Study On The Online Product Oil Detection System Based On Inductor Model Of Electron Cloud

At present, our country's product oil market is developing rapidly. The increasing need of product oil demands more highly level of product oil transportation. Pipeline transportation of product oil is more convenient, faster, more economical, more environment-friendly and safer, among transportation industries. So far, product oil pipelines of the world are 430,000 kilometers long in total, while product oil pipelines of our country have been more than 12,000 kilometers long. The economization superiority of the product oil transportation technology is mainly embodied in sequential product oil transportation. 47% of the whole product oil transportation is pipeline transportation in overseas, while our country's product oil transportation is dependent on railways in a long time, and percentage of pipeline transportation in product oil is just 4%. The principal reason lies in our country's undeveloped technology of pipeline transportation of product oil, therefore our country can't flexibly transport product oil in multi-batch and multi-type way, which restricts the economization superiority in product oil pipeline transportation.The main technology of pipeline transportation of product oil is as follows: Leakage Detection, Oil Mixture Concentration Detection, Oil Mixture Area Track, Oil Mixture Area Cutting Automation Control. Oil Mixture Concentration Detection affects positioning accuracy of Leakage Detection and the result of Oil Mixture Area Track and Oil Mixture Area Cutting. Furthermore Oil Mixture Concentration Detection is the key to our country's technology development of product oil pipeline transportation.Based on the previous team work, this dissertation involves the in-depth study on the Detection Technology of Pipeline Product Oil and the IMEC (Inductor Model of Electron Cloud). This dissertation also constructs the IMEC of product oil and proposes a method based on the IMEC of product oil to calculate the oil mixture concentration and designs experiment to test and verify the IMEC of product oil and the method of calculating the oil mixture concentration and sets up an Online Detection System of Product Oil based on IMEC of product oil. It has been proved theoretically that this system can detect not only the product oil medium in the pipeline but also the oil mixture's concentration in the pipeline, and can track the oil mixture field. The major study of this dissertation covers the following aspects:1. It involves the in-depth study on the construction of the IMEC and its properties and influencing factors and proposes and constructs the IMEC of product oil and analyzes the influences induced by the equivalent volume, shape and relative location to the light waves of IMEC of product oil with the changes of electron cloud space in product oil relative to a single electron into consideration;2. It proposes a method to simulate the Refraction Power of the Inductor of Electron Cloud and through the software ANSYS, analyzes changes of the value of refraction power and the distribution of refraction power in IMEC induced by the changes of the IMEC's coil's turns, IMEC's coil's size, IMEC's volume, IMEC's shape and IMEC's relative location to magnetic field of light waves;3. It proposes a method to calculate the oil mixture concentration based on the IMEC of product oil, which can calculate the oil mixture concentration with the clearness of the relation between the IMEC of the two types of pure product oil comprising the oil mixture, the proportion of the two pure product oil in oil mixture and the IMEC of oil mixture and has tested and verified the method;4. It designs and produces a set of experiment device and tests and verifies the correctness of the Inductor Model of Electron Model of product oil and the feasibility of the Oil Mixture Concentration Detection based on the IMEC of product oil;5. It designs a set of detection system of the product oil based on the IMEC of product oil, and elaborates on the working principle of the system and the detecting principle of oil mixture, and proves theoretically that this system can monitor the oil mixture concentration through the online test of the product oil in sampling sites and can track the oil mixture area at all the times according to the location of every sampling site and changes of the oil mixture concentration.