IP Library Granted Patent US 12,209,712
Granted Patent B2
US 12,209,712 · App. 18/644,085 · Granted Jan 28, 2025

Methods and systems for safety management of gas pipe wells based on smart gas internet of things

Inventors: Zehua Shao (Chengdu, CN); Yong Li (Chengdu, CN); Yuefei Wu (Chengdu, CN); Lei Zhang (Chengdu, CN); Xiaojun Wei (Chengdu, CN)
Assignee: CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD.
F17D5/005G06N20/00G06Q50/06
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,209,712
App. No.
18/644,085
Granted
Jan 28, 2025
Kind
B2
Abstract

Disclosed is a method and a system for safety management of a gas pipe well based on a smart gas IoT. The method may be executed by a processor and include: obtaining an environmental information sequence of the gas pipe well and an in-well monitoring data sequence by controlling a monitoring component according to a monitoring parameter based on the smart gas IoT, and storing the environmental information sequence and the in-well monitoring data sequence in a storage unit; determining an in-well risk value; adjusting the monitoring parameter in response to determining that the in-well risk value exceeds a risk threshold and updating the in-well risk value; determining an impact degree of a gas component; determining a pipe well inspection program and generating a corresponding pipe well inspection instruction to be sent to an inspection terminal; and adjusting the monitoring parameter and clearing expired data in the storage unit.

Claims (45)

1. A method for safety management of a gas pipe well based on a smart gas Internet of Things (IoT), wherein the method is executed by a processor, and the method comprises:

obtaining an environmental information sequence of the gas pipe well and an in-well monitoring data sequence by controlling a monitoring component according to a monitoring parameter based on the smart gas IoT, and storing the environmental information sequence of the gas pipe well and the in-well monitoring data sequence in a storage unit;

determining an in-well risk value based on the environmental information sequence and the in-well monitoring data sequence, wherein the in-well risk value includes a well-wall immersion risk value and a well-wall corrosion risk value, and the in-well risk value is determined by:

determining consistency of changes between an environment inside the gas pipe well and an environment outside the gas pipe well based on the environmental information sequence and the in-well monitoring data sequence;

determining a performance integrity degree of the gas pipe well based on the consistency of changes; and

determining the in-well risk value through a risk assessment model based on the performance integrity degree, a pipe well location characteristic, the environmental information sequence, and the in-well monitoring data sequence, the risk assessment model being a machine learning model, wherein the risk assessment model includes an immersion layer and a corrosion layer, the immersion layer is configured to process the performance integrity degree, the pipe well location characteristic, and the environmental information sequence to obtain the well-wall immersion risk value, and the corrosion layer is configured to process the well-wall immersion risk value and the in-well monitoring data to obtain the well-wall corrosion risk value;

adjusting the monitoring parameter in response to determining that the in-well risk value exceeds a risk threshold and updating the in-well risk value based on the adjusted monitoring parameter;

determining an impact degree of a gas component based on the updated in-well risk value;

determining a pipe well inspection program based on the impact degree of the gas component and generating a corresponding pipe well inspection instruction to be sent to an inspection terminal; and

adjusting the monitoring parameter and clearing expired data in the storage unit based on an inspection result on the pipe well inspection instruction by an inspector.

2. The method according to claim 1 , wherein the determining consistency of changes between an environment inside the gas pipe well and an environment outside the gas pipe well based on the environmental information sequence and the in-well monitoring data sequence includes:

segmenting the environmental information sequence to obtain a plurality of environmental information sub-sequences based on a characteristic of changes of the environment outside the gas pipe well in the environmental information sequence;

determining, based on the plurality of environmental information sub-sequence and the in-well monitoring data sequence, a plurality of in-well monitoring data sub-sequences corresponding to the plurality of environmental information sub-sequences, respectively; and

determining the consistency of changes based on a matching degree between the plurality of environmental data sub-sequences and the plurality of in-well monitoring data sub-sequences.

3. The method of claim 1 , wherein the method further comprises:

determining a well-cover integrity degree based on a sequence of light data in the gas pipe well; and

determining the performance integrity degree based on the well-cover integrity degree.

4. The method of claim 1 , wherein the determining an impact degree of a gas component based on the updated in-well risk value includes:

determining weatherability of the gas component based on a historical inspection record of the gas component, historical operational data, gas component information, and a historical in-well risk value of the gas pipe well; and

determining the impact degree of the gas component based on the weatherability of the gas component and the updated in-well risk value.

5. The method of claim 4 , wherein the determining weatherability of the gas component based on a historical inspection record of the gas component, historical operational data, gas component information, and a historical in-well risk value of the gas pipe well includes:

determining the weatherability of the gas component using a weatherability model based on the historical inspection record, the historical operating data, the gas component information, and the historical in-well risk value, the weatherability model being a machine learning model.

6. The method of claim 1 , wherein the determining a pipe well inspection program based on the impact degree of the gas component includes:

determining a pipe well inspection priority based on the impact degree of the gas component; and

determining the pipe well inspection program based on the pipe well inspection priority.

7. A system for safety management of a gas pipe well based on a smart gas Internet of Things (IoT), wherein the system comprises a smart gas user platform, a smart gas service platform, a smart gas device management platform, a smart gas sensing network platform, and a smart gas object platform, wherein the smart gas device management platform is configured to:

obtain an environmental information sequence of a gas pipe well and an in-well monitoring data sequence by controlling a monitoring component according to a monitoring parameter based on the smart gas IoT, and store the environmental information sequence of the gas pipe well and the in-well monitoring data sequence in a storage unit;

determine an in-well risk value based on the environmental information sequence and the in-well monitoring data sequence, wherein the in-well risk value includes a well-wall immersion risk value and a well-wall corrosion risk value, and to determine the in-well risk value, the smart gas device management platform is further configured to:

determine consistency of changes between an environment inside the gas pipe well and an environment outside the gas pipe well based on the environmental information sequence and the in-well monitoring data sequence;

determine a performance integrity degree of the gas pipe well based on the consistency of changes; and

determine the in-well risk value through a risk assessment model based on the performance integrity degree, a pipe well location characteristic, the environmental information sequence, and the in-well monitoring data sequence, the risk assessment model being a machine learning model, wherein the risk assessment model includes an immersion layer and a corrosion layer, the immersion layer is configured to process the performance integrity degree, the pipe well location characteristic, and the environmental information sequence to obtain the well-wall immersion risk value, and the corrosion layer is configured to process the well-wall immersion risk value and the in-well monitoring data to obtain the well-wall corrosion risk value;

adjust the monitoring parameter in response to determining that the in-well risk value exceeds a risk threshold and update the in-well risk value based on the adjusted monitoring parameter;

determine an impact degree of a gas component based on the updated in-well risk value;

determine a pipe well inspection program based on the impact degree of the gas component and generate a corresponding pipe well inspection instruction to be sent to an inspection terminal; and

adjust the monitoring parameter and clear expired data in the storage unit based on an inspection result of the pipe well inspection instruction by an inspector.

8. The system of claim 7 , wherein the smart gas device management platform is configured to:

segment the environmental information sequence to obtain a plurality of environmental information sub-sequences based on a characteristic of changes of the environment outside the gas pipe well in the environmental information sequence;

determine, based on the plurality of environmental information sub-sequence and the in-well monitoring data sequence, a plurality of in-well monitoring data sub-sequences corresponding to the plurality of environmental information sub-sequences, respectively; and

determine the consistency of changes based on a matching degree between the plurality of environmental data sub-sequences and the plurality of in-well monitoring data sub-sequences.

9. The system of claim 7 , wherein the smart gas device management platform is configured to:

determine a well-cover integrity degree based on a sequence of light data in the gas pipe well; and

determine the performance integrity degree based on the well-cover integrity degree.

10. The system of claim 7 , wherein the smart gas device management platform is configured to:

determine weatherability of the gas component based on a historical inspection record of the gas component, historical operational data, gas component information, and a historical in-well risk value of the gas pipe well; and

determine the impact degree of the gas component based on the weatherability of the gas component and the updated in-well risk value.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 14, 2024
From: SHAO, ZEHUA; LI, YONG; WU, YUEFEI; ZHANG, LEI; WEI, XIAOJUN
To: CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD.
Reel/Frame 068589/0013 →
Priority Claims (1)
CN 202410369960.9 · Mar 29, 2024 · national
Continuity (1)
Related Publication 20240271762A1 · Aug 15, 2024
References Cited (26)
US 11879599B2 · Shao · 2024 [cited by examiner]
US 11898895B2 · Shao · 2024 [cited by examiner]
US 11966885B2 · Shao · 2024 [cited by examiner]
US 11982409B2 · Shao · 2024 [cited by examiner]
US 11982613B2 · Shao · 2024 [cited by examiner]
US 12045837B2 · Shao · 2024 [cited by examiner]
US 20080127654A1 · Darling et al. · 2008 [cited by applicant]
US 20230143654A1 · Shao et al. · 2023 [cited by applicant]
US 20230160540A1 · Shao et al. · 2023 [cited by applicant]
CN 115899595A · 2023 [cited by applicant]
CN 218845772U · 2023 [cited by applicant]
CN 116308965A · 2023 [cited by applicant]
CN 116485066A · 2023 [cited by applicant]
CN 116506470A · 2023 [cited by applicant]
CN 116629580A · 2023 [cited by applicant]
CN 116645041A · 2023 [cited by applicant]
CN 117495356A · 2024 [cited by applicant]
JP H09243070A · 1997 [cited by applicant]
First Office Action in Chinese Application No. 202410369960.9 mailed on May 8, 2024, 17 pages. [cited by applicant]
Notification to Grant Patent Right for Invention in Chinese Application No. 202410369960.9 mailed on May 24, 2024, 4 pages. [cited by applicant]
First Office Action in Chinese Application No. 202410369960.9 mailed on May 8, 2024, 19 pages. [cited by applicant]
Zeng, Rui, Practice of Risk Assessment of Buried Steel Gas Pipeline, GAS & HEAT, 40(4): A39-A42, B44, 2020. [cited by applicant]
Li, Minghao et al., Risk Assessment of Buried PE Pipes for Gas, Petroleum and chemical equipment, 2017, 6 pages. [cited by applicant]
Shao, Zehua, Research on Smart Gas Meter Sensor Network Platform, GAS & HEAT, 38(5): B33-B37, 2018. [cited by applicant]
Gu, Xun'Ao, Risk analysis of urban gas pipeline and optimization of inspection strategy, CNKI, 2021, 8 pages. [cited by applicant]
Zhao, Fei et al., Gas Turbine Exhaust System Health Management Based on Recurrent Neural Networks, 11th CIRP Conference on Industrial Product-Service Systems, 83: 630-635, 2019. [cited by applicant]
Cited By (1)
US 12,692,990