US 11,953,356 B2
Methods and internet of things (IoT) systems for monitoring smart gas pipeline networks based on ultrasonic flowmeters
Zehua Shao, Chengdu (CN); Bin Liu, Chengdu (CN); Lei Zhang, Chengdu (CN); and Yuefei Wu, Chengdu (CN)
Assigned to CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD., Chengdu (CN)
Filed by CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD., Sichuan (CN)
Filed on Jul. 23, 2023, as Appl. No. 18/357,148.
Claims priority of application No. 202310757123.9 (CN), filed on Jun. 26, 2023.
Prior Publication US 2023/0366710 A1, Nov. 16, 2023
Int. Cl. G06Q 10/063 (2023.01); G01F 1/66 (2022.01); G01F 1/667 (2022.01)
CPC G01F 1/667 (2013.01) 7 Claims
OG exemplary drawing
 
1. A method for monitoring a smart gas pipeline network based on an ultrasonic flowmeter implemented by a smart gas management platform of an Internet of things (IoT) system for monitoring a smart gas pipeline network based on an ultrasonic flowmeter, comprising:
acquiring distributed ultrasonic data for at least one moment, the distributed ultrasonic data including ultrasonic data acquired by the ultrasonic flowmeter and the ultrasonic flowmeter being deployed at at least one detection position of the gas pipeline network; the distributed ultrasonic data being ultrasonic data of different detection positions of the gas pipeline network;
determining a leakage risk of at least one preset point of the gas pipeline network based on the distributed ultrasonic data; and the leakage risk including a first leakage risk, and determining the first leakage risk including:
dividing, based on a preset sliding parameter, the distributed ultrasonic data for the at least one moment into at least one sliding interval set, and determining a gas feature sub-stability of each of the at least one sliding interval set, the preset sliding parameter being a parameter used to divide the distributed ultrasonic data for a plurality of moments into a plurality of groups of data, the sliding interval set being a set including a plurality of sliding intervals;
determining a gas feature stability based on the gas feature sub-stability of the each of the at least one sliding interval set, the gas feature sub-stability being used to reflect a stability of data of the sliding interval set, the gas feature stability being used to reflect a gas feature stability at the plurality of moments; and
determining the first leakage risk based on the gas feature stability, the first leakage risk being a risk and a risk probability related to a sudden leakage of gas; and
generating and sending warning information to a user based on the leakage risk.