IoT Welding Risk Monitoring for Smart Gas Pipelines
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Solution Overview
Problem
Existing methods for monitoring gas pipeline welding do not adequately account for the influence of environmental factors, leading to variability in welding quality and efficiency.
Innovation Solution
An IoT system for monitoring welding of smart gas pipelines that integrates a smart gas government safety supervision platform, sensing network, and construction object platform to assess welding risks, generate adjustment instructions, and issue early warnings based on environmental and construction data, ensuring timely maintenance and quality control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional welding monitoring methods are used, then the monitoring process is simple, but the welding quality is affected by environmental factors leading to variability
Solution Approach 1:
The monitoring system is divided into multiple independent modules: environmental factor monitoring module, welding process monitoring module, risk assessment module, and early warning module. Each module independently collects and processes specific types of data, allowing the system to handle complex monitoring tasks through modular components rather than a monolithic complex system.
Solution Approach 2:
A risk assessment module serves as an intermediary between environmental/welding data collection and quality control decisions. This intermediary layer processes raw data from multiple sources, assesses risks, and generates appropriate warnings or adjustments, thereby mediating the complexity between data collection and quality assurance functions.
2Manufacturing precision
If comprehensive environmental factor monitoring is implemented, then welding quality improves, but data processing complexity increases
Solution Approach 1:
The system monitors different environmental factors with different levels of detail depending on their specific impact on welding quality. Critical factors like temperature and humidity receive focused monitoring and processing, while less critical factors are monitored at lower detail levels, allowing comprehensive coverage without uniformly high processing complexity across all factors.
Solution Approach 2:
The system performs preliminary data processing and risk assessment before final quality determination. Environmental and welding data are collected, pre-processed, and assessed for risks in advance, allowing the actual quality control process to focus on actionable insights rather than raw data processing complexity.
3Reliability
If real-time risk assessment is performed, then welding safety improves, but computational resources are consumed
Solution Approach 1:
The risk assessment is performed periodically at key welding stages rather than continuously at maximum computational intensity. The system assesses risks at environmental factor threshold crossings, at defined welding process milestones, and when early warning signals are detected, allowing real-time safety monitoring with reduced peak computational resource consumption compared to continuous high-intensity processing.
Data Source
AI summary
Embodiments of the present disclosure provide a method and an Internet of Things (IoT) system for monitoring welding of a smart gas pipeline based on government supervision, the system comprising a smart gas government safety supervision platform, a smart gas government safety supervision sensing network platform, a smart gas government safety supervision object platform, a gas company sensing network platform, and a gas construction object platform. The method is performed based on the gas company management platform, comprising: obtaining at least one set of welding point information and corresponding pipeline construction information in a preset pipeline region; determining a first welding risk based on the pipeline construction information; and determining a first risk value based on the first welding risk and a historical welding risk; in response to determining that the first risk value meets a preset condition, generating a welding adjustment instruction; obtaining welding process information uploaded by a welding personnel terminal; performing a preset processing on the welding process information to obtain welding key information; obtaining monitoring parameters of the preset pipeline region.