ABNORMALITY DIAGNOSTIC DEVICE AND METHOD

PROBLEM TO BE SOLVED: To provide an abnormality diagnostic device capable of accurately diagnosing abnormality of a railway vehicle, and a method.SOLUTION: An abnormality diagnostic device relating to one embodiment comprises a learning section and a diagnostic section. The learning section learns d...

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Bibliographische Detailangaben
1. Verfasser:	EZAWA TORU
Format:	Patent
Sprache:	eng ; jpn
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING CONTROL OR REGULATING SYSTEMS IN GENERAL CONTROLLING COUNTING ELECTRIC EQUIPMENT OR PROPULSION OF ELECTRICALLY-PROPELLEDVEHICLES ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES, IN GENERAL ENSURING THE SAFETY OF RAILWAY TRAFFIC FUNCTIONAL ELEMENTS OF SUCH SYSTEMS GUIDING RAILWAY TRAFFIC MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES MEASURING MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS PERFORMING OPERATIONS PHYSICS RAILWAYS REGULATING TESTING TESTING STATIC OR DYNAMIC BALANCE OF MACHINES ORSTRUCTURES TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR TRANSPORTING VEHICLES IN GENERAL
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Zusammenfassung:	PROBLEM TO BE SOLVED: To provide an abnormality diagnostic device capable of accurately diagnosing abnormality of a railway vehicle, and a method.SOLUTION: An abnormality diagnostic device relating to one embodiment comprises a learning section and a diagnostic section. The learning section learns data selection conditions for selecting sensor data used for a diagnosis of a diagnostic object based on a model generated on the basis of the sensor data of the diagnostic object of a railway vehicle. The diagnostic section diagnoses abnormality of the diagnostic object based on the sensor data satisfying the data selection conditions and a diagnosis model obtained by modeling a relation between the sensor data and the abnormality of the diagnostic object.SELECTED DRAWING: Figure 1 【課題】鉄道車両の異常を精度よく診断できる異常診断装置及び方法を提供する。【解決手段】一実施形態に係る異常診断装置は、学習部と、診断部と、を備える。学習部は、鉄道車両における診断対象のセンサデータに基づいて生成されるモデルに基づいて、診断対象の診断に利用するセンサデータを選択するためのデータ選択条件を学習する。診断部は、データ選択条件を満たすセンサデータと、センサデータと診断対象の異常との関係をモデル化した診断モデルと、に基づいて、診断対象の異常を診断する。【選択図】図１