Sensitivity analysis of moment magnitude (Mw) spectral fitting parameters based on orthogonal design: using aftershocks of the 2019 Mw 6.5 Ambon, Indonesia earthquake

Kusumawati, Dian; Sahara, David P.; Nugraha, Andri Dian; Puspito, Nanang T.; Widiyantoro, Sri; Zulfakriza, Zulfakriza; Rosalia, Shindy; Shiddiqi, Hasbi Ash; Ardianto, Ardianto; Baskara, Aria Widhi; Rusdin, Andi Azhar; Wibowo, Adi; Heliani, Leni Sophia

doi:10.1007/s10518-022-01606-6

Cited by 2 publications

(2 citation statements)

References 29 publications

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“…The proper extraction of spectral features is crucial in earthquake event recognition as the core component of seismic monitoring 4 . Power Spectral Density (PSD) is commonly employed to extract earthquake signal frequencies 5 .…”

Section: Introductionmentioning

confidence: 99%

Spectrum feature extraction method combining Allan variance, VMD, and PSD

Liu,

Wang,

Liu

et al. 2024

Sci Rep

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Spectrum feature extraction plays a crucial role in identifying seismic events and calculating structural response parameters. However, the criteria for identifying effective modal components in Variational Mode Decomposition (VMD) are not well-defined, resulting in inaccurate spectrum feature extraction. To address this issue, we propose a novel spectrum feature extraction method that combines Allan variance, VMD, and power spectral density (PSD). Firstly, VMD is applied to filter noise components from triaxial accelerometer observations and add effective signals. Secondly, PSD is utilized to extract three groups of seismic frequencies (tri-axial accelerometers). Finally, the Allan method is introduced to identify the group of accelerometer observations with the highest reliability as the vibration frequency caused by the seismic excitation. We validate the effectiveness of our method by analyzing a Mw 2.6 micro-seismic event that occurred in Huairou, Beijing in 2022. The result shows that our proposed method accurately extracts spectrum features of the Great Wall. Specifically, the seismic excitation vibration frequencies at four monitoring stations were found to be 26.95 Hz, 12.89 Hz, 12.89 Hz, and 12.5 Hz. These findings underscore our method's utility in evaluating the Great Wall's structural response to seismic loading, which has significant implications for the conservation and protection of heritage structures.

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Section: Introductionmentioning

confidence: 99%

Spectrum feature extraction method combining Allan variance, VMD, and PSD

Liu,

Wang,

Liu

et al. 2024

Sci Rep

View full text Add to dashboard Cite

show abstract

“…The proper extraction of spectral features is crucial in earthquake event recognition and seismic parameter inversion as the core component of seismic monitoring [4]. Power Spectral Density (PSD) is commonly employed to extract earthquake signal frequencies [5].…”

Section: Introductionmentioning

confidence: 99%

Seismic Spectrum Feature Extraction Method Combining Allan Variance, VMD, and PSD: - A Case Study of the 2022 Mw 2.6 Microseismic Event in Huairou, Beijing

Liu,

Wang,

Liu

et al. 2023

Preprint

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Spectrum feature extraction plays a crucial role in identifying earthquake events and calculating seismic parameters. However, the identification standards of effective modal components in variational mode decomposition (VMD) are incomplete, leading to imprecise spectrum feature extraction. To address this issue, we propose a novel seismic spectrum feature extraction method that combines Allan variance, VMD, and power spectral density (PSD). First, VMD is applied to filter noise components from triaxial accelerometer observations and add effective signals. Second, PSD is utilized to extract three groups of seismic frequencies (tri-axial accelerometers). Finally, the Allan method is introduced to identify the group of accelerometer observations with the highest reliability as the vibration frequency caused by the seismic excitation. We validate the effectiveness of our method by analyzing a Mw 2.6 microseismic event that occurred in Huairou, Beijing in 2022. Our analysis demonstrates that triaxial accelerometers can effectively detect such events with a magnitude of 2.6. Additionally, our proposed method accurately extracts seismic spectrum features. Specifically, the seismic excitation vibration frequencies at four seismic monitoring stations were found to be 26.95 Hz, 12.89 Hz, 12.89 Hz, and 12.5 Hz. These findings highlight the potential of our approach for identifying and characterizing earthquake events, which has important implications for earthquake monitoring and hazard assessment.

show abstract

Sensitivity analysis of moment magnitude (Mw) spectral fitting parameters based on orthogonal design: using aftershocks of the 2019 Mw 6.5 Ambon, Indonesia earthquake

Cited by 2 publications

References 29 publications

Spectrum feature extraction method combining Allan variance, VMD, and PSD

Spectrum feature extraction method combining Allan variance, VMD, and PSD

Seismic Spectrum Feature Extraction Method Combining Allan Variance, VMD, and PSD: - A Case Study of the 2022 Mw 2.6 Microseismic Event in Huairou, Beijing

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