Prognostic and health management system for system management and method thereof
A machine-learning-based prognostic and health management system includes a machine monitor, a command receiver, a processor, and an alarm. The machine monitor dynamically receives to-be-tested machine data that is associated with a to-be-tested machine's operations. The command receiver dynami...
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Main Authors | , , , |
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Format | Patent |
Language | Chinese English |
Published |
01.02.2023
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Subjects | |
Online Access | Get full text |
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Abstract | A machine-learning-based prognostic and health management system includes a machine monitor, a command receiver, a processor, and an alarm. The machine monitor dynamically receives to-be-tested machine data that is associated with a to-be-tested machine's operations. The command receiver dynamically receives a model assigning command. The processor dynamically applies a damage early warning machine learning model that is assigned via the model assigning command for processing the to-be-tested machine data to predict an anomaly probability that an anomaly occurs to the to-be-tested machine. Also, the processor generates a damage possibility warning dynamically according to the anomaly probability for determining whether to keep the to-be-tested machine running or not. The alarm indicates the anomaly probability according to the damage possibility warning and indicates whether to keep the to-be-tested machine running or not. |
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AbstractList | A machine-learning-based prognostic and health management system includes a machine monitor, a command receiver, a processor, and an alarm. The machine monitor dynamically receives to-be-tested machine data that is associated with a to-be-tested machine's operations. The command receiver dynamically receives a model assigning command. The processor dynamically applies a damage early warning machine learning model that is assigned via the model assigning command for processing the to-be-tested machine data to predict an anomaly probability that an anomaly occurs to the to-be-tested machine. Also, the processor generates a damage possibility warning dynamically according to the anomaly probability for determining whether to keep the to-be-tested machine running or not. The alarm indicates the anomaly probability according to the damage possibility warning and indicates whether to keep the to-be-tested machine running or not. |
Author | PAN, YING-HAO CHEN, MENG-JEN WEN, YUAN-HAO CHEN, YEN-JEN |
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Snippet | A machine-learning-based prognostic and health management system includes a machine monitor, a command receiver, a processor, and an alarm. The machine monitor... |
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SubjectTerms | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS PHYSICS |
Title | Prognostic and health management system for system management and method thereof |
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