Provided are a method for predicting a failure of vessel propulsion equipment using machine learning and a system thereof. In order to use an RUL prediction model, characteristics of data are extracted and processed to generate a status indicator through the PCA. By dividing operation areas and standardizing result data for each operation area, the failure of equipment can be predicted based on a learning result input to machine learning.

    머신러닝을 이용하여 함정 추진 장비의 고장을 예측하는 방법 및 시스템이 제공된다. RUL 예측 모델을 사용하기 위해 데이터의 특징을 추출 및 가공하여 PCA를 통해 상태표시기를 생성하고, 운용 구역을 나누어 운용 구역별로 결과데이터를 표준화하여 머신러닝에 입력한 학습결과를 기준으로 장비의 고장 예측을 가능하도록 한다.


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    Title :

    Method and system for predicting the failure of naval ship propulsion system using machine learning


    Additional title:

    머신러닝을 이용하여 함정 추진 장비의 고장을 예측하는 방법 및 시스템


    Contributors:

    Publication date :

    2020-03-11


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Korean


    Classification :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B63G OFFENSIVE OR DEFENSIVE ARRANGEMENTS ON VESSELS , Angriffs- oder Verteidigungsanordnungen auf Schiffen / G05B Steuer- oder Regelsysteme allgemein , CONTROL OR REGULATING SYSTEMS IN GENERAL



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