Smart Gas IoT Pipeline Cleaning Evaluation Method
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Gas pipelines often experience blockages due to hydrate formation from carbon dioxide and hydrogen sulfide, leading to reduced transmission efficiency and safety hazards, necessitating an effective method for evaluating pipeline cleaning solutions.
Innovation Solution
A method utilizing a smart gas equipment management platform within an Internet of Things system to evaluate pipeline cleaning solutions by obtaining operation and inspection data, determining areas to be cleaned, generating candidate solutions, predicting cleaning effects, and selecting optimal solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional pipeline cleaning methods are used, then cleaning operations can be performed, but the transmission efficiency cannot be effectively improved and pipeline resistance cannot be reduced
Solution Approach 1:
The system performs preliminary assessment of pipeline cleaning needs by analyzing operation data and inspection data before cleaning operations. It predicts future pipeline features and identifies areas requiring cleaning in advance, allowing proactive maintenance that prevents blockages and maintains transmission efficiency without unnecessary cleaning operations.
Solution Approach 2:
The system establishes a feedback mechanism that continuously monitors pipeline operation data, inspection data, and cleaning effects. It evaluates the effectiveness of cleaning operations and uses this feedback to optimize future cleaning decisions, thereby improving transmission efficiency and reducing pipeline resistance over time through data-driven adjustments.
2Measurement precision
If comprehensive pipeline inspection and evaluation systems are implemented, then cleaning effectiveness can be improved, but system complexity increases
Solution Approach 1:
The smart gas equipment management platform performs multiple functions including data collection, pipeline feature prediction, cleaning area identification, cleaning effect evaluation, and optimization recommendations. By consolidating these functions into a single multi-functional system, the patent achieves comprehensive measurement precision while avoiding the complexity of multiple separate systems.
Solution Approach 2:
The system automatically collects operation data and inspection data, predicts pipeline features, identifies cleaning areas, and evaluates cleaning effects without requiring extensive manual intervention. This self-service capability reduces operational complexity while maintaining high measurement precision through automated data processing and analysis.
Data Source
AI summary
The present disclosure provides a method for evaluating a pipeline cleaning solution based on smart gas and an Internet of Things system. The method comprises: obtaining an 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; generating at least one candidate pipeline cleaning solution based on the area feature of the area to be cleaned; processing each of the at least one candidate pipeline cleaning solution and the area feature through a pipeline cleaning effect prediction model to determine a pipeline cleaning effect of each of the at least one candidate pipeline cleaning solution; determining a pipeline cleaning solution based on the pipeline cleaning effect; and evaluating a pipeline cleaning effect of the pipeline cleaning solution based on an implementation of the pipeline cleaning solution.