臺灣博碩士論文加值系統

現代科技產業中量測系統技術被普遍使用，尤其當感測器失效偵測及隔離是避免裝備損壞、確保系統性能與可靠度的重要關鍵。本研究探討類神經網路在感測器失效偵測之應用，類神經網路具有分散式平行處理、學習能力的優點，可運用來估測感測器運作狀態，處理即時性的失效與判別。本文提出失效偵測模式並以F-16飛機操控系統感測器為研究對象，以飛機正常飛行及各種系統感測器失效狀況模擬，運用訓練過的類神經網路進行狀態估測值與感測器量測值之殘差計算，再配合失效偵測模式中的偵測邏輯及臨限值設定與判斷，達到感測器之失效偵測。最後以三種不同失效類型驗證分析，以驗證其偵錯能力。

The paper investigates the application of sensor fault detection design in neural networks. The sensor technology is a key point for avoiding break down with equipment and ensuring the running and reliability of system in industry for sensor fault detection and isolation. Neural networks(NNs) used to provide analytical redundancy to estimate working status for sensor and to treat real fault detection and judgment in detection logic, because they have the following advantages: robustness against unmodeled dynamics, capability of handing nonlinear dynamics, modular and systematic design, and potential for unanticipated failures. It’s show that program to construct flying condition via F-16 aircraft model and to collect regular and fault information as well. The developed back propagation NNs were trained flying information, and then, to fulfill detection by residuals from comparing the NNs output with the sensor output. The faults decision employed logic detection and threshold value setting in the proposed fault detection mode. Finally, the paper verify it’s detects ability among three various fault type analysis.

中文摘要I
英文摘要II
誌謝III
目錄IV
表目錄VI
圖目錄VII
符號說明IX
第一章 緒論1
1.1研究緣起及背景1
1.2研究目的3
1.3研究方法與架構4
1.4論文大綱6
第二章文獻探討7
2.1感測器失效偵測7
2.2類神經網路架構11
2.2.1類神經網路模式分類11
2.2.2倒傳遞類神經網路13
2.3F-16飛機背景介紹20
第三章飛機模式之建立22
3.1運動座標22
3.2F-16飛機數學模式23
3.3F-16飛機模式建構27
3.4F-16飛機正常飛行模式30
3.5飛機失效狀況分析33
3.6飛機失效狀況之感測器敏感度分析42
第四章失效偵測模式建立45
4.1類神經網路運算流程46
4.2偵測邏輯48
4.3偵測臨限值設定52
4.4感測器失效偵測模擬分析53
4.5本章小結61
第五章結論與未來研究方向62
5.1結論62
5.2未來研究方向63
參考文獻64

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