{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-12007760","patent":{"patent_number":"US-12007760","title":"Anomaly detection and diagnosis in factory automation system using pre-processed time-delay neural network with loss function adaptation","assignee":null,"inventors":[],"filing_date":"2021-09-02T00:00:00.000Z","publication_date":"2024-06-11T00:00:00.000Z","cpc_codes":["G05B","G05B","G05B","G06F","G06N","G05B"],"num_claims":12,"abstract":"A computer-implemented pre-processed time-delay autoencoder based anomaly detection method are provided for detecting anomalous states of machines arranged in a factory automation (FA) system or a manufacturing production line. The method includes acquiring source signals from the machines via an interface performing a data pre-processing process for the acquired source signals by normalizing value ranges of the acquired source signals and filtering undesired features from the acquired source signals performing a time-delayed data reform process for the pre-processed source signals based on a time-delay window to generate pre-processed time-delay data submitting pre-processed time-delay testing data to a pre-processed time-delayed autoencoder (Prep-TDAE) neural network, wherein the pre-processed time-delay testing data are collected online while the machines are operated, wherein the Prep-TDAE neural network has been pre-trained by using the pre-processed time-delay training data detecting, if an anomaly state is encountered with respect to the machines, by computing anomaly scores of the pre-processed time-delay testing data, and determining, when the anomaly state is detected, anomaly occurrence time, duration and severity with respect to the anomaly state of each of the machines."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Anomaly detection and diagnosis in factory automation system using pre-processed time-delay neural network with loss function adaptation","description":"A computer-implemented pre-processed time-delay autoencoder based anomaly detection method are provided for detecting anomalous states of machines arranged in a factory automation (FA) system or a man","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-12007760","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-12007760","citation_suggestion":"Patentable. \"Anomaly detection and diagnosis in factory automation system using pre-processed time-delay neural network with loss function adaptation\" (US-12007760). https://patentable.app/patents/US-12007760","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-12007760","json":"https://patentable.app/api/llm-context/US-12007760","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T14:43:02.488Z"}