{
  "abstract": "Industrial plants collect high-frequency telemetry while critical quality variables may be measured only every few hours. We study soft sensing for an industrial monoammonium phosphate process using 260,642 one-minute records and 1,325 paired laboratory observations. The grey-box model reconstructs latent acid properties from conductivity and combines them with material-balance calculations to estimate molar ratio and downstream density. Validation is entirely chronological: nine pre-gap rolling tests, a short-term regime-transfer test, a strict external post-gap test on 438 future laboratory pairs, and ten post-gap rolling comparisons. To prevent uncontrolled extrapolation, the conductivity input to the fitted latent-property mappings is limited to the range observed in the corresponding training data. Ridge and LSBoost remain more accurate than the physics-guided model, particularly in the independent long-horizon evaluation. The results show that physical structure improves interpretability but does not by itself ensure temporal robustness, motivating regime-aware monitoring, recalibration, and fallback logic for industrial virtual telemetry.",
  "abstract_shown": true,
  "affiliations": [
    "Moscow Institute of Physics and Technology (National Research University",
    "Molecular Electronics Research Institute",
    "JSC (MERI",
    "UralAiTech LLC"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "German A. Karnup",
      "orcid": "0000-0001-6517-4712"
    },
    {
      "affs": [
        3
      ],
      "name": "Andrey N. Sychev"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Oleg A. Telminov"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Evgeny S. Gornev"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5wncvv7mcjyk9.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15009979/v1",
  "fulltext_url": null,
  "id": "5wncvv7mcjyk9",
  "issns": [],
  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009979/v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2207|Fault Detection and Control Systems"
    ]
  ],
  "openalex": "W7220649278",
  "pdf_url": "https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15009979/v1",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-06",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/5wncvv7mcjyk9.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:22Z",
      "native_id": "10.26434/chemrxiv.15009979",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009979/v1"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "source:chemrxiv",
      "subfield": "general"
    }
  ],
  "title": "Physics-Guided Soft Sensing under Sparse Laboratory Measurements and Temporal Regime Shifts in Industrial Monoammonium Phosphate Production",
  "title_text": "Physics-Guided Soft Sensing under Sparse Laboratory Measurements and Temporal Regime Shifts in Industrial Monoammonium Phosphate Production",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:22Z",
  "url": "https://research.draconitic.com/paper/5wncvv7mcjyk9",
  "venue": "ChemRxiv",
  "versions": []
}