{
  "annotation_id": "e5b80aac-18b2-4967-83db-713c0d41205a",
  "date_created": "2026-03-02T18:00:46.912000Z",
  "date_modified": "2026-03-02T18:00:46.912000Z",
  "file_hash": "17b334176a001e1232d95d6628ba11f0698199fbad812644135a8b0c9a1c762a",
  "private": false,
  "record": {
    "abstract": "The statistical properties of acoustic emission signals for tool condition\nmonitoring (TCM) applications in mechanical lathe machining are analyzed in\nthis paper. Time series data and root mean square (RMS) values at various tool\nwear levels are shown to exhibit features that can be put into relation with\nageing in both cases. In particular, the histograms of raw data show power-law\ndistributions above a cross-over value, in which newer cutting tools exhibit\nmore numerous larger events compared with more worn-out ones. For practical\npurposes, statistics based on RMS values are more feasible, and the analysis of\nthese also reveals discriminating age-related features. The assumption that\nexperimental RMS histograms follow a Beta (b) distribution has also been\ntested. The residuals of the modeling b functions indicate that the search for\na more appropriate fitting function for the experimental distribution is\ndesirable.",
    "arxiv_id": "physics/0312148",
    "authors": [
      "G. Pontuale",
      "F. A. Farrelly",
      "A. Petri",
      "L. Pitolli"
    ],
    "categories": [
      "physics.data-an",
      "cond-mat.mtrl-sci"
    ],
    "journal_ref": "ARLO 4(1), 13-18 (2003)",
    "title": "A statistical analysis of acoustic emission signals for tool condition   monitoring (TCM)",
    "url": "https://arxiv.org/abs/physics/0312148"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "4f2d0219-dd30-4cc8-af0d-778facdf357e",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}