Explosion Prediction with Data-Constructed Gas and Flame Images
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Solution Overview
Problem
Current methods for predicting explosions in environments are inaccurate due to the presence of physical blockages and the inability to capture representative images, leading to unreliable explosion predictions.
Innovation Solution
A computer-implemented method utilizing gas and flame sensor data to construct a data-constructed image, processed by a prediction model to determine explosion likelihood, which includes assigning different channels for gas and flame data and applying a computer vision model to identify explosion contribution levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If physical blockages are present in the environment, then image-based explosion prediction methods can be implemented, but the prediction accuracy deteriorates due to inability to capture representative images
Solution Approach 1:
The patent introduces data-constructed images as an intermediary representation that translates sensor data (gas concentrations, flame detection) into visual formats. This mediator allows explosion prediction models to process environmental data without requiring direct optical image capture, thereby bypassing the blockage problem while maintaining prediction reliability
Solution Approach 2:
The patent replaces the mechanical/optical image capture system with a data-based construction system. Instead of using cameras to physically capture images of the environment, the system constructs images from sensor readings, substituting the optical measurement mechanism with a data processing mechanism that is not affected by physical blockages
2Measurement precision
If multiple sensor types are integrated to improve prediction accuracy, then explosion prediction accuracy improves, but device complexity increases
Solution Approach 1:
The patent creates a universal data construction framework that can process multiple sensor types (gas sensors, flame sensors, and potentially other sensors) through a common pipeline. The data-constructed image approach serves as a universal interface that translates diverse sensor data into a standardized format, allowing the system to handle multiple sensor types without proportionally increasing complexity
Solution Approach 2:
The patent merges data from multiple sensor types into a single integrated representation (the data-constructed image). By combining gas concentration data, flame detection data, and other sensor readings into one unified structure, the system processes multiple information sources through a single prediction model, reducing the complexity that would arise from handling each sensor type separately
Data Source
AI summary
Embodiments utilize captured data, such as gas data and/or flame/heat data, from sensors in an environment to generate a data-constructed image for use in predicting explosion likelihood within an environment. Some embodiments utilize gas and flame data to generate the data-constructed image that is processable via one or more model(s) to determine whether the environment includes one or more sub-regions at risk of explosion. Some embodiments receive a plurality of gas sensor data and a plurality of flame sensor data, generate a data-constructed image including a plurality of channels based at least in part on such data, and generate explosion prediction data by applying at least a portion of the data-constructed image to a prediction model.