IoT Pipeline Drying Control via Dynamic Parameter Adjustment
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Solution Overview
Problem
Existing gas pipeline cleaning devices are complex and inefficient, failing to effectively dry the interior of gas pipelines, leading to incomplete drying and quality issues with natural gas.
Innovation Solution
A method and IoT system for pipeline drying treatment based on smart gas safety supervision, which uses a gas company management platform to determine initial drying values, adjust progressive drying parameters, and evaluate drying effectiveness through detection data, ultimately improving drying efficiency and quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If traditional gas pipeline cleaning devices are used, then cleaning operation can be performed, but the device structure is complicated and drying efficiency is low
Solution Approach 1:
The system segments the drying process into multiple stages: initial drying value determination, progressive drying parameter adjustment, and confidence level evaluation. This segmentation allows each stage to be optimized independently, improving overall drying efficiency while maintaining operational simplicity.
Solution Approach 2:
The drying parameters are made dynamic and adjustable based on real-time detection data. The system continuously monitors drying progress and adjusts parameters such as drying medium flow rate, temperature, and pressure dynamically, rather than using fixed parameters, thereby significantly improving drying efficiency.
2Manufacturing precision
If traditional cleaning methods are used, then basic cleaning can be achieved, but water accumulates in low regions and gaseous residual water on pipeline walls is difficult to remove
Solution Approach 1:
The system implements a closed-loop feedback mechanism where detection data from sensors monitoring pipeline humidity and water accumulation is continuously fed back to the control platform. Based on this feedback, the system automatically adjusts drying parameters to eliminate residual water in low regions and on pipeline walls, achieving high drying quality without requiring complex manual intervention.
Solution Approach 2:
The system replaces traditional mechanical drying methods with a smart control system that uses detection data and automated parameter adjustment. This substitution of mechanical operations with intelligent control achieves superior drying quality while keeping the overall system architecture relatively simple.
3Reliability
If no drying evaluation is performed, then the process is simple, but the drying effect cannot be evaluated and natural gas quality is affected
Solution Approach 1:
The system performs self-evaluation of drying effectiveness through automated detection and confidence level calculation. The control platform automatically assesses whether drying targets are met based on detection data, eliminating the need for complex external evaluation systems while ensuring natural gas quality requirements are satisfied.
Data Source
AI summary
Disclosed is a method and an Internet of Things (IoT) system for pipeline drying treatment based on smart gas safety supervision. The IoT system comprises a gas company management platform, a government gas supervision management platform, a gas company object platform, etc. The method comprises obtaining drying medium information of at least one gas pipeline outlet; determining an initial drying value of at least one gas pipeline; in response to the initial drying value being less than a drying threshold, using the at least one gas pipeline as a target gas pipeline, and determining a progressive drying parameter; generating a first control instruction to be sent to the gas company object platform; evaluating a confidence level of the initial drying value; generating a threshold adjustment instruction, and sending the threshold adjustment instruction to the gas company management platform to update the drying threshold; and generating a performance adjustment instruction.