生產研發實驗產生的量測數據資料(非隨機數據),有很多有用的內涵.經過解析可評估與判斷製程的優劣.一般以圖形或計算求得內含的誤差:偏移offset與轉換率gain的干擾狀況.課程中介紹特定的補償修正方法.以實務應用為主.從標準的實驗設計,儀器設備規格的選取,整體結構的精確度估算方法,數據採集的處理工具,報告記錄。目的在學習正確的實驗規劃與設計步驟。課程內容包含: 實驗數據的解讀與分析, 繪圖工具軟體演練與記錄製作. 並介紹誤差干擾排除, 校準與定性的技術。實作項目則選取溫度或阻抗等 搭配數據擷取器Data aquisition board( NI DAQ6008) ,利用人工智能軟體Python建立一個完整的實驗數據解析的軟硬體系統為目標。

Quantitative data (non-random data) generated by production research and development experiments have many useful connotations. Through analysis, the advantages and disadvantages of the process can be evaluated and judged. Generally, the errors contained in it are obtained by using graphics or calculations: offset offset and conversion rate ga The interference situation of in. The course introduces specific compensation correction methods. It focuses on practical applications. From standardized experiment design, selection of instrument equipment specifications, accurate estimation methods of overall structure, data collection processing tools, and report records. The purpose is to learn correct experimental planning and design steps. The course content includes: interpretation and analysis of experiment data, practice of drawing tool software and recording. It also introduces the techniques of error interference exclusion, calibration and qualitative. The actual project should select temperature or impedance, etc. The data aquisition board (NI DAQ6008) is used to create a complete software and hardware system for experimenting with data analysis using artificial intelligence software Python.

自編講義

Self-edited lecture