عنوان المقالة:A fuzzy logic approach for pavement section classification
ماهر شاكر محمود | MAHER SHAKIR MAHMOOD | 4025
نوع النشر
مجلة علمية
المؤلفون بالعربي
Maher Mahmood, Mujib Rahman, Lars Nolle, Senthan Mathavan
الملخص العربي
Section classification is one of the primary challenges in any successful pavement management system. Sections are normally classified based on their pavement condition index in order to categorise as “good”, “moderate” and “poor”. Conventionally, this has been done by comparing various pavement distress data against threshold values. However, borderline values between two categories have significant influence on the subsequent pavement maintenance and rehabilitation decision. This study is the first attempt to create a system based on fuzzy logic to estimate the pavement condition index (PCI). In this paper, section data classifications are conducted using a fuzzy inference system (FIS) to utilise multiple distress data such as cracking, patching, bleeding and ravelling to develop a membership function for each defect. A FIS rule based system was then used to develop a fuzzified pavement condition index (PCI) for section classification. The result showed good agreement with the conventional PCI based pavement classification system. The proposed system has the potential to realistically differentiate pavement sections, which would aid to have economical maintenance and rehabilitation decision.
تاريخ النشر
30/09/2013
الناشر
International Journal of Pavement Research and Technology
رابط الملف
تحميل (135 مرات التحميل)
رابط خارجي
http://dx.doi.org/10.6135/ijprt.org.tw/2013.6(5).620
الكلمات المفتاحية
Fuzzy Logic; Pavement classification; Pavement condition index; Pavement distress; Pavement manageme
رجوع