The Technology Research On Long Petroleum Pipeline Leakage And Localization Base On Network Control

The leakage accidents in pipelines transportation not only cause great loss of material, but also pollute the environment; what's more, it may lead to serious casualty. Leakage accidents in pipeline transportation occur frequently in recent years. In order to guarantee the pipelines work safely and minimize the losses caused by leakage accidents, it is necessary to study leakage detecting technology to raise the sensitivity of detection and accuracy of localization. Pipeline leakage detection is a multi-field object, which involved many subjects, such as pipeline hydrodynamics, thermodynamics, sensor technology, subtle signal detection and signal processing. This search on pipeline leakage detection and localization is carried out in this dissertation The main efforts accomplished can be summed up as the following aspects:1. Two crucial technologies in instantaneous negative pressure wave method are analyzed in this dissertation, then a means is presented which can eliminate the dynamic response time diversity between pressure sensors in the beginning and end of the pipeline, by adopting GPS to unify the system time between data collecting systems in two ends. Taking account of the corresponding characteristic of the signal singularity and wavelet transform module maximum in multi-scale changing, the discrete wavelet transform is applied to get the featured inflection point of negative pressure wave. Because data that scene gather contain a large number of noises, we use wavelet valve method denoise interferes, Have made the good result in practical application 2. "Energy -fault recognition", a fault diagnosis method based on wavelet packets analysis for the transport pipeline supervising system is proposed in this dissertation. Eigenvector target is presented which reflect the characteristic of leakage pressure signal. The signal is wavelet packets decomposed in this method. By analyzing the new sequences reconstructed on every decomposition note, the fault then can be recognized according to the eigenvectors in each frequency band.3. Use characteristic vector quantity of normal situation with leak characteristic vector quantity of situation compare, adopting valve method determinant the leakage of pipelines. The method that this text still adopts RBF neural network discerns the state of pipeline online, Can measure out the leakage of pipeline , the simulation result indicates that the result is better.4. Use network control theory, set up one petroleum pipeline leak network control system of leakage detection and localization, corresponding network control models and basic software and hardware had been put out.