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工業技術研究院

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技術名稱: 汽車零組件機台動態保養維護管理技術

技術簡介

透過設備擷取沖床控制器、感測器參數,應用LSTM(長短期記憶)深度學習方法預測油溫,將數據做轉化,假設每個輸入數據與前幾個陸續輸入數據有關係,使用前一時間步(t-1)的值來預測下一時間步(t+1)的預測結果,藉由時序分析動態數列,適時提出保養建議

Abstract

Through the equipment to capture the press controller, sensor parameters, application LSTM (Long Short-Term Memory) deep learning for predicting the depth of the oil temperature, the data conversion do, assuming that each input data associated with the input data before several successively, before using a value of the time step (t-1) to the results of prediction of the next time step (t + 1), the timing analysis by dynamic series, made maintenance recommendations.

技術規格

提升稼動率3~5%

Technical Specification

Increase utilization rate by 3~5%

技術特色

透過設備擷取沖床控制器、感測器參數,應用LSTM(長短期記憶)深度學習方法預測油溫,將數據做轉化,假設每個輸入數據與前幾個陸續輸入數據有關係,使用前一時間步(t-1)的值來預測下一時間步(t+1)的預測結果,藉由時序分析動態數列,適時提出保養建議

應用範圍

可應用於任何工具機,不侷限沖床

接受技術者具備基礎建議(設備)

1.作業系統環境:Windows 64位元作業系統2.硬體規格需求:CPU、RAM、HD

接受技術者具備基礎建議(專業)

機械背景專業人才

技術分類 機械製造業

聯絡資訊

聯絡人:黃一萍 工業物聯網技術組

電話:+886-3-5913817 或 Email:yiping@itri.org.tw

客服專線:+886-800-45-8899

傳真:+886-3-5826564

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