Search Results - "Wu, Hongan"

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  1. 1

    Characteristics inversion of underground goaf based on InSAR techniques and PIM by Fan, Hongdong, Li, Tengteng, Gao, Yantao, Deng, Kazhong, Wu, Hongan

    “…•A new method of characteristics inversion of underground goaf has been developed.•Mining subsidence can be generated by InSAR and offset-tracking methods.•The…”
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    Journal Article
  2. 2

    HLSTM: Heterogeneous Long Short-Term Memory Network for Large-Scale InSAR Ground Subsidence Prediction by Liu, Qinghao, Zhang, Yonghong, Wei, Jujie, Wu, Hongan, Deng, Min

    “…Accurate prediction of ground subsidence is of great significance for the prevention and mitigation of this type of geological disaster. It is still a…”
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    Journal Article
  3. 3

    Investigating Ground Subsidence and the Causes over the Whole Jiangsu Province, China Using Sentinel-1 SAR Data by Zhang, Yonghong, Wu, Hongan, Li, Mingju, Kang, Yonghui, Lu, Zhong

    Published in Remote sensing (Basel, Switzerland) (01-01-2021)
    “…Interferometric synthetic aperture radar (InSAR) mapping of localized ground surface deformation has become an important tool to manage subsidence-related…”
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    Journal Article
  4. 4

    Mining Subsidence Monitoring With Modified Time-Series SAR Interferometry Method Based on the Multi-Level Processing Strategy by He, Qian, Zhang, Yonghong, Wu, Hongan, Luo, Yong

    Published in IEEE access (2021)
    “…The supply of coal is related to the stability of social development in China. Coal mining faces are generally located under farmland and wasteland to avoid…”
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    Journal Article
  5. 5

    Ground Subsidence in the Beijing-Tianjin-Hebei Region from 1992 to 2014 Revealed by Multiple SAR Stacks by Zhang, Yonghong, Wu, Hong’an, Kang, Yonghui, Zhu, Chuanguang

    Published in Remote sensing (Basel, Switzerland) (01-08-2016)
    “…The coordinated development of the Beijing-Tianjin-Hebei has become a national strategy with Beijing and Tianjin as twin engines driving the regional…”
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    Journal Article
  6. 6

    A temporal difference matrix for historical cumulative change detection in time series PolSAR data by Wei, Jujie, Zhang, Yonghong, Yu, Xiaoping, Wu, Hong’an, Lu, Jufeng

    “…•This paper introduces a time series change detection method for land cover.•This method integrates both intensity differences and polarization…”
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    Journal Article
  7. 7

    The Automatic Detection of Fire Scar in Alaska using Multi-Temporal PALSAR Polarimetric SAR Data by Jujie Wei, Yonghong Zhang, Hong’an Wu, Bin Cui

    Published in Canadian journal of remote sensing (03-09-2018)
    “…The existing fire scar detection methods based on multi-temporal analysis only used the difference in either backscattering intensity or polarimetric…”
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    Journal Article
  8. 8

    An Unsupervised SAR Change Detection Method Based on Stochastic Subspace Ensemble Learning by Cui, Bin, Zhang, Yonghong, Yan, Li, Wei, Jujie, Wu, Hong’an

    Published in Remote sensing (Basel, Switzerland) (01-06-2019)
    “…As synthetic aperture radar (SAR) is playing an increasingly important role in Earth observations, many new methods and technologies have been proposed for…”
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    Journal Article
  9. 9

    An Efficient Change Detection for Large SAR Images Based on Modified U-Net Framework by Jujie Wei, Yonghong Zhang, Hong’an Wu, Bin Cui

    Published in Canadian journal of remote sensing (03-05-2020)
    “…Large SAR images usually contain a variety of land-cover types and accordingly complicated change types, which cause great difficulty for accurate change…”
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    Journal Article
  10. 10

    Mechanisms of endogenous and exogenous partial denitrification in response to different carbon/nitrogen ratios: Transcript levels, nitrous oxide production, electron transport by Wu, Hongan, Zeng, Wei, Wu, Lei, Lu, Sijia, Peng, Yongzhen

    Published in Bioresource technology (01-05-2024)
    “…[Display omitted] •EdPD has more stable NTR (74.5% to 61.0%) with rising C/N ratios (from 3 to 6).•ETSA of ExPD is about 3–5 times higher than that of…”
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    Journal Article
  11. 11

    Multivariate dynamic mode decomposition and its application to bearing fault diagnosis by Zhang, Qixiang, Yuan, Rui, Lv, Yong, Li, Zhaolun, Wu, Hongan

    Published in IEEE sensors journal (01-04-2023)
    “…In practical engineering applications, the multivariate signal contains more fault feature information than the single channel signal. How to realize…”
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    Journal Article
  12. 12

    Variable-Bandwidth Self-Convergent Variational Mode Decomposition and Its Application to Fault Diagnosis of Rolling Bearing by Lv, Yong, Li, Zhaolun, Yuan, Rui, Zhang, Qixiang, Wu, Hongan

    “…Variational mode decomposition (VMD) gained popularity due to its excellent performance in rolling bearing fault diagnosis. To obtain accurate diagnosis…”
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    Journal Article
  13. 13

    The successful application of light to the system of simultaneous nitrification/endogenous denitrification and phosphorus removal: Promotion of partial nitrification and glycogen accumulation metabolism by Meng, Qingan, Zeng, Wei, Liu, Hongjun, Zhan, Mengjia, Zhang, Jiayu, Wu, Hongan

    Published in Water research (Oxford) (01-11-2023)
    “…Partial nitrification (PN) and high glycogen accumulating metabolism (GAM) activity are the basis for efficient nitrogen (N) and phosphorus (P) removal in…”
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    Journal Article
  14. 14

    Recursive demodulated synchro spline-kernelled chirplet extracting transform: a useful tool for non-linear behavior estimation of non-stationary signal and application to wind turbine fault detection by Ma, Yubo, Wu, Huawei, Yuan, Rui, Zhong, Hongyu, Wu, Hongan

    Published in Structural health monitoring (17-05-2024)
    “…Non-linear behavior is widespread in many kinds of signals from nature and engineering fields. Although the high energy-concentration level of various advanced…”
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    Journal Article
  15. 15

    Generalized Synchroextracting-based Stepwise Demodulation Transform and Its Application to Fault Diagnosis of Rotating Machinery by Lv, Yong, Wu, Hongan, Yuan, Rui, Dang, Zhang, Song, Gangbing

    Published in IEEE sensors journal (01-03-2023)
    “…The nonstationary characteristics of time-varying signals can be characterized by time-frequency analysis (TFA) accurately, which has been widely used in fault…”
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    Journal Article
  16. 16

    Self-Matching Chirplet Extraction Transform: A Novel Tool for Dense Multicomponent Signals Analysis and Machinery Fault Diagnosis by Wu, Hongan, Lv, Yong, Yuan, Rui, Li, Bowen, Yang, Xingkai, Zhu, Weihang

    Published in IEEE sensors journal (01-04-2024)
    “…This study introduces a novel time-frequency (TF) analysis methodology, designated as the self-matching chirplet extraction transform (SMCET). This innovative…”
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    Journal Article
  17. 17

    Self-Iterated Extracting Wavelet Transform and Its Application to Fault Diagnosis of Rotating Machinery by Li, Bowen, Yuan, Rui, Lv, Yong, Wu, Hongan, Zhong, Hongyu, Zhu, Weihang

    “…Time-frequency (TF) analysis (TFA) is a valuable tool for capturing nonstationary features in time-varying signals. However, for strongly amplitude-modulated…”
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    Journal Article
  18. 18

    Synchro-Reassigned Extracting Transform: An Effective Tool for Rotating Machinery Fault Diagnosis Under Varying Speed Condition by Wu, Hongan, Lv, Yong, Yuan, Rui, Yang, Xingkai, Feng, Ke, Zhu, Weihang

    “…Time-frequency analysis (TFA) techniques offer valuable insights into the dynamic characteristics of nonstationary signals, making them suitable for diagnosing…”
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    Journal Article
  19. 19

    Recent subsidence in Tianjin, China: observations from multi-looking TerraSAR-X InSAR from 2009 to 2013 by Zhu, Chuanguang, Zhang, Yonghong, Zhang, Jixian, Zhang, Liya, Long, Sichun, Wu, Hongan

    Published in International journal of remote sensing (02-12-2015)
    “…Tianjin, China, has been suggested to have serious ground subsidence due to excessive extraction of groundwater. It is essential to monitor this subsidence,…”
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    Journal Article
  20. 20

    Polarimetric SAR interferometry for forest canopy analysis by using the iterative method by Ming Guo, Yonghong Zhang, Zhen Li, Hongan Wu, Zhong-qiong Wang

    “…The Improved TD-RVoG model was combined with the classical forest inversion algorithm, three-stage inversion method, for the estimation of forest height by…”
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    Conference Proceeding