scholarly journals Development and Application of Methane Leakage Monitoring System for Gas Transmission Pipeline

2021 ◽  
Vol 5 (6) ◽  
pp. 44-49
Author(s):  
Qijun Wang ◽  
Shiqi Wei

Oil and gas pipeline transportation, as a relatively safe way of oil and gas transportation, undertakes most of the transportation tasks of crude oil and natural gas. Oil and gas pipeline accidents affect a wide range of consequences. Therefore, the oil and gas pipeline leakage detection is paid more and more attention. In this paper, ultra-low power methane gas sensor is selected to collect methane gas concentration in the air, and wireless network technology is used to build a wireless network sensor system with 4G function. Through the sensor distribution along the pipeline, it can intuitively and accurately judge whether there is a micro-leakage in the pipeline, and understand the diffusion situation after the leakage. The sensor system has high reliability and stability, and has high value of popularization and application.

2014 ◽  
Vol 1044-1045 ◽  
pp. 1406-1410
Author(s):  
Liu Miao ◽  
Man Cang Yuan ◽  
Cheng Qiang Wang ◽  
Rui Qiang Gao

For improving the reliability and resource utilization of oil and gas pipeline Supervisory Control and Data Acquisition (SCADA) system, the application framework of oil and gas pipeline SCADA system based on cloud computing and a high reliability scheduling algorithm is proposed in the paper. Simulation results show the SCADA system based on cloud computing with new scheduling algorithm can realize history data backup in many computers and real-time data processed with primary-backup copy. So, the new application framework and new scheduling algorithm can provide better reliability and improve the resource utilization of system.


Author(s):  
Mark A. Smith ◽  
Linda M. Ward

The need to develop an accurate, autonomous, and economical pipeline mapping system capable of use within a wide range of pipeline sizes, configurations, operating pressures and specific uses was accomplished, resulting in the manufacture of a series of unique inertial-based smart probes. This paper reviews the innovative technology developed to identify, map and plan for the management and integrity of pipeline assets through use of the smart probe technology. Today’s owners and operators of the world’s pipeline infrastructure are faced with competitive pressures and regulatory constraints which are creating increasingly stringent demands to manage our pipeline assets in an efficient and responsible manner. Billions of dollars will be spent over the next 20 years to rehabilitate the world’s infrastructure and oil and gas pipeline systems. “Out of sight – out of mind” no longer applies. Now, more than ever, pipeline owners and operators need solid information to plan for the challenges of tomorrow.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Michael C. W. English ◽  
Gilles E. Gignac ◽  
Troy A. W. Visser ◽  
Andrew J. O. Whitehouse ◽  
James T. Enns ◽  
...  

Abstract Background Traits and characteristics qualitatively similar to those seen in diagnosed autism spectrum disorder can be found to varying degrees in the general population. To measure these traits and facilitate their use in autism research, several questionnaires have been developed that provide broad measures of autistic traits [e.g. Autism-Spectrum Quotient (AQ), Broad Autism Phenotype Questionnaire (BAPQ)]. However, since their development, our understanding of autism has grown considerably, and it is arguable that existing measures do not provide an ideal representation of the trait dimensions currently associated with autism. Our aim was to create a new measure of autistic traits that reflects our current understanding of autism, the Comprehensive Autism Trait Inventory (CATI). Methods In Study 1, 107 pilot items were administered to 1119 individuals in the general population and exploratory factor analysis of responses used to create the 42-item CATI comprising six subscales: Social Interactions, Communication, Social Camouflage, Repetitive Behaviours, Cognitive Rigidity, and Sensory Sensitivity. In Study 2, the CATI was administered to 1068 new individuals and confirmatory factor analysis used to verify the factor structure. The AQ and BAPQ were administered to validate the CATI, and additional autistic participants were recruited to compare the predictive ability of the measures. In Study 3, to validate the CATI subscales, the CATI was administered to 195 new individuals along with existing valid measures qualitatively similar to each CATI subscale. Results The CATI showed convergent validity at both the total-scale (r ≥ .79) and subscale level (r ≥ .68). The CATI also showed superior internal reliability for total-scale scores (α = .95) relative to the AQ (α = .90) and BAPQ (α = .94), consistently high reliability for subscales (α > .81), greater predictive ability for classifying autism (Youden’s Index = .62 vs .56–.59), and demonstrated measurement invariance for sex. Limitations Analyses of predictive ability for classifying autism depended upon self-reported diagnosis or identification of autism. The autistic sample was not large enough to test measurement invariance of autism diagnosis. Conclusions The CATI is a reliable and economical new measure that provides observations across a wide range of trait dimensions associated with autism, potentially precluding the need to administer multiple measures, and to our knowledge, the CATI is also the first broad measure of autistic traits to have dedicated subscales for social camouflage and sensory sensitivity.


Author(s):  
Mohadese Jahanian ◽  
Amin Ramezani ◽  
Ali Moarefianpour ◽  
Mahdi Aliari Shouredeli

One of the most significant systems that can be expressed by partial differential equations (PDEs) is the transmission pipeline system. To avoid the accidents that originated from oil and gas pipeline leakage, the exact location and quantity of leakage are required to be recognized. The designed goal is a leakage diagnosis based on the system model and the use of real data provided by transmission line systems. Nonlinear equations of the system have been extracted employing continuity and momentum equations. In this paper, the extended Kalman filter (EKF) is used to detect and locate the leakage and to attenuate the negative effects of measurement and process noises. Besides, a robust extended Kalman filter (REKF) is applied to compensate for the effect of parameter uncertainty. The quantity and the location of the occurred leakage are estimated along the pipeline. Simulation results show that REKF has better estimations of the leak and its location as compared with that of EKF. This filter is robust against process noise, measurement noise, parameter uncertainties, and guarantees a higher limit for the covariance of state estimation error as well. It is remarkable that simulation results are evaluated by OLGA software.


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