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  "author": "Gabriel Michau",
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  "author": "Gabriel Michau",
            
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  "doi": "10.57702/o5fy1y66",
            
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  "doi_date_published": null,
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  "doi_date_published": "2024-12-16",
            
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  "extra_authors": [
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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "Olga Fink",
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      "extra_author": "Olga Fink",
            
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      "name": "condition-monitoring",
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      "name": "condition-monitoring",
            
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      "title": "Condition Monitoring"
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      "title": "Condition Monitoring"
            
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Fault Detection",
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      "name": "fault-detection",
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      "name": "fault-detection",
            
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      "title": "Fault Detection"
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      "title": "Fault Detection"
            
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    }
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  "metadata_modified": "2024-12-16T17:28:18.226702",
            
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  "name": 
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  "name": 
            
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for-fault-detection-in-high-dimensional-condition-monitoring-signals",
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for-fault-detection-in-high-dimensional-condition-monitoring-signals",
            
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  "notes": "Complex industrial systems are continuously monitored by a 
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  "notes": "Complex industrial systems are continuously monitored by a 
            
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large number of heterogeneous sensors. The diversity of their 
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large number of heterogeneous sensors. The diversity of their 
            
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operating conditions and the possible fault types make it impossible 
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operating conditions and the possible fault types make it impossible 
            
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to collect enough data for learning all the possible fault patterns.",
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to collect enough data for learning all the possible fault patterns.",
            
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      "name": "Condition Monitoring",
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      "name": "Fault Detection",
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      "name": "Feature Learning",
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    }
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  ],
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  "title": "Feature Learning for Fault Detection in High-Dimensional 
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  "title": "Feature Learning for Fault Detection in High-Dimensional 
            
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Condition-Monitoring Signals",
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Condition-Monitoring Signals",
            
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}
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}