Predictive Safety Detection for Spinning Workshop Risk Areas
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Solution Overview
Problem
The spinning process in the textile industry poses significant safety hazards due to complex procedures and specialized environments, threatening production safety and hindering the industry's healthy, stable, and sustainable development.
Innovation Solution
A method and apparatus for safety detection that involves obtaining actual and predicted environmental parameters, expanding detection areas based on area positions, and generating safety pre-warning information using a trained time sequence model to accurately identify risk areas and broadcast warnings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If detection areas are expanded to cover the entire production workshop, then safety coverage is improved, but system complexity and computational burden increase
Solution Approach 1:
The production workshop is divided into multiple detection areas, each with its own detection device. This segmentation allows comprehensive coverage of the entire workshop while maintaining manageable system complexity through modular architecture. Each detection area operates semi-independently, detecting local environmental parameters and risks.
Solution Approach 2:
The system transitions from detecting only current environmental parameters to predicting future environmental parameters at multiple time points. This temporal dimension expansion allows the system to identify potential risks before they materialize, improving safety coverage without proportionally increasing system complexity through predictive modeling.
2Measurement precision
If real-time environmental parameters are monitored across all areas, then risk detection accuracy is improved, but data processing time and computational resources increase
Solution Approach 1:
The system performs preliminary prediction of future environmental parameters based on current detection data. By predicting trends before risks fully develop, the system achieves high detection accuracy while reducing the need for continuous real-time analysis of all parameters across all areas, thus decreasing data processing time.
Solution Approach 2:
A centralized management platform acts as an intermediary between distributed detection devices and decision-making systems. This platform aggregates data, performs predictive analysis, and generates risk warnings, reducing the computational burden on individual detection devices and optimizing overall data processing efficiency.
3Reliability
If multiple detection areas are monitored simultaneously, then safety coverage is improved, but the cost of detection equipment and maintenance increases
Solution Approach 1:
Detection devices are designed with multi-functional capabilities, able to measure multiple environmental parameters (temperature, humidity, gas concentration, etc.) simultaneously. This universality reduces the total number of specialized devices needed while maintaining comprehensive safety coverage across all detection areas.
Solution Approach 2:
The system incorporates automatic warning generation and notification functions that operate autonomously based on detected parameters. This self-service capability reduces the need for additional monitoring equipment and manual intervention, lowering overall system costs while maintaining extensive safety coverage.
Data Source
AI summary
A method for safety detection, an electronic device, and a storage medium are provided, relating to the field of computer technologies. The method includes: obtaining an actual environmental parameter of each of multiple first detection areas in a first time period; obtaining a first environmental parameter prediction result of each first detection area in a second time period based on the actual environmental parameter; obtaining multiple second detection areas based on an area position of each first detection area in the production workshop; obtaining a second environmental parameter prediction result of each second detection area in the second time period based on the first environmental parameter prediction result; and generating safety pre-warning information corresponding to a risk area when determining that the risk area is present in the multiple second detection areas based on the second environmental parameter prediction result.