Bo Dang

Bo Dang

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Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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25 September 2019 in Environmental Science & Technology
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Qiyuan WangQiyuan Wang
Qiyuan Wang
Jianhuai YeJianhuai Ye
Jianhuai Ye
YWYichen Wang
Yichen Wang
TZTing Zhang
Ting Zhang
WRWeikang Ran
Weikang Ran
JCJun-Ji Cao
Jun-Ji Cao

1 February 2016 in Acta Geophysica
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YLYanping Liu
Yanping Liu
BDBo Dang
Bo Dang
YLYue Li
Yue Li
HLHongbo Lin
Hongbo Lin
HMHaitao Ma
Haitao Ma
Open Access Published: 01 February 2016 Applications of Savitzky-Golay Filter for Seismic Random Noise Reduction Yanping Liu1, Bo Dang1, Yue Li2, Hongbo Lin2 & Haitao Ma2 Acta Geophysica volume 64, pages 101–124 (2016)Cite this article 909 Accesses 33 Citations Metrics details Abstract This article utilizes Savitzky–Golay (SG) filter to eliminate seismic random noise. This is a novel method for seismic random noise reduction in which SG filter adopts piecewise weighted polynomial via leastsquares estimation. Therefore, effective smoothing is achieved in extracting the original signal from noise environment while retaining the shape of the signal as close as possible to the original one. Although there are lots of classical methods such as Wiener filtering and wavelet denoising applied to eliminate seismic random noise, the SG filter outperforms them in approximating the true signal. SG filter will obtain a good tradeoff in waveform smoothing and valid signal preservation under suitable conditions. These are the appropriate window size and the polynomial degree. Through examples from synthetic seismic signals and field seismic data, we demonstrate the good performance of SG filter by comparing it with the Wiener filtering and wavelet denoising methods. Download to read the full article text References Awal, Md.A., S.S. Mostafa, and M. Ahmad (2011), Performance analysis of Savitzky–Golay smoothing filter using ECG signal, Int. J. Comput. Inf. Technol. 1, 2, 24–29. Google Scholar Bian, J., A. Li, M. Song, L. Ma, and J. Jiang (2010), Reconstruction of NDVI timeseries datasets of MODIS based on Savitzky–Golay filter, J. Remote Sens. 14, 4, 725–741. Google Scholar Bonettini, S., and V. Ruggiero (2011), An alternating extragradient method for total variation-based image restoration from Poisson data, Inverse Probl. 27, 9, 095001, DOI: 10.1088/0266-5611/27/9/095001. 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Liu (2009), A new gradient fidelity term for avoiding staircasing effect, J. Comput. Sci. Technol. 24, 6, 1162–1170, DOI: 10.1007/s11390-009-9289-1. Article Google Scholar Ferahtia, J., K. Baddari, N. Djarfour, and A.K. Kassouri (2010), Incorporation of a non-linear image filtering technique for noise reduction in seismic data, Pure Appl. Geophys. 167, 11, 1389–1404, DOI: 10.1007/s00024-010-0101-5. Article Google Scholar Gong, C. (2012), Method research of the seismic data denoising based on total variation principle, MSc. Thesis, Chengdu University of Technology, Chengdu, China, 46 pp. Google Scholar Guiñón, J.L., E. Ortega, J. García-Antón, and V. Pérez-Herranz (2007), Moving average and Savitzki–Golay smoothing filters using Mathcad. In: Proc. Int. Conf. on Engineering Education (ICEE 2007), 3-7 September 2007, Coimbra, Portugal. Google Scholar Hargittai, S. (2005), Savitzky–Golay least-squares polynomial filters in ECG signal processing, Comput. Cardiol. 32, 763–766, DOI: 10.1109/CIC.2005.1588216. Google Scholar Wayt, H.J., and T.R. Khan (2007), Integrated Savitzky–Golay filter from inverse Taylor series approach. In: Proc. 15th Int. Conf. on Digital Signal Processing, 1-4 July 2007, Cardiff, Great Britain, 375–378, DOI: 10.1109/ICDSP.2007.4288597. Google Scholar Huang, Y.H., J.H. Wang, D. Jiang, and Q. Zhou (2009), Reconstruction of MODISEVI time-series data with S-G filter, Geomat. Inf. Sci. Wuhan Univ. 34, 12, 1440–1444. Google Scholar Li, M., and J. Liu (2011), Reconstructing vegetation temperature condition index based on the Savitzky–Golay filter. In: D. Li, Y. Liu, and Y. Chen (eds.), Computer and Computing Technologies in Agriculture IV, IFIP Advances in Information and Communication Technology, Vol. 346, 629–637, DOI: 10.1007/978-3-642-18354-6_74. Article Google Scholar Li, X., and N.M. Bilgutay (1993), Wiener filter realization for target detection using group delay statistics, IEEE Trans. Signal Process. 41, 6, 2067–2074, DOI: 10.1109/78.218136. Article Google Scholar Nie, P. (2012), The study and application of noise suppression method in seismic exploration–Regularization constrained Wiener filter and directional derivative trace transform, Ph.D. Thesis, Jilin University, Jilin, China. Google Scholar O’Haver, T. (2012), An introduction to signal processing with applications in chemical analysis, http://terpconnect.umd.edu/~toh/spectrum/TOC.html,last updated 8 May. Google Scholar O’Haver, T. (2013), A pragmatic introduction to signal processing with applications in chemical analysis, http://terpconnect.umd.edu/~toh/spectrum/TOC.html, last updated 28 July. Google Scholar Qu, Y., J.X. Cao, H.D. Zhu, and C. Ren (2011), An improved total variation technique for seismic image denoising, Acta Petrolei Sin. 32, 815–819. Google Scholar Rudin, L.I., S. Osher, and E. Fatemi (1992) Nonlinear total variation based noise removal algorithms, Physica D 60, 1–4, 259–268, DOI: 10.1016/0167-2789(92)90242-F. Article Google Scholar Ruffin, C., and R.L. King (1999), The analysis of hyperspectral data using Savitzky–Golay filtering–Theoretical basis (Part 1). In: Conf. IEEE Int. Geoscience and Remote Sensing Symposium, Hamburg, Germany, 756–758, DOI: 10.1109/IGARSS.1999.774430. Google Scholar Savitzky, A., and M.J.E. Golay (1964), Smoothing and differentiation of data by simplified least squares procedures, Anal. Chem. 36, 8, 1627–1639, DOI: 10.1021/ac60214a047. Article Google Scholar Schafer, R.W. (2011), What is a Savitzky–Golay filter? IEEE Signal Process. Mag. 28, 4, 111–117, DOI: 10.1109/MSP.2011.941097. Article Google Scholar Selesnick, I.W., and İ. Bayram (2010), Total variation filtering, OpenStax-CNX module: m31292, http://cnx.org/content/m31292/1.1. Google Scholar Vaiphasa, C. (2006), Consideration of smoothing techniques for hyperspectral remote sensing, ISPRS J. Photogramm. Remote Sens. 60, 2, 91–99, DOI:10.1016/j.isprsjprs.2005.11.002. Article Google Scholar Vivó-Truyols, G., and P.J. Schoenmakers (2006), Automatic selection of optimal Savitzky–Golay smoothing, Anal. Chem. 78, 13, 4598–4608, DOI: 10.1021/ac0600196. Article Google Scholar Vogel, C.R., and M.E. Oman (1996), Iterative methods for total variation denoising, SIAM J. Sci. Comput. 17, 1, 227–238, DOI: 10.1137/0917016. Article Google Scholar Xu, J., H. Jiang, L. Xu, L. Jiang, T. Qian, and C. Feng (2011), Pulse wave processing and analysis based on smoothing filter, Chin. J. Sci. Instr. 32, 334–337. Google Scholar Zehtabian, A., and H. Hassanpour (2011), Optimized singular vector denoising approach for speech enhancement, Iran. J. Ener. Environ. 2, 2, 166–180. Google Scholar Zhou, W., and Q. Li (2013), Adaptive total variation regularization based scheme for Poisson noise removal, Math. Method. Appl. Sci. 36, 3, 290–299, DOI:10.1002/mma.2587. Article Google Scholar Download references Author information Affiliations College of Electronic Engineering, Xi’an Shiyou University, Xi’an, China Yanping Liu & Bo Dang College of Communication Engineering, Jilin University, Changchun, China Yue Li, Hongbo Lin & Haitao Ma Authors Yanping Liu View author publications You can also search for this author in PubMed Google Scholar Bo Dang View author publications You can also search for this author in PubMed Google Scholar Yue Li View author publications You can also search for this author in PubMed Google Scholar Hongbo Lin View author publications You can also search for this author in PubMed Google Scholar Haitao Ma View author publications You can also search for this author in PubMed Google Scholar Corresponding author Correspondence to Yanping Liu. Rights and permissions Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0), which permits use, duplication, adaptation, distribution, and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Reprints and Permissions About this article Cite this article Liu, Y., Dang, B., Li, Y. et al. Applications of Savitzky-Golay Filter for Seismic Random Noise Reduction. Acta Geophys. 64, 101–124 (2016). https://doi.org/10.1515/acgeo-2015-0062 Download citation Received: 03 September 2013 Revised: 11 January 2015 Accepted: 09 February 2015 Published: 01 February 2016 Issue Date: February 2016 DOI : https://doi.org/10.1515/acgeo-2015-0062 Share this article Anyone you share the following link with will be able to read this content: Get shareable link Sorry, a shareable link is not currently available for this article. Copy to clipboard Provided by the Springer Nature SharedIt content-sharing initiative Keyword SG filter seismic random noise reduction synthetic seismic signals field seismic data

1 October 2015 in Journal of Petroleum Science and Engineering
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GGGuowang Gao
Guowang Gao
RDRuirong Dang
Ruirong Dang
ANAlireza Nouri
Alireza Nouri
HJHuiqin Jia
Huiqin Jia
LLLipin Li
Lipin Li
BDBo Dang
Bo Dang

17 August 2018 in Sensors
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BDBo Dang
Bo Dang
玲杨玲 杨
玲 杨
CLChangzan Liu
Changzan Liu
YZYahong Zheng
Yahong Zheng
HLHui Li
Hui Li
BSBaoquan Sun
Baoquan Sun
Borehole transient electromagnetic (TEM) techniques have been proven to be efficient for nondestructive evaluations (NDEs) of metal casings using eddy-current properties. However, physical limitations and bad borehole conditions restrict the use of eddy-current sensors, which makes downhole casing inspections very different from those of conventional NDE systems. In this paper, we present a uniform linear multi-coil array-based borehole TEM system for NDEs of downhole casings. On the basis of the borehole TEM signal model, a numerical multi-coil array approach using the Gauss–Legendre quadrature is derived. The TEM response can be divided into two independent parts related to the transmitting-receiving distance (TRD) and the observation time and casing thickness. Using this property, the signal received by the multi-coil array is weighted to cancel the influence of the TRDs of the different array elements to obtain the optimal response according to the linearly constrained minimum variance criterion, which can be shown to be identical to that of achieving the maximum signal-to-noise ratio. The effectiveness of the proposed method was verified by applying the uniform linear multi-coil array to a borehole TEM system for NDEs of oil-well casings. Field experiments were conducted, and the results demonstrate the effectiveness of the proposed method.

30 August 2023 in Measurement Science and Technology
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Open access
玲杨玲 杨
玲 杨
JDJINGXIN DANG
JINGXIN DANG
MYMengfan Yang
Mengfan Yang
YDYixin Dang
Yixin Dang
KYKai Yuan
Kai Yuan
BDBo Dang
Bo Dang
The inspection of corrosion under insulation (CUI) has been identified as a significant challenge in the petroleum and chemical process industries. As some of the most effective strategies, pulsed eddy current (PEC) techniques have proved effective for the measurement of the CUI of pipelines. In this paper, we propose a circular-arc array (CAA) to improve the measurement efficiency for the PEC inspection of thermally insulated pipelines. Based on the PEC system model for inspecting the CUI of pipelines, the magnetic field distribution of the CAA with multiple excitors was investigated. It is shown that the coverage of induced magnetic field gets much larger than that of the single excitor to realize high-efficiency measurements. Moreover, a sparsely distributed receiver array is designed to further improve the signal-to-noise ratio by eliminating the waviness effect due to multiple excitors. Finally, experiments were conducted, and the results demonstrated the effectiveness of the proposed method for the inspection of thermally insulated pipelines.

27 June 2022 in IEEE Transactions on Magnetics
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CLChangzan Liu
Changzan Liu
BDBo Dang
Bo Dang
HWHaiyan Wang
Haiyan Wang
LYLing Yang
Ling Yang
JDJINGXIN DANG
JINGXIN DANG
RDRuirong Dang
Ruirong Dang
In this article, we address the problem of synthesized magnetic field focusing (SMF) of the pulsed eddy-current (PEC) technology for the non-destructive testing (NDT) of oil and gas well casing pipes. The electromagnetic response excited by multiple transmitters was derived using the signal model of downhole PEC system. The magnetic field was shown to be adjustable by modifying the currents of the multiple transmitting array. Based on this property, magnetic fields were synthesized with the mean squared error (MMSE) criterion to be focused on the center of the transmitting array, and a weighted MMSE (WMMSE)-based SMF was also proposed to achieve an optimal synthetic magnetic field. Furthermore, the primal-dual interior-point method was used to solve the WMMSE optimization problem with the total and single transmit power constraints for the practical application. Simulations and experimental results showed that the SMF with the PEC array effectively focuses the eddy-current field on the center of the transmitting array.