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Studies On Detection And Evaluation Techniques For Coating Defects Of Buried Pipelines

Posted on:2004-06-12Degree:DoctorType:Dissertation
Country:ChinaCandidate:S L ChenFull Text:PDF
GTID:1102360092980673Subject:Precision instruments and machinery
Abstract/Summary:PDF Full Text Request
In terms of transporting liquid, such as oil, gas and water, the method of pipeline transportation has prominent advantage and has been widely used all over the world. As usually mild steel is chosen to be the material of pipelines, the external corrosion of steel becomes one important problem of influencing the reliability and the lifetime of buried pipeline system. To avoid the corrosion, antiseptic coating and electrochemistry method are usually used. But the antiseptic coating will lose its effects due to several factors, and cause the pipeline corrosion, even result in the pipeline leakage. According to the experience, most long distance oil or gas pipelines in our country have been gradually stepped into a period of high possibility of events. So it is necessary to carry on the work of repairing the antiseptic coating of pipelines in time. In order to provide the scientific basis of this work, it has great significance to research the method of measurement and evaluation to the defects of pipeline antiseptic coating, as well as evaluate the quality of the coating accurately and effectively. The technique of antiseptic coating detection has been studied intensively in this dissertation, and the main work accomplished can be summed up as the following aspects.1. There are many methods to detect the quality of the buried pipeline coating, and the advantages and disadvantages of these methods are studied intensively. Electrochemistry method which can detect faults of coating and peel them off at the same time is proposed.2. Equivalent circuit model corresponding to buried pipeline system is analyzed, which laid firm foundations of electrochemistry theory application to the detection of pipeline coating faults.3. A coating defect detection method which uses small amplitude lasting sine or step current is used, whose feasibility is testified during practical process.4. Faced with the fact that there is a great deal of noise in detecting signal when using small amplitude lasting sine current on field, a developed Lease Minimum Squares method is adopted, which makes the parameters of sine sequence with known frequency picked up on the real time. At the same time, original signal is processed by using wavelet theory, gaining true information which responses to the coating quality.5. In step current detection, intelligent pattern recognition capacity of artificial neural networks is utilized, then man-made factors are eliminated during judging the quality of pipeline coating, as well as avoiding numerous iterant calculations in curve imitation. Therefore, the speed of judging coating quality is accelerated greatly.6. Under the condition of cathodic protection, the distributing rules of electric field, electric potential and current density have relationships with the features of fault, such as figure and magnitude. After studying these relationships, finite element calculation model is established, which provides theoretical basis for instrument design.7. A set of detection instrument is developed to judge the type of the antiseptic coating defects on real field. Field detection over 20 kilometers is completed with this instrument, obtaining a great deal of detecting data.8. Discussing the synthetical evaluation problem to the safety of buried pipelines' run. On the base of fast detector developed by self and detection data of synthetical detector, synthetical evaluation system of antiseptic coating and pipe body is established, as well as erosion and defending database and evaluation system software are programmed. On the study of left erosion life of buried pipeline, a erosion forecasting method without excavation is proposed...
Keywords/Search Tags:buried pipeline, corrosion, coating, electrochemistry impedance spectrum, wavelet analysis, neural network, finite element method
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