Shiuan-Hau; Lee, Wei-Jen

doi:10.1109/mias.2019.2943664

Cited by 37 publications

(10 citation statements)

References 13 publications

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“…Therefore, many researchers have also attempted to detect arc faults through non-VI characteristics. Zhao et al [8] proposed a method of arc fault detection based on the influence of arc light on the light spectrum. There are other methods to detect arc faults by arc light, for instance, a diagnosing method based on the intensity and duration of arc flashes [9].…”

Section: Introductionmentioning

confidence: 99%

Fast-Fourier-Transform Enhanced Progressive Singular-Value-Decomposition Algorithm in Double Diagnostic Window Frame for Weak Arc Fault Detection

Shen

Wai

2022

IEEE Access

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In this study, a novel method that progressively applies the fastest form of singular-value decomposition (SVD) to extract nonperiodic arc-fault features is proposed in order to pursue a competent solution for AC weak arc fault detection. First, bus-current signals of the normal state and the arc-fault state are collected and normalized before being processed by progressive SVD (PSVD) to detect the discrepancy brought by comparatively stronger arc-fault nonperiodic components expressed in singular values. To provide a more comprehensive feature extraction for an enhanced accuracy, the fast Fourier transform (FFT) is incorporated for accumulating periodic variations caused by arc faults. Because weak arc faults are difficult to distinguish from normal signals when they start, a double diagnostic window frame (DDWF) is designed to reduce false negative errors. The effectiveness of each partial design of the method is verified by experiments with numerous load types and current amplitudes conducted on an industrial experimental platform. The proposed PSVD-FFT algorithm has achieved a satisfactory and consistent performance measured by both the detection accuracy and diagnosis time in all of the experiments. The proposed method is on average at least 10% more accurate than the selected methods for a parallel comparison (in total more than a thousand experimental cases), with a satisfactory range of execution time.INDEX TERMS Arc fault, singular value decomposition (SVD), fast Fourier transform (FFT), support vector machine (SVM).

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Section: Introductionmentioning

confidence: 99%

Fast-Fourier-Transform Enhanced Progressive Singular-Value-Decomposition Algorithm in Double Diagnostic Window Frame for Weak Arc Fault Detection

Shen

Wai

2022

IEEE Access

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“…the physical signal detection methods and the electrical signal detection methods. The former methods use signals including voice, light, heat, electromagnetic radiation and ultraviolet for SAF detection [3]. The latter methods are mainly based on current and voltage signals [4][5].…”

Section: Introductionmentioning

confidence: 99%

A Coupling Method for Identifying Arc Faults Based on Short-Observation-Window SVDR

Jiang

Bao

Hong

et al. 2021

IEEE Trans. Instrum. Meas.

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This paper presents a new method for effective detection of AC series arc fault (SAF) and extraction of SAF characteristics in residential buildings, which addresses the challenges with conventional current detection methods in discriminating arcing and non-arcing current due to their similarity. Different from the traditional method, in the proposed method, the differential magnetic flux is coupled to obtain high-frequency signals by putting the live line and the neutral line through the current transformer, which can effectively solve the problem of SAF features disappearing in the trunk-line current. However, similar to the traditional method, the effectiveness of the proposed coupling method could also be compromised when being used in cases with dimmer load and load starting process. This is found to be caused by the presence of high-amplitude pulse phenomenon in the non-arcing signals in these scenarios, which are incorrectly detected as arcing signals in other loads. To address this issue, a short-observation-window singular value decomposition and reconstruction algorithm (SOW-SVDR) is used to enhance the capability to identify SAFs by the coupling method. The proposed method has been implemented and validated according to UL1699 standard with different types of loads connected to the system and also tested under their starting processes. The experimental results show that the proposed approach is more effective in detecting arc faults compared with existing methods.

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“…A number of algorithms have been proposed to detect the DC series arc using characteristics in various domains. Specifically, methods using time-domain characteristics [3], [6]- [11], frequency-domain characteristics [2], [4], [12], [13], combined time and frequency domain characteristics [5], [14]- [18], artificial intelligence [19]- [23], and techniques using electromagnetic properties during arc generation [24]- [27] have been proposed.…”

Section: Introductionmentioning

confidence: 99%

DC Series Arc Detection Algorithm Based on Adaptive Moving Average Technique

2021

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This paper proposes a DC series arc detection algorithm in a photovoltaic (PV) system using an adaptive moving average (AMA). The proposed algorithm uses two moving averages of which is the average of 5 kHz to 40 kHz frequency band. One is which is the moving average highly affected by recent . The other is which is the moving average heavily affected by past . There is a little difference between and before arcing because is approximately constant. However, this difference increases when the arc occurs because slowly follows . This difference is used as an arc detection indicator (ADI) in this study. Additionally, AMA is proposed to avoid nuisance tripping in the normal transient state. The proposed method determines the arc occurrence using the relative magnitudes of the two moving averages. Therefore, it is less affected by the shape of the frequency fluctuations caused by the load inverter. Hence, the proposed algorithm is effective in the centralized and spread-type of frequency fluctuations. These results were verified through an arc detection test and nuisance tripping test using arc experimental data and MATLAB.

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High-Speed Arcing Fault Detection: Using the Light Spectrum

Cited by 37 publications

References 13 publications

Fast-Fourier-Transform Enhanced Progressive Singular-Value-Decomposition Algorithm in Double Diagnostic Window Frame for Weak Arc Fault Detection

Fast-Fourier-Transform Enhanced Progressive Singular-Value-Decomposition Algorithm in Double Diagnostic Window Frame for Weak Arc Fault Detection

A Coupling Method for Identifying Arc Faults Based on Short-Observation-Window SVDR

DC Series Arc Detection Algorithm Based on Adaptive Moving Average Technique

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