Study on the detection arm accuracy of a leaf spring caliper for detecting internal convex defects in gas pipelines

The safety of pipelines is an important factor in the natural gas industry. In natural gas fields, some pipelines are less than 200 mm in diameter, and these pipes cannot be inspected in ordinary inspection facilities. This paper describes the development of a leaf spring caliper to solve this issue. The factors that influence the accuracy of the detection arm were studied, a theoretical model of the leaf spring was constructed, and simulations were used to verify the theoretical model. Subsequent experiments were designed to study the influence of the accuracy of the detection arm under different working conditions. The experimental results indicate that the strain is proportional to the vertical displacement at the end of the detection arm under testing conditions. Based on an analysis of the process of a detection arm passing different height defects, a correction algorithm of the length was developed. In addition, a correction algorithm was developed for the height to adjust the speed and compression. The effectiveness of the developed correction formula was experimentally demonstrated.

[1]  V. E. Loskutov,et al.  Improving the quality of diagnostics of gas-main pipelines by using a device for automated control of the velocity of pig flaw detectors , 2008 .

[2]  Tarek Zayed,et al.  Evidential reasoning-based condition assessment model for offshore gas pipelines , 2016 .

[3]  Yi Huang,et al.  Experimental study on seawater-pipeline internal corrosion monitoring system , 2008 .

[4]  H. S Choi,et al.  Acceptance criteria of defects in undersea pipeline using internal inspection , 2003 .

[5]  Simon Pedersen,et al.  Challenges in Slug Modeling and Control for Offshore Oil and Gas Productions: A Review Study , 2017 .

[6]  Marco Pirola,et al.  A novel smart caliper foam pig for low-cost pipeline inspection - Part B: Field test and data processing , 2015 .

[7]  Shuhai Liu,et al.  Dynamic simulation and experimental research on the motion of odometer passing over the weld , 2016 .

[8]  Dariush Mowla,et al.  Mathematical modeling and simulation of pigging operation in gas and liquid pipelines , 2009 .

[9]  M H S Siqueira,et al.  The use of ultrasonic guided waves and wavelets analysis in pipe inspection. , 2004, Ultrasonics.

[10]  P Hopkins,et al.  Best practice for the assessment of defects in pipelines – Corrosion , 2007 .

[11]  Hossam A. Gabbar,et al.  Review of pipeline integrity management practices , 2010 .

[12]  Moon Ho Park,et al.  Ultrasonic inspection of long steel pipes using Lamb waves , 1996 .

[13]  Xiaolong Li,et al.  Experimental study on the probe dynamic behaviour of feeler pigs in detecting internal corrosion in oil and gas pipelines , 2015 .

[14]  Gwan Soo Park,et al.  Development of the caliper system for a geometry pig based on magnetic field analysis , 2003 .

[15]  Marco Pirola,et al.  A novel smart caliper foam pig for low-cost pipeline inspection—Part A: Design and laboratory characterization , 2015 .

[16]  Sang Bong Kim,et al.  Speed control of PIG using bypass flow in natural gas pipeline , 2001, ISIE 2001. 2001 IEEE International Symposium on Industrial Electronics Proceedings (Cat. No.01TH8570).

[17]  Tan Tien Nguyen,et al.  Dynamic modeling and its analysis for PIG flow through curved section in natural gas pipeline , 2001, Proceedings 2001 IEEE International Symposium on Computational Intelligence in Robotics and Automation (Cat. No.01EX515).

[18]  Wenming Wang,et al.  Experimental study on dynamics of rotatable bypass-valve in speed control pig in gas pipeline , 2014 .

[19]  Sung-Ho Cho,et al.  Design and implementation of 30„ geometry PIG , 2003 .

[20]  Claudio Soligo Camerini,et al.  Feeler Pig: A Simple Way to Detect and Size Internal Corrosion , 2008 .

[21]  Luis Volnei Sudati Sagrilo,et al.  MFL signals and artificial neural networks applied to detection and classification of pipe weld defects , 2006 .

[22]  C. Guedes Soares,et al.  Reliability of pipelines with corrosion defects , 2008 .

[23]  Shuhai Liu,et al.  An experimental evaluation of the probe dynamics as a probe pig inspects internal convex defects in oil and gas pipelines , 2015 .

[24]  Gangbing Song,et al.  Experimental study of leakage detection of natural gas pipeline using FBG based strain sensor and least square support vector machine , 2014 .