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研擬有效預測鋪面抗滑之鋪面紋理指標

Development of Pavement Texture Index for Predicting Skid Resistance

指導教授 : 周家蓓
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摘要


鋪面在潮濕情況下時會大幅提高運具產生水滑現象之機率,並可能會提高事故發生,因此監測鋪面抗滑能力的工作更顯得重要。屬於定點抗滑儀中的動態摩擦測試儀(Dynamic Friction Tester, DFT)和英式擺錘(British Pendulum Tester, BPT)在實際應用上僅能得知鋪面局部的抗滑能力,無法得知全段道路之抗滑能力,然而影響鋪面抗滑能力的因素以鋪面紋理為最主要的因素,本研究使用動態紋理量測儀量測單一鋪面下的紋理與抗滑值,並研擬紋理指標,做為預測該鋪面在不同速度下之抗滑能力。 本研究於現地之30個鋪面樣本進行紋理與抗滑檢測,得知不同鋪面下之紋理剖面和BPN、DFT值。將紋理剖面分別利用功率頻譜密度(Power Spectral Density, PSD)分析和ISO 13565-2紋理高度分析方法得到波長參數和高度參數與BPN、不同速度下之DFT動態摩擦數進行相關性分析,結果得到從12.8mm的波長參數開始影響DFT80,102.4mm、204.8mm的波長皆對不同速度下之DFT動態摩擦數有影響,另外波長偏細質的紋理參數會影響BPN。高度參數中紋理核心部分(Rk)、紋理凹下面積(A2)、折減紋理深度(Rvk)為主要影響DFT之因素,另外,高度參數對BPN的相關性分析結果無高度的相關性。 將紋理參數與DFT50、DFT60、DFT80經由SPSS逐步迴歸法分析結果得到預測DFT50、DFT60之迴歸式R2最高為0.38和0.51,DFT80迴歸分析的結果以靠近橡膠滑片摩擦的兩條測線之迴歸式R2=0.77為最高,計算紋理指標預測之DFT80和實際DFT80誤差平均值為0.018。

並列摘要


To evaluate the skid resistance of pavement is very important. Using DFT and BPT only can evaluate the spot skid resistance, so the continuous skid resistance is unknown. However, pavement texture is the major factor to affect the pavement skid resistance. This paper uses the dynamic texture measuring meter and BPT, DFT to measure a spot pavement texture, BPN, and DFT friction coefficient. Then develop a texture index to predict the skid resistance in different speeds. From measuring the texture profiles of 30 pavement samples in the field, and then using the PSD analysis and ISO 13565-2 method to obtain different wavelength parameters and height parameters. Take these texture parameters and BPN, DFT to regression analysis. The result shows that microtexture has little influence on DFT friction coefficient, and the wavelength which is greater than 12.8mm has influence on DFT80. The 102.4mm, 204.8mm wavelength has influence on the DFT skid resistance; the microtexture has little influence on BPN. About height parameters, core roughness depth (Rk), valley area (A2) and reduced valley depth (Rvk) are the major factors to affect the DFT skid resistance; there is insufficient relation between height parameters and BPN. Use the texture parameters through the SPSS stepwise regression to obtain a regression equation for predicting the DFT50, DFT60 and DFT80. The R2 of predicting DFT50 and DFT60 regression equation are 0.38 and 0.51. The R2 of predicting DFT80 regression equation by choosing two texture profiles which are close to the rubber pads is 0.77, and the average error is 0.018.

參考文獻


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被引用紀錄


吳承晏(2013)。應用鋪面快速高程檢測資料於抗滑能力評估之初擬〔碩士論文,國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU.2013.00827

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