Pipeline full life cycle reliability quantitative analysis device based on big data

Abstract

The invention provides a pipeline full life cycle reliability quantitative analysis device based on big data. A pipeline is arranged in a simulation box; prefabricated weld joints, predetermined defects and a data acquisition dot matrix are arranged on the wall of the pipeline, the data acquisition dot matrix is connected with a data acquisition module, the data acquisition module is connected with a data processing module and a camera, and the pipeline is further connected with an operation control module. A balancing weight, a supporting part, a simulation block and a driving part are arranged outside the pipeline, and the driving part is connected with a driving source. The modular design is adopted, parts are replaced according to needs, and the universality and flexibility of the whole device are improved; the reliability research of the whole life cycle of pipeline service is realized; the visualization of each variable research is realized; establishing a pipeline macroscopic and microcosmic behavior relationship; the influence degree and rule of multiple factors on the pipeline reliability are quantitatively analyzed in a targeted and accurate mode, the system is fused with an intelligent pipeline system, a pipeline reliability data information base is established, and mining processing is conducted through the big data analysis technology.

Description

technical field [0001] The invention relates to the field of quantitative analysis devices, in particular to a large-data-based reliability quantitative analysis device for the whole life cycle of pipelines. Background technique [0002] On the one hand, the risk of the pipe network system comes from the flammability and explosiveness of its conveying medium. Once an accident occurs, the consequences are often catastrophic, not only causing economic losses, environmental pollution, but also possible casualties. On the other hand, most of the pipeline networks in my country are located in a complex geographical environment, and pipelines are prone to failure due to geological disasters such as collapse, gully and landslide. At the same time, the pipeline network is also affected by the management level. Without a systematic and systematic management mechanism for pipeline safety management, the risk of the pipeline network system will be seriously increased and the reliabilit...

AI Technical Summary

Problems solved by technology

[0007] (3) The analysis and simulation of the force of the soil on the pipeline (network) cannot be visually simulated, especially under special geological disasters, and the reuse of various components cannot be realized;

[0008] (4) It is impossible to realize the full life cycle research of the pipeline (network) system service process;

[0009] (5) The establishment of pipeline (network) macro and micro behavior relationship cannot be realized

[0010] To sum up, it is still difficult to evaluate the safety of pipelines (networks) quantitatively, efficiently, and accurately in the prior art, so that it can be more scientifically used to guide high steel grades, larger pipe diameters, and higher design coefficients Formulate and optimize pipeline design, production, construction, and operation plans to ensure the reliability level of pipelines (networks)

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