Siphon drainage monitoring system and method based on large data

Abstract

The invention discloses a siphon drainage monitoring system and method based on large data. The siphon drainage monitoring system comprises a siphon drainage system and a drainage monitoring system, wherein the drainage monitoring system is used for monitoring drainage condition in a pipeline in the siphon drainage system. The siphon drainage system comprises a macromolecule protection drainage special-shaped sheet, a drainage groove, a pipeline, an observation well and a water collection well; the drainage monitoring system comprises a large data processing center, a drainage monitoring subsystem, an alarm subsystem, a large data storage unit and a drainage network monitoring platform. According to the siphon drainage monitoring system and method based on large data, the siphon system does not need slope finding or waterproof treatment; the original passive drainage is changed into active drainage by adopting siphon principle, and incomplete drainage, water leakage, vegetation damageof the existing drainage structure are thereby avoided; the drainage condition in the pipeline can be monitored in real time through a large data system; and unified supervision and real-time maintenance are facilitated.

Description

technical field [0001] The invention relates to the technical field of a data monitoring system and a monitoring method, in particular to a big data-based siphon drainage monitoring system and a monitoring method. Background technique [0002] In the prior art, in the greening and drainage systems of three-dimensional garages or other house structures, drainage boards and waterproof structures are the most commonly used. Drainage boards are generally used for planting roofs. The existing drainage boards form solid or cup-shaped protrusions on the polymer sheet. The mouth of the cup-shaped protrusions is in the opposite direction of the protrusions. The protrusions are generally upward. The space in between constitutes the drainage channel. When the protrusions are down, holes are punched between the protrusions, and water passes through the holes and flows away from the spaces between the protrusions. The drainage system using drainage boards in the current technology is s...

AI Technical Summary

Problems solved by technology

The drainage system using drainage boards in the current technology is simply to lay several drainage boards on the roof, and then cover a layer of filter cloth on it, and then cover the greening soil on the filter cloth, so that the sewage that seeps down can only be drained from the roof. The side row, and the drainage effect is not good, it is more likely to cause moisture seepage on the roof and affect the structure of the house

[0003] The traditional roof planting node waterproof structure of underground buildings generally includes building roof, slope layer, leveling layer, waterproof layer, isolation layer, fine stone concrete protection layer, storage and drainage layer, filter layer and planting soil, which greatly increases the operating cost And increase the construction period, and even if such a waterproof structure is adopted, the building structure will leak after a long time, which has brought a lot of troubles to developers and users

[0004] At the same time, with the rapid development of urban construction, the siphon drainage system has become more and more complex and large. The traditional management method has been developed to meet the needs of the modernization of the urban pipe network. Since the siphon drainage pipe network facilities are underground, so It is impossible to conduct surveys through conventional ground inspections, and the number of various pipe networks is huge. Maintenance operations may cause damage to other pipelines and affect the environment. Due to the wide distribution of drainage pipe network monitoring points and the large amount of collected data, The monitoring effect is poor. Therefore, we propose a siphon drainage monitoring system and monitoring method based on big data

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