US 12,435,842 B2
Methods and systems for pipeline temperature control of smart gas based on internet of things (IOT)
Zehua Shao, Chengdu (CN); Yong Li, Chengdu (CN); Xiaojun Wei, Chengdu (CN); Guanghua Huang, Chengdu (CN); and Yunsong Gu, Chengdu (CN)
Assigned to CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD., Chengdu (CN)
Filed by CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD., Sichuan (CN)
Filed on Apr. 8, 2025, as Appl. No. 19/173,784.
Claims priority of application No. 202510230457.X (CN), filed on Feb. 28, 2025.
Prior Publication US 2025/0237360 A1, Jul. 24, 2025
Int. Cl. F17D 5/00 (2006.01); F17D 3/00 (2006.01); G05B 13/02 (2006.01); G05B 15/02 (2006.01)
CPC F17D 5/005 (2013.01) [F17D 3/00 (2013.01); G05B 13/0265 (2013.01); G05B 15/02 (2013.01)] 9 Claims
OG exemplary drawing
 
1. A method for pipeline temperature control of smart gas based on an Internet of Things (IoT), implemented based on a system for pipeline temperature control of smart gas based on an Internet of Things (IoT), comprising:
obtaining, based on a gas company management platform, pipeline information of a gas pipeline and basic perceptual data, obtaining at least one candidate parameter, and determining at least one transportation parameter based on at least one iterative interaction with a government safety supervision management platform; wherein the at least one candidate parameter includes at least one of a candidate gas transportation temperature and a candidate gas transportation rate of each of at least one transportation station; and
controlling, based on the at least one candidate parameter, a gas equipment object platform to adjust a gas transportation temperature; wherein
the at least one iterative interaction includes:
the gas company management platform determining, based on the at least one candidate parameter, the pipeline information, and environmental information, a temperature effect of the gas pipeline through a first model, and sending the temperature effect of the gas pipeline to the government safety supervision management platform; temperature effect of the gas pipeline reflecting a temperature change in the gas pipeline, the first model being a machine learning model; wherein
the gas pipeline includes a plurality of pipeline segments, the first model includes a plurality of temperature layers, each of the plurality of temperature layers corresponds to one of the plurality of pipeline segments, an input of each of the plurality of temperature layers includes inlet data of the corresponding pipeline segment, the pipeline information, and the environmental information, and an output of each of the plurality of temperature layers includes the temperature effect and outlet data of the corresponding pipeline segment; the inlet data includes at least one of an inlet temperature and an inlet rate, the inlet data of a first pipeline segment is the at least one candidate parameter; and the output data includes at least one of an outlet temperature and an outlet rate;
the government safety supervision management platform determining, based on the temperature effect of the gas pipeline, the at least one candidate parameter, the pipeline information, and the basic perceptual data, a deformation assessment of the gas pipeline;
obtaining at least one updated candidate parameter by updating, based on the deformation assessment of the gas pipeline, the at least one candidate parameter; and
in response to determining that the deformation assessment of the gas pipeline satisfies a preset deformation condition, determining the at least one updated candidate parameter as the at least one transportation parameter.