{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11295012","patent":{"patent_number":"US-11295012","title":"Characterizing and mitigating spillover false alarms in inferential models for machine-learning prognostics","assignee":null,"inventors":[],"filing_date":"2019-01-09T00:00:00.000Z","publication_date":"2022-04-05T00:00:00.000Z","cpc_codes":["G06F","G06F","G06F","G06F","G06N","G06N","G06N","G06F","G06N"],"num_claims":20,"abstract":"The disclosed embodiments relate to a system that determines whether an inferential model is susceptible to spillover false alarms. During operation, the system receives a set of time-series signals from sensors in a monitored system. The system then trains the inferential model using the set of time-series signals. Next, the system tests the inferential model for susceptibility to spillover false alarms by performing the following operations for one signal at a time in the set of time-series signals. First, the system adds degradation to the signal to produce a degraded signal. The system then uses the inferential model to perform prognostic-surveillance operations on the time-series signals with the degraded signal. Finally, the system detects spillover false alarms based on results of the prognostic-surveillance operations."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Characterizing and mitigating spillover false alarms in inferential models for machine-learning prognostics","description":"The disclosed embodiments relate to a system that determines whether an inferential model is susceptible to spillover false alarms. During operation, the system receives a set of time-series signals f","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11295012","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-11295012","citation_suggestion":"Patentable. \"Characterizing and mitigating spillover false alarms in inferential models for machine-learning prognostics\" (US-11295012). https://patentable.app/patents/US-11295012","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11295012","json":"https://patentable.app/api/llm-context/US-11295012","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-30T20:05:27.443Z"}