The current study presents a novel and high-sensitivity in-line inspection (ILI) method for gas pipelines. The proposed method is based on integrated ILI methods, optical sensor and bimorph sensor. The uniqueness of the proposed method lies in; (1) combining two advanced methods for more accurate and sensitive outcome, (2) real-time inspection of target pipeline, (3) specifically designed sensor array to estimate and locate defects in three dimensions, and (4) low power consumption and economic viability. The theoretical framework for the relationship between the sensor outputs and the presence of defect as well as the design of the sensor housing module are also developed and presented. Laboratory tests are conducted on various types of defects to illustrate the robustness and sensitivity of the method. Additionally, the conventional magnetic flux leakage (MFL) method is adopted to verify the effectiveness of the proposed method. Furthermore, for the real-world application purposes, a smart pipeline inspection gauge (smart PIG) with integrated different sensor arrays are developed for the field testing of gas pipeline networks. The two-dimensional (2-D) image produced by the sensor array is presented to visualize the inner surface of the pipeline and enable accurate identification of bolted pipe joints. A speed control system is also developed and designed to eliminate errors caused by speed spikes and maintain the speed of the smart PIG within the desired range. An analysis of the chatter vibration signal of the smart PIG running in a gas pipeline network is presented. The current research work provides a solid base towards a step change from a pilot study to a real-time, real-world application of a novel inspection method for pipelines.

当前的研究提出了一种新颖的，高灵敏度的天然气管道在线检查（ILI）方法。所提出的方法基于集成的ILI方法，光学传感器和双压电晶片传感器。所提出方法的唯一性在于：（1）结合两种先进方法以获得更准确和敏感的结果；（2）实时检查目标管道；（3）经过专门设计的传感器阵列，以在三个维度上估计和定位缺陷；（4）低功耗和经济性可行性。还开发并介绍了传感器输出与缺陷的存在之间的关系的理论框架，以及传感器外壳模块的设计。对各种类型的缺陷进行了实验室测试，以说明该方法的鲁棒性和敏感性。此外，采用传统的漏磁法（MFL）验证了该方法的有效性。此外，出于实际应用的目的，开发了具有集成的不同传感器阵列的智能管道检测仪（smart PIG），用于天然气管道网络的现场测​​试。呈现了传感器阵列产生的二维（2-D）图像，以可视化管道的内表面并能够准确识别螺栓连接的管接头。还开发并设计了速度控制系统，以消除由速度峰值引起的错误，并将智能PIG的速度保持在所需范围内。分析了燃气管道网络中运行的智能PIG的颤振信号。