Advanced Phase-Difference Estimation Algorithm Using Cross Teager–Kaiser Energy Operator for DERs Synchronization

Lee, Jung Hoon; Yoo, Je-Ho; Baek, Ja-Hyun; Park, Sang-Ho; Cho, Soo-Hwan

doi:10.1007/s42835-023-01547-3

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…Step 1: Utilize Teager energy operator to concentrate energy on the spectrum. For discrete-time signals x(n), the Teager energy operator is defined as [27]:…”

Section: Spectrum Division Improvement In Ewtmentioning

confidence: 99%

Escalator Foundation Bolt Loosening Fault Recognition Based on Empirical Wavelet Transform and Multi-Scale Gray-Gradient Co-Occurrence Matrix

Wang

2023

Sensors

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An escalator is an essential large-scale public transport equipment; once it fails, this inevitably affects the operation of the escalator and even leads to safety concerns, or perhaps accidents. As an important structural part of the escalator, the foundation of the main engine can cause the operation of the escalator to become abnormal when its fixing bolts become loose. Aiming to reduce the difficulty of extracting the fault features of the footing bolt when it loosens, a fault feature extraction method is proposed in this paper based on empirical wavelet transform (EWT) and the gray-gradient co-occurrence matrix (GGCM). Firstly, the Teager energy operator and multi-scale peak determination are used to improve the spectral partitioning ability of EWT, and the improved EWT is used to decompose the original foundation vibration signal into a series of empirical mode functions (EMFs). Then, the gray-gradient co-occurrence matrix of each EMF is constructed, and six texture features of the gray-gradient co-occurrence matrix are calculated as the fault feature vectors of this EMF. Finally, the fault features of all EMFs are fused, and the degree of the loosening of the escalator foundation bolt is identified using the fused multi-scale feature vector and BiLSTM. The experimental results show that the proposed method based on EWT and GGCM feature extraction can diagnose the loosening degree of foundation bolts more effectively and has a certain engineering application value.

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“…Step 1: Utilize Teager energy operator to concentrate energy on the spectrum. For discrete-time signals x(n), the Teager energy operator is defined as [27]:…”

Section: Spectrum Division Improvement In Ewtmentioning

confidence: 99%

Escalator Foundation Bolt Loosening Fault Recognition Based on Empirical Wavelet Transform and Multi-Scale Gray-Gradient Co-Occurrence Matrix

Wang

2023

Sensors

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Advanced Synchronization Check Method Using Hilbert Transform-Based Voltage Envelope Analysis

Yoo,

Cho

2023

J. Electr. Eng. Technol.

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Advanced Phase-Difference Estimation Algorithm Using Cross Teager–Kaiser Energy Operator for DERs Synchronization

Cited by 2 publications

References 14 publications

Escalator Foundation Bolt Loosening Fault Recognition Based on Empirical Wavelet Transform and Multi-Scale Gray-Gradient Co-Occurrence Matrix

Escalator Foundation Bolt Loosening Fault Recognition Based on Empirical Wavelet Transform and Multi-Scale Gray-Gradient Co-Occurrence Matrix

Advanced Synchronization Check Method Using Hilbert Transform-Based Voltage Envelope Analysis

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