Research On Reliability Data Collection And Analysis For The Equipment Of Oil And Gas Pipeline Station

Oil and gas pipeline station is a key link in oil and gas transportation, and a set of low reliability equipment which comes across a failure might cause all pipeline stop transportating and cost high maintenance fee. Because the domestic oil and gas pipelines yard equipment reliability data collection and analysis work is still in its infancy. In order to have a more clear understanding of the nature of the event for equipment failures, to execute equipment maintenance plans, and strengthen the effective management of equipment reliability data, to make reasonable assessment of equipment reliability, this topic mainly studies the content of the following aspects:(1) On the basis of GB/T 20172-2006, the oil and gas pipelines yard equipment data acquisition plan was studied, and a summary to the station equipment list had been carried on, and the equipment boundary had also been divided, and the equipment code and failure mode had also been designed, and the general and special data collection forms had been designed. The equipment data acquisition and data quality had been specificated, and finally a set of standardized data collection process was established. This research on oil and gas pipeline equipment data acquisition process made a beneficial attempt in order to establish China’s own pipeline industry equipment reliability database, which had certain guidance and reference value.(2) Preliminary equipment analysis had carried on the collected data. The theory of bayesian was used in fitting of the probabilities of failure modes for single equipment reliability. By using the second moment method, a single equipment reliability of the first and second approximate limit was estimated. Monte Carlo method was also used to solve complex system which was composed of several devices. And complex system structure or system data under the condition of the elusive problem of reliability assessment was solved. Would collect data and the corresponding analysis method together, had realized the single equipment and the reliability evaluation of the system which was composed of multiple devices.(3) For the purpose of getting the equipment reliability database appropriate for China petrochemical industry, a Bayesian method was proposed for calculating failure rate. Firstly, took an existing reliability database as prior information and reliability data from enterprises as sample information, then used Poisson distribution to simulate equipment failure processes and establish failure mode distribution functions. According to the above functions obtained, Gamma distribution was chosen as prior distribution to describe the mean failure rate for each failure mode. After that, the dynamic posterior distribution of failure rate on petrochemical equipment was exported through Bayesian method. With prior information and technological gap coefficient introduced to compensate the equipment differences, the prior distribution hyper-parameters were obtained. Meanwhile, there was equipment technological gap time between China and foreign counties, so fuzzy comprehensive method was used to estimate the time. Next was to calculate the time difference when prior information and sample information were got. So the ratio of equipment technical gap time and time difference was regarded as the technological gap coefficient. Finally, expectation of posterior distribution and the standard deviation were calculated, and the corresponding average failure rate of each failure mode and standard deviation estimations were gained under both cumulative calendar time and cumulative running time.(4) In Visual Basicenvironment, with basic data table, failure data table, data maintenance form and special data table designed as the system interface, and Microsoft Access 2007 was also combined in the research of station equipment reliability data management system. This research has a certain practical and innovative to some extent.