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다양한 운행 환경에 적용 가능한 철도차량 현가장치 고장 진단
박찬희(Chan Hee Park),이준민(Junmin Lee),김수호(Sooho Kim),이동기(Dong-Ki Lee),나규민(Kyumin Na),송주환(Joowhan Song),윤병동(Byeng D. Youn) 대한기계학회 2018 대한기계학회 춘추학술대회 Vol.2018 No.12
This research focused on introducing a hybrid method to identify the damper failures on rail vehicle suspensions using some spectral information. The investigated system has been announced at a competition named as 2017 Data Challenge organized by prognostics and health management (PHM) society, and there were three kinds of variations that the failure detection method should consider; (1) payload, (2) speed and, (3) track. Due to the different operating conditions with no failure data of the system, two methods, which could be represented by data-driven and physics based approach, have been aggregated. First, a data-driven approach, targeting the different payload and speed conditions, was introduced which computes root mean square error (RMSE) between training data set and validation data set at all the sensors. Second, the ensemble method, which integrates physical model estimating the system parameters (SPE) and Pearson correlation coefficient (PCC) based approach, was developed for the different track condition. The result from the proposed method was led to the third prize in 2017 Data Challenge. Although the result could be improved if more information of the system is provided, this study could give a general methodology of diagnosing failures in the bogie car suspensions.
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