植基於關聯式分類技術之機車噴射引擎診斷輔助系統 = An Associa...
國立高雄大學資訊工程學系碩士班

 

  • 植基於關聯式分類技術之機車噴射引擎診斷輔助系統 = An Associative-Classification Based Motorcycle Injection Engine Diagnosis Support System
  • 紀錄類型: 書目-語言資料,印刷品 : 單行本
    並列題名: An Associative-Classification Based Motorcycle Injection Engine Diagnosis Support System
    作者: 蔡國彬,
    其他團體作者: 國立高雄大學
    出版地: [高雄市]
    出版者: 撰者;
    出版年: 民100
    面頁冊數: 75葉圖,表格 : 30公分;
    標題: 機車噴射引擎
    標題: Motorcycle injection engine
    電子資源: http://handle.ncl.edu.tw/11296/ndltd/28736505678011390661
    附註: 參考書目:葉61-64
    摘要註: 近來年所有4期環保法規的舊車款都已停止販售,往後機車製造廠推出的新車款將採用和汽車類似的噴射供油系統,與傳統引擎相較之下,機車噴射引擎的檢測維修更加複雜,很難單純依賴機師的經驗進行問題判斷,必須仰賴輔助的系統。然而現階段機車維修方式需透過診斷器讀取ECU所判定的故障碼,由於ECU數據相當複雜,工程師根據測試經驗調整ECU的參數需花費不少時間,並無一套完整系統輔助工程師動態的參考歷史記錄做出更即時準確的診斷。本研究以國內某機車製造業者為例,旨在建構一套機車噴射引擎的診斷輔助系統。我們的系統收集該業者的ECU資訊及故障分析相關資料,建置出資料倉儲,並結合線上分析處理(OLAP)與我們發展的資料探勘技術。我們的探勘工具採用關聯式分類探勘,運用我們提出R-CMAR演算法,可以有效減少資料的儲存量。另外,我們也使用規則預存DB的方法,結合資料庫管理系統的索引和查詢處理功能,以加快系統的回應時間。從實驗中印證,我們提出的演算法在效能上確實優於其它演算法,可以快速回答使用者線上進行噴射引擎故障分析的查詢。  In the recent years, due to the discontinuation of the old type scooter of the fourth Environmental regulations, scooter manufacturers have to launch a new type of scooter using the injection fuel supply system similar to the automobile. Comparing with the traditional engines, the diagnosis of injection engines are too difficult to only count on the experiences of mechanics. A diagnosis support system is necessary. The current procedure for repairing a scooter uses a diagnostic device to read the defect code diagnosed by ECU. However, due to the complication of the ECU data, engineers have to spend a lot of time adjusting the ECU's parameters based on their test experience. There is no complete set of systems to help the engineer make a prompt and correct diagnosis. In this thesis, we take some motorcycle manufacture in Taiwan as a case study, aiming to develop a motorcycle injection engine diagnosis support system. Our system is based on a data warehouse collecting data derived from the ECU information and the defect analyses by the manufacturer, and provides OLAP and our developed data mining tool. Our mining tool adopts our proposed R-CMAR algorithm, an associative-classification technique, which can effectively reduce the amount of stored data. In addition, we use the concept of prestore to store the candidate rules in DB in order to combine the index and inquiry processing function of the data management system to speed up the response time of the system. According to the experiments, our proposed algorithm is superior to other algorithms, through which our system can provide an on-line and interactive diagnosis environment.
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310002135021 博碩士論文區(二樓) 不外借資料 學位論文 TH 008M/0019 464103 4464 2011 一般使用(Normal) 在架 0
310002135013 博碩士論文區(二樓) 不外借資料 學位論文 TH 008M/0019 464103 4464 2011 c.2 一般使用(Normal) 在架 0
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