Gas Pipeline Protection Deployment Using IoT Risk Mapping
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Solution Overview
Problem
Existing gas pipeline management systems lack proactive preventive measures during installation, relying on periodic inspections and post-failure repairs, which can reduce the service life and pose safety hazards due to external interferences like temperature variations, mechanical stress, vibration, freeze-thaw cycles, and biological corrosion.
Innovation Solution
A deployment method and system using a smart gas IoT platform that integrates environmental, biological, and facility information to determine risk values and deploy pipeline protection components based on actual conditions, adjusting deployment density and gas delivery pressure to mitigate risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If periodic inspections and post-failure repairs are used for pipeline management, then operational simplicity is maintained, but pipeline service life is reduced and safety hazards increase
Solution Approach 1:
The patent applies preliminary action by deploying protection components during pipeline installation based on pre-assessed risk factors (geological conditions, biological corrosion risks, vibration sources). This proactive approach identifies and protects vulnerable sections before failures occur, transitioning from reactive post-failure repairs to preventive protection, thereby extending pipeline service life while maintaining manageable operational complexity through automated risk assessment algorithms
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring pipeline conditions and protection component status, then adjusting maintenance schedules and protection strategies accordingly. Sensors detect changes in pipeline integrity, environmental conditions, and protection component effectiveness, feeding this data back to the management system to optimize future protection decisions, thus improving reliability while keeping operations systematic and controllable
2Ease of manufacture
If protection components are deployed uniformly across all pipeline sections, then installation simplicity is maintained, but resource waste occurs in low-risk areas
Solution Approach 1:
The patent applies local quality by varying the density and type of protection components deployed to different pipeline sections based on their specific risk profiles. High-risk areas (e.g., sections with poor soil conditions, high vibration exposure, or biological corrosion threats) receive denser protection component deployment, while low-risk areas receive minimal or no protection components. This targeted approach optimizes resource allocation, reducing protection component waste in low-risk areas while maintaining adequate protection where needed
Solution Approach 2:
The system changes the deployment parameters (density, type, spacing) of protection components based on risk assessment results. By adjusting these parameters according to local conditions rather than applying a uniform standard, the system achieves both cost efficiency and effective protection, balancing deployment simplicity with resource optimization through data-driven parameter selection
3Measurement precision
If risk assessment is performed using comprehensive environmental, biological, and facility data, then protection accuracy is improved, but system complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the risk assessment system into distinct functional modules: environmental data collection, biological condition monitoring, facility information gathering, and integrated analysis. Each module handles specific data types and processing tasks independently, then feeds results to the overall risk assessment algorithm. This modular approach improves measurement precision through specialized data collection while managing system complexity through clear separation of functions and standardized data interfaces
Data Source
AI summary
Disclosed are a deployment method and a deployment system for a pipeline protection component based on a smart gas IoT. The method includes: obtaining environmental information of a target region during a plurality of first preset time periods; obtaining biological information, climate information, and facility information of the target region; determining a vibration risk value of the target region; determining a target risk distribution of the target region; determining target protection component information of a target protection component deployed at each of a plurality of acquisition points in the target region; determining a deployment density distribution of the target protection components based on the target risk distribution and a pipeline deployment map of the target region; before and/or executing a protection component deployment operation, generating a valve control instruction to regulate a gas delivery pressure of at least one gas pipeline in the target region.