Site characterizations for the Tehran network (TDMMO) in Tehran Region Using Micro-Earthquake, Microtremor and Quarry Blast Data

Farahani, Jamileh Vasheghani; Zaré, Mehdi

doi:10.1016/j.soildyn.2014.03.013

Cited by 6 publications

(3 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our intuition that these features are in a certain period, this period starts at the onset time (t 0 ) and ends at a certain time which we call (t 2 ). Most of the previously published approaches depend on extracting different features from low and high frequencies (Horasan et al 2009;Kekovalı et al 2012;Yılmaz et al 2013;Farahani and Zaré 2014). In this paper, for better representation of the seismic signals, we define a new parameter referred to as wavelet discriminator (W D), Eq.…”

Section: The Proposed Algorithmmentioning

confidence: 99%

“…While short-time Fourier transform (STFT) was utilized to support discrimination based on the complexity and spectral ratio (Yılmaz et al 2013). Furthermore, in Farahani and Zaré (2014), the proportion between the spectrums of the horizontal and the vertical components was applied as an indicator of the discrimination, given the same station.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Automatic discrimination of earthquakes and quarry blasts using wavelet filter bank and support vector machine

2018

View full text Add to dashboard Cite

False discrimination between earthquakes and quarry blasts may lead to an unrealistic characterization of the natural seismicity of a region. The similarity in seismograms between earthquakes and quarry blasts is the primary reason for incorrect discrimination. Therefore, in this paper, we propose a discriminative algorithm utilizing wavelet filter bank to extract unique features between earthquakes and quarry blasts. The discriminative features are found to be in the first five seconds after the onset time. The proposed algorithm is divided into two stages: first, wavelet filter bank extracts the features of the seismic signals; then, support vector machine classifies the event based on these extracted features. The proposed algorithm achieves a discrimination accuracy of 98.5% when applied to 900 earthquakes and quarry blast waveforms.

show abstract

Section: The Proposed Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automatic discrimination of earthquakes and quarry blasts using wavelet filter bank and support vector machine

2018

View full text Add to dashboard Cite

show abstract

“…Before impoundment of Three Gorges Reservoir, the seismic activity in that area was weak but, subsequently, the causes have been complicated, including natural earthquakes, explosion earthquakes in mining (Yang et al, 1993;Hu et al, 1998), earthquakes occurring after intense rainfall, and collapse earthquakes caused by subsidence of overburden (Gu, 1982). Farahani and Zare (2014) compared H/V amplification functions for the three kinds of seismic sources and demonstrated higher ratios in quarry blasts due to the importance of surface waves from shallow quarry blasts than for earthquakes or microtremors.…”

Section: Introductionmentioning

confidence: 99%

Mining induced collapse in 1997 and seismic records at Changyu, SE China

Shang

Yang

et al. 2016

Episodes

View full text Add to dashboard Cite

Quarry induced collapse, an issue of particular concern in the mining industry, is a typical form of manmade disaster. Identification of the morphological characteristics of such collapses is commonly based on seismic records but comprehensive studies regarding the mechanism and energy conversion mode utilizing the seismic record is seldom undertaken. A huge collapse event at the Biyutan mining cavern at Changyu Dongtian in Wenling city, China, lasting for about 20 seconds, was observed on August 11, 1997. After the collapse, nearly 11 million m 3 of rock blocks were left on the floor. By conducting a field survey on engineering geology, retrospectively analyzing the collapsing process through interviewing local residents, referring to related documents, and identifying the seismic records obtained from 3 surrounding seismic stations, it was established the roof collapse at the Biyutan cavern, excavated in massive tuff, was due to over excavation of several pillars, which substantially affected the stress field in cavern roof giving rise to a local failure of the roof that gradually developing into a widespread failure in an area EW 800m long, SN 460m wide. During the collapse, outbursts of water and air shock waves result in loss of life and property within a distance of 150m from the mine opening. This reminds us that reasonable allocation of sufficiently strong safety pillars and installation of monitoring system are absolutely essential in quarrying operations to avoid overall failure and ensure the safety of the people nearby.

show abstract

Application of Neuro-Fuzzy Systems in Geophysics

Hajian

Styles

2018

Application of Soft Computing and Intelligent Methods in Geophysics

View full text Add to dashboard Cite

Site characterizations for the Tehran network (TDMMO) in Tehran Region Using Micro-Earthquake, Microtremor and Quarry Blast Data

Cited by 6 publications

References 16 publications

Automatic discrimination of earthquakes and quarry blasts using wavelet filter bank and support vector machine

Automatic discrimination of earthquakes and quarry blasts using wavelet filter bank and support vector machine

Mining induced collapse in 1997 and seismic records at Changyu, SE China

Application of Neuro-Fuzzy Systems in Geophysics

Contact Info

Product

Resources

About