結合智慧感測標籤與支持向量機快速判定混凝土裂縫位置

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姓名

楊謦豪(Qing-Hao Yang) 查詢紙本館藏

畢業系所

土木工程學系

論文名稱

結合智慧感測標籤與支持向量機快速判定混凝土裂縫位置
(Combining smart sensing tags and support vector machine to determine the location of concrete cracks)

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至系統瀏覽論文 (2027-6-30以後開放)

摘要(中)

台灣之社會與經濟發展至今，國土上的土木建築物逐漸增多，在土地資源有限的情況下已經無法再隨意建造大型建築物了。中華民國內政部建築研究所亦提出高樓建築不能在僅僅是提供空間作居住或辦公使用，還需要考慮使用時的安全、通訊、防災、節能等問題。將高資訊科技化與人性化融入建築設計，建造智慧建築，並且以此間接提升國家競爭力。
本研究結合RFID智慧感測標籤與3D列印等技術用作感測混凝土裂縫位置，並加上SVM支持向量機尋找資料特徵，以加速判斷裂縫存在與否。結合以上技術，本研究以智慧化安全防災為目標，開發一套非破壞性檢測系統，用於快速、方便且價格低廉地檢測混凝土裂縫之位置。使用RFID智慧感測標籤可以降低檢測系統中感測器的價格花費。當混凝土有裂縫產生時，該區域的混凝土滲水量將會上升，而埋置於混凝土內部的RFID智慧感測標籤就可以感測環境中的水分變化、回傳相應的數值。使用3D列印技術可以為RFID智慧感測標籤提供一定的保護，避免芯片遭受混凝土侵蝕。經由讀取器收集到的數據可由SVM支持向量機做分類，可以獲得快速且準確的結果。
經過本研究的嘗試，當混凝土結構物是處於潮濕的環境中，經由SVM支持向量基分類，正確找到混凝土裂縫是否有經過的機率為98.82%。且該結果已經透過其他數項AI人工智慧模型的效果指標驗證其精度。透過正確分類數據，可以推斷產生該數據的感測區域是否有裂縫通過。

摘要(英)

Integrate high information technology and humanization into architectural design, build smart buildings, and indirectly enhance national competitiveness. Taiwan′s social and economic development has gradually increased the number of civil buildings on the land. Given the limited land resources, building large buildings at will is no longer possible. The Architectural Research Institute of the Ministry of Internal Affairs of the Republic of China also pointed out that high-rise buildings should not only provide space for living or office use but also consider issues such as safety, communication, disaster prevention, and energy saving during use.
In this study, technologies such as RFID smart sensing tags and 3D printing are used to sense the location of concrete cracks, and SVM support vector machine is used to find data features to speed up the judgment of the existence of cracks. Combining the above technologies, this research aims at intelligent safety and disaster prevention and develops a non-destructive detection system to detect the location of concrete cracks quickly, conveniently, and inexpensively. Using RFID smart sensor tags can reduce the cost of sensors in the detection system. When there are cracks in the concrete, the amount of water seepage in the concrete will increase, and the RFID smart sensor tag embedded in the concrete can sense the moisture change in the environment and return the corresponding value. 3D printing technology can provide specific protection for the RFID smart sensor tag to prevent the chip from being corroded by concrete. The data collected via the reader can be sorted by the SVM support vector machine, which can obtain fast and accurate results.
After the attempts of this study, when the concrete structure is in a wet environment, the probability of correctly finding whether the concrete crack has passed through the SVM support vector basis classification is 98.82%. Moreover, the result has been verified by the performance indicators of several other AI artificial intelligence models. By correctly classifying the data, it is possible to infer whether a crack has passed through the sensing area where the data was generated.

關鍵字(中)

★ RFID 智慧感測標籤
★ 3D列印
★ SVM支持向量機
★ AI人工智慧

關鍵字(英)

★ RFID smart tag
★ 3D printing
★ SVM support vector machine
★ AI artificial intelligence model

論文目次

摘要 I
ABSTRACT II
致謝 IV
目錄 V
圖目錄 VIII
表目錄 XI
一、緒論 1
1-1 研究背景與動機 1
1-2 研究目的 2
1-3 論文架構 2
二、文獻回顧 4
三、研究方法 8
3-1 研究架構 8
3-2 RFID智慧感測標籤 10
3-3 破壞指標 12
3-4 支持向量機 16
3-4-1 最優超平面 16
3-4-2 不完美之樣本的最佳超平面 20
3-4-3 核函數 23
3-5 模型效果分析方法 25
四、實驗規劃與設計 27
4-1實驗設備 27
4-1-1實驗儀器 27
4-1-2 軟體 29
4-2 數據來源 30
4-2-1 一般梁設計 30
4-2-2 實驗設置 32
4-2-3 實驗流程 33
4-2-4 實驗梁裂縫分布 34
4-3 模型特徵選擇 37
4-4 模型輸入之訓練與測試資料說明 40
五、成果與討論 44
5-1 以破壞指標為單一特徵參數輸入訓練之模型 44
5-2 以讀取值與初始值為雙特徵輸入訓練之模型 56
5-3 以破壞指標與讀取距離為雙特徵輸入訓練之模型 68
5-4 以破壞指標與讀取夾角為雙特徵輸入訓練之模型 80
5-5 以破壞指標、讀取距離及讀取夾角做為三項特徵輸入訓練之模型 92
5-6 五維特徵之模型 104
5-7 總指標模型 113
六、結論與未來展望 130
6-1 結論 130
6-2 未來建議 132
七、參考文獻 133

參考文獻

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指導教授

林子軒(Tzu-Hsuan Lin)

審核日期

2022-8-17

推文