## 1 Introduction  
Building resilient, ecological and sustainable infrastructure systems is increasingly becoming important since these systems degrade with time and are prone to damage when they are subjected to natural hazards and other unexpected disturbances. Pipelines, such as gas and utility pipeline systems and networks, are some of the most critical components of civil infrastructure. Therefore, to meet the goal that they have highly reliable serviceability performance under general or unforeseen loading scenarios, they must be properly designed to resist damage and deterioration over their entire lifespans. More importantly, implementation and utilization of an effective structural health monitoring system to assure the safety and potential damage detection of pipeline systems is important. Structural health monitoring can be divided into three major components including damage identification and its associated feature characterization, algorithm interpretation for diagnosis and prognostics, and structural reliability and risk assessment [1; 2; 3]. In engineering applications, composite structures have several distinct advantages such as high strength/weight ratio and corrosion resistance property, especially under the freeze andthaw cycle effects. Some disadvantages of composite structures are that they are prone to matrix cracks, fiber breakage, and delamination. These problems and faults are usually invisible and may lead to catastrophic structural failures [4; 5]. Design methods, manufacturing process, and quality control are common factors that may cause internal and external damage. Several main failure modes of fiber reinforced polymer composites (FRP) include temperature-induced failure, corrosion-induced failure, bend failure, tensile failure, stress failure, impact failure, attachment joint failure, improper installation, etc. These failure types are complex and are not easy to identify, localize and quantify especially when structures are subjected to joint effects of multiple factors. Different monitoring and analytical approaches have been proposed and employed for damage identification. By employing an improved conjugated beam method (ICBM), distributed structural deformation was monitored when the structure was subjected to combined actions of loads, support settlements and temperature variations [6]. This method has also been used to identify the settlement and lateral displacement of a statically indeterminate shield tunnel [7]. A theory regarding a long gauge strain influence line coefficient was introduced to detect damage and evaluate the bearing capacity of a bridge [8]. For long-gauge fiber applications, overall bonding and point fixation methods were investigated experimentally to develop non-slippage optical fibers, and critical effective sensing length was further studied [9]. A type of long distance fiber based sensing and monitoring system was employed to collect vibration signal responses of soil around the pipeline, and classify different kinds of activities using an artificial neural network [10]. A hydrostatic leak test for a water pipeline was studied using a distributed optical fiber vibration sensing system, which was based on phase-sensitive optical time-domain reflectometer (OTDR) technology [11] and fatigue damage identification for composite pipeline systems using electrical capacitance sensors [12]. A modal macro-strain vector was proposed and verified as an efficient damage identification algorithm to localize damage for flexural structures by directly extracting modal parameters from the dynamic responses of macro-strain [13; 14]. By using macro-strain based distributed sensing and high-density point sensing, a comprehensive comparison of macro-strain modes and displacement modes was presented [15]. Local parameters such as bending stiffness and the global parameters, such as mass density and rotational stiffness of support, were well identified by introducing these parameters in the objective function and updating the finite element model [16].