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Featured researches published by Pengchao Chen.


Volume 4: Pipelining in Northern and Offshore Environments; Strain-Based Design; Risk and Reliability; Standards and Regulations | 2012

Study on a Method Monitoring Oil and Gas Pipelines in Permafrost Regions

Yunbin Ma; Dongjie Tan; Ning Song; Pengchao Chen; Tao Ma

Based on conditions of oil and gas pipelines in permafrost regions, this paper demonstrates a method for monitoring pipeline stress and displacement as well as permafrost temperature field. To measure pipeline displacement, Total Station measuring technique which calculates displacement by measuring the change of pipeline sign post was adopted; and to monitor pipeline stress and temperature field of permafrost, Fiber Grating Sensing technique was used. This method has been applied to Pipeline No. A for a year, according to the test results, during the year, displacements of different degrees have been occurred to the pipeline; this pipeline was not influenced by frost heave in winter but was influenced by thaw collapse in summer. Due to this monitoring method for oil and gas pipelines in permafrost regions, the condition of permafrost and the change of pipeline under the impact of permafrost were successfully monitored; therefore, this method is effective and feasible.Copyright


2008 7th International Pipeline Conference, Volume 2 | 2008

A Fiber Bragg Grating Sensing System and Its Application to Monitoring Landslides and Associated Pipelines

Pengchao Chen; Jianping Liu; Jianbin Hao; Hongyuan Jing; Jianchun Zhao

The integrity of oil and gas pipelines is seriously threatened by landslides and other geohazards in tough terrain in western China. Monitoring the landslides with slow, continual movements and the strain build up in pipelines due to landslides is an effective way to maintain the serviceability of pipelines. In this paper, a monitoring system based on Fiber Bragg Grating (FBG) sensors is developed and applied. The system is made up of four related parts: the pipeline strain measurement of the with FBG strain sensors, the soil-pipeline contact pressure detecting with FBG soil pressure cells, the landslide inner deformation monitoring with pipe strain gages and the landslide surface monitoring with a special buried concrete beam with FBG sensors. The system is used to monitor a huge, slow moving landslide and the pipeline affected by it. The monitoring results are analyzed and the pipeline integrity is assessed basing the monitoring results. The FBG system has been proved to be suitable to monitor landslides and pipelines automatically and real-timely.Copyright


Archive | 2011

Method and system for monitoring and warning pipeline landslide and method for constructing system

Jianping Liu; Jianbin Hao; Pengchao Chen; Hongyuan Jing; Bing Han; Dongjie Tan


Archive | 2010

Method and system for monitoring and warning pipeline landslide surface displacement and method for constructing system

Jianbin Hao; Jianping Liu; Pengchao Chen; Hongyuan Jing; Yi Guo; Yongjun Cai


Archive | 2009

Device for monitoring landslide interior conduit stress based on optical fiber and grating

Pengchao Chen; Jianbin Hao; Jianping Liu; Zhixin Hu; Yunbin Ma; Yongjun Cai


Archive | 2009

Monitoring pre-warning system for influence of landslide to pipeline

Jianping Liu; Jianbin Hao; Hongyuan Jing; Zhixin Hu; Yunbin Ma; Pengchao Chen; Yongjun Cai


Archive | 2012

System for monitoring oil-gas pipeline in mining subsidence area and constructing method thereof

Yunbin Ma; Zhangzhong Wu; Pengchao Chen; Yi Sun; Bing Han; Hongyuan Jing; Jianping Liu; Honghui Qiu; Xiliang Yang


Archive | 2009

Pipeline landslide surface displacement monitoring pre-alarming system based on fiber grating

Jianbin Hao; Jianping Liu; Pengchao Chen; Hongyuan Jing; Yi Guo; Yongjun Cai


Archive | 2009

Pipeline landslide monitoring pre-alarming system based on fiber grating

Jianping Liu; Jianbin Hao; Pengchao Chen; Hongyuan Jing; Bing Han; Dongjie Tan


Archive | 2012

Method and system for monitoring and warning influence of landslide on pipeline

Jianping Liu; Jianbin Hao; Hongyuan Jing; Zhixin Hu; Yunbin Ma; Pengchao Chen; Yongjun Cai

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