{
  "abstract": "Early-stage defects in wind turbine bearings often generate weak impulsive signatures that are easily obscured by strong background noise, posing a significant challenge to accurate extraction of fault-related features. To overcome this limitation, a novel concave sparsity-assisted time-reassigned multisynchrosqueezing transform (CSA-TMSST) is developed to improve the extraction of weak fault-related signatures. First, a non-convex sparse optimization model incorporating the generalized minimax-concave (GMC) penalty is established to reconstruct fault impulsive components from the raw signal. The introduced GMC-based sparse regularization enhances signal sparsity, enabling the accurate extraction of impulsive fault signatures. Subsequently, TMSST is employed to characterize the reconstructed signal in the time-frequency (TF) domain, yielding a more concentrated time-frequency representation (TFR). Furthermore, the iterative reassignment mechanism is utilized to enhance the concentration of TF energy distribution, thereby yielding a clearer TFR of transient fault features. Finally, characteristic fault frequencies are identified via spectral analysis. The results demonstrate that CSA-TMSST is capable of extracting weak fault-related signatures and producing high-quality TFRs under strong noise conditions, confirming its effectiveness and superiority.",
  "abstract_shown": true,
  "affiliations": [
    "Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle, Hubei University of Arts and Science, Xiangyang, P.R. China",
    "Hubei Longzhong Laboratory, Hubei University of Arts and Science, Xiangyang, P.R. China",
    "Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan, China"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Delong Zhang"
    },
    {
      "affs": [
        1
      ],
      "name": "Yubo Ma"
    },
    {
      "affs": [
        2
      ],
      "name": "Hongan Wu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/b4mh4jgm4k72c.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0360733",
  "fulltext_url": null,
  "id": "b4mh4jgm4k72c",
  "issns": [
    "1932-6203"
  ],
  "landing_url": "https://doi.org/10.1371/journal.pone.0360733",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2207|Machine Fault Diagnosis Techniques"
    ],
    [
      "plos",
      "/Computer and information sciences/Information theory/Background signal noise"
    ],
    [
      "plos",
      "/Earth sciences/Geophysics/Seismology"
    ],
    [
      "plos",
      "/Engineering and technology/Energy and power/Alternative energy/Wind power"
    ],
    [
      "plos",
      "/Engineering and technology/Signal processing"
    ],
    [
      "plos",
      "/Engineering and technology/Signal processing/Background signal noise"
    ],
    [
      "plos",
      "/Engineering and technology/Signal processing/White noise"
    ],
    [
      "plos",
      "/Physical sciences/Physics/Classical mechanics/Damage mechanics"
    ],
    [
      "plos",
      "/Physical sciences/Physics/Classical mechanics/Vibration"
    ],
    [
      "plos",
      "/Physical sciences/Physics/Geophysics/Seismology"
    ],
    [
      "plos",
      "/Physical sciences/Physics/Resonance/Resonance frequency"
    ]
  ],
  "openalex": "W7222532637",
  "pdf_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0360733&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-16",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/b4mh4jgm4k72c.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:23Z",
      "native_id": "10.1371/journal.pone.0360733",
      "source": "plos",
      "url": "https://doi.org/10.1371/journal.pone.0360733"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "plos:seismology",
      "subfield": "geophysics"
    }
  ],
  "title": "Concave sparsity-assisted time-reassigned multisynchrosqueezing transform for early-stage weak fault feature enhancement with applications to bearing fault diagnosis",
  "title_text": "Concave sparsity-assisted time-reassigned multisynchrosqueezing transform for early-stage weak fault feature enhancement with applications to bearing fault diagnosis",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:23Z",
  "url": "https://research.draconitic.com/paper/b4mh4jgm4k72c",
  "venue": "PLOS One",
  "versions": []
}