{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-10496085","patent":{"patent_number":"US-10496085","title":"Power plant system fault diagnosis by learning historical system failure signatures","assignee":null,"inventors":[],"filing_date":"2018-01-26T00:00:00.000Z","publication_date":"2019-12-03T00:00:00.000Z","cpc_codes":["G05B","G01D","G05B","G05B","G06F","G06F","H04L","H04L"],"num_claims":20,"abstract":"A method, computer program product, and a system is provided for power plant system fault diagnosis. The method includes detecting, using an invariant model, a fault event based on a broken pair-wise correlation. The method also includes constructing a fault signature based on the fault event. The method further includes generating a feature vector in a feature subspace for the fault signature, wherein said feature vector includes at least one status of at least one system component during the fault event. The method additionally includes determining a corrective action correlated to the fault signature, from among a plurality of candidate corrective actions associated with the one or more historical representative signature, based on a Jaccard similarity using the feature vector in the feature subspace. The method also includes initiating the corrective action on a hardware device to mitigate expected harm."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Power plant system fault diagnosis by learning historical system failure signatures","description":"A method, computer program product, and a system is provided for power plant system fault diagnosis. The method includes detecting, using an invariant model, a fault event based on a broken pair-wise ","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-10496085","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-10496085","citation_suggestion":"Patentable. \"Power plant system fault diagnosis by learning historical system failure signatures\" (US-10496085). https://patentable.app/patents/US-10496085","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-10496085","json":"https://patentable.app/api/llm-context/US-10496085","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T05:40:07.760Z"}