Methods for smart gas pipeline cleaning management for safety management and internet of things systems thereof

Patent metadata

Field	Value
Publication number	US-11998962-B2
Application number	US-202318149157-A
Country	US
Kind code	B2
Filing date	Jan 3, 2023
Priority date	Nov 24, 2022
Publication date	Jun 4, 2024
Grant date	Jun 4, 2024

Abstract

The present disclosure provides a method of smart gas pipeline cleaning management for safety management and an Internet of Things system. The method comprises: obtaining operation feature of at least one gas pipeline and inspection data of the at least one gas pipeline; determining an area to be cleaned and an area feature of the area to be cleaned based on the operation feature of the at least one gas pipeline and the inspection data of the at least one gas pipeline; determining a pipeline cleaning solution based on the area feature of the area to be cleaned; evaluating a pipeline cleaning effect of the pipeline cleaning solution based on an implementation of the pipeline cleaning solution. The Internet of Things system comprises a smart gas user platform, a smart gas service platform, a smart gas sensing network platform, and a smart gas object platform.

First claim

What is claimed is:

1. A method of smart gas pipeline cleaning management for safety management, implemented based on a smart gas equipment management platform of an Internet of Things system of smart gas pipeline cleaning management for safety management, comprising:
obtaining operation feature of at least one gas pipeline and inspection data of the at least one gas pipeline;
determining an area to be cleaned and an area feature of the area to be cleaned based on the operation feature of the at least one gas pipeline and the inspection data of the at least one gas pipeline;
determining a pipeline cleaning solution based on the area feature of the area to be cleaned; and
evaluating a pipeline cleaning effect of the pipeline cleaning solution based on an implementation of the pipeline cleaning solution; wherein the determining a pipeline cleaning solution based on the area feature of the area to be cleaned includes:
determining at least one joint area and a joint area feature of each of the at least one joint area through merging one or more gas pipelines contained in the area to be cleaned based on a preset method; and
determining a target pipeline cleaning solution of the at least one joint area based on the joint area feature of the at least one joint area; wherein the determining a target pipeline cleaning solution of the at least one joint area based on the joint area feature of the at least one joint area includes:
generating at least one candidate pipeline cleaning solution based on the joint area feature of the at least one joint area;
determining a pipeline cleaning effect of each of the at least one candidate pipeline cleaning solution through processing each of the at least one candidate pipeline cleaning solution and the joint area feature of the joint area based on a pipeline cleaning effect prediction model; and
determining the target pipeline cleaning solution of the at least one joint area based on the pipeline cleaning effect of each of the at least one candidate pipeline cleaning solution; wherein
the pipeline cleaning effect prediction model includes a future feature prediction layer and a pipeline cleaning effect prediction layer, the future feature prediction layer and the pipeline cleaning effect prediction layer are obtained by joint training based on training samples and labels, wherein the training samples include a sample historical cleanliness sequence, a joint area feature of a sample joint area, and a sample pipeline cleaning solution, the joint area feature of the sample joint area includes a sample cleanliness at a current moment and a sample pipeline feature, and the sample pipeline cleaning solution includes sample pipeline cleaning time and other sample parameters, and the labels include a sample pipeline cleaning effect, the joint training including:
inputting the sample historical cleanliness sequence, the sample cleanliness at the current moment, and the sample pipeline feature, and the sample pipeline cleaning time into an initial future feature prediction layer and obtaining cleanliness at a future moment output from the initial future feature prediction layer;
inputting the cleanliness at the future moment and the other sample parameters into an initial pipeline cleaning effect prediction layer and obtaining the pipeline cleaning effect output from the initial pipeline cleaning effect prediction layer;
constructing a loss function based on the sample pipeline cleaning effect and the pipeline cleaning effect output from the initial pipeline cleaning effect prediction layer;
updating parameters of the initial future feature prediction layer and the initial pipeline cleaning effect prediction layer simultaneously; and
obtaining the future feature prediction layer and the pipeline cleaning effect prediction layer.

2. The method of claim 1 , wherein the determining an area to be cleaned and an area feature of the area to be cleaned based on the operation feature of the at least one gas pipeline and the inspection data of the at least one gas pipeline includes:
determining cleanliness of each of the at least one gas pipeline based on the operation feature of the at least one gas pipeline and the inspection data of the at least one gas pipeline;
determining the area to be cleaned based on the gas pipeline whose cleanliness meets a preset cleanliness condition; and
determining the area feature of the area to be cleaned based on the cleanliness of the gas pipeline corresponding to the area to be cleaned.

3. The method of claim 1 , wherein an input of the pipeline cleaning effect prediction model further includes a historical cleanliness sequence of the gas pipeline contained in the joint area, the historical cleanliness sequence is determined by a cleanliness determination model, and the pipeline cleaning effect prediction model and the cleanliness determination model are machine learning models.

4. The method of claim 1 , wherein the Internet of Things system of the smart gas pipeline cleaning management for safety management further comprises a smart gas user platform, a smart gas service platform, a smart gas sensing network platform, and a smart gas object platform;
the operation feature and the inspection data of the at least one gas pipeline are obtained based on the smart gas object platform; and transmitted to the smart gas equipment management platform based on the smart gas sensing network platform;
the method further comprises:
transmitting the pipeline cleaning solution and the pipeline cleaning effect to the smart gas user platform based on the smart gas service platform.

5. The method of claim 4 , wherein the smart gas user platform includes a gas user sub-platform, a government user sub-platform, and a supervision user sub-platform;
the smart gas service platform includes a smart gas service sub-platform, a smart operation service sub-platform, and a smart supervision service sub-platform;
the smart gas equipment management platform includes a smart gas indoor equipment management sub-platform, a smart gas pipeline network equipment management sub-platform, and a smart gas data center, wherein the smart gas pipeline network equipment management sub-platform includes an equipment ledger management module, an equipment maintenance record management module, and an equipment status management module;
the smart gas sensing network platform includes a smart gas indoor equipment sensing network sub-platform, and a smart gas pipeline network equipment sensing network sub-platform; and
the smart gas object platform includes a smart gas indoor equipment object sub-platform and a smart gas pipeline network equipment object sub-platform.

6. A non-transitory computer readable storage medium, wherein the storage medium stores computer instructions, when the computer instructions are executed by a processor, a method of smart gas pipeline cleaning management for safety management of claim 1 is implemented.

7. An Internet of Things system of smart gas pipeline cleaning management for safety management, comprising: a smart gas user platform, a smart gas service platform, a smart gas equipment management platform, a smart gas sensing network platform, and a smart gas object platform, wherein
the smart gas object platform is used to obtain operation feature of at least one gas pipeline and inspection data of the at least one gas pipeline;
the smart gas sensing network platform is used to transmit the operation feature of the at least one gas pipeline and the inspection data of the at least one gas pipeline to the smart gas equipment management platform;
the smart gas equipment management platform is used to:
determine an area to be cleaned and an area feature of the area to be cleaned based on the operation feature of the a

Assignees

• Chengdu Qinchuan Iot Tech Co Ltd

Inventors

• Shao Zehua
• Quan Yaqiang
• Liu Bin
• Wei Xiaojun
• Zhang Lei

Classifications

• B08B9/0551 Primary

  Control mechanisms therefor · CPC title

• B08B2209/053

  being moved along the pipes by a fluid, e.g. by fluid pressure or by suction · CPC title

• G06Q10/04 Primary

  Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202) · CPC title

• B08B9/0325 Primary

  Control mechanisms therefor · CPC title

• G06Q50/06

  Energy or water supply · CPC title