AI Control Platform for Stable MSWI Optimization and Safety Isolation
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Solution Overview
Problem
Municipal solid waste incineration (MSWI) plants face challenges in maintaining stable optimization conditions due to the variability of expert experience, leading to instability and inefficiency, and the lack of effective AI integration for safety collaboration across cloud, edge, and end sides, which affects industrial control safety and environmental compliance.
Innovation Solution
An AI evaluation platform integrating a synchronous publishing system, AI-driven modeling system, AI control system for multiple-input multiple-output loops, AI control system for edge-side safety isolation, and AI optimization system for cloud-side safety isolation, enabling closed-loop operations and multi-layer security isolation for data transmission, and supporting intelligent control and optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual control by domain experts is used, then operational flexibility and experience-based adjustments are maintained, but stability and consistency of the incineration process deteriorate due to randomness and variability in expert experience
Solution Approach 1:
The patent creates a digital twin of the physical incineration system that copies and simulates the complex thermal, chemical, and mechanical processes. This digital model enables consistent reproduction of optimal operating conditions without relying on variable human expertise, thereby maintaining operational flexibility while improving process stability through automated control based on the digital twin simulations.
Solution Approach 2:
The patent replaces manual mechanical control operations with an automated control system that uses machine learning models and digital twin simulations. The system substitutes human expert judgment with algorithmic decision-making, eliminating the randomness and variability inherent in manual operations while maintaining the ability to adapt to changing conditions through automated adjustments.
2Reliability
If AI technology is integrated for intelligent control, then process stability and optimization are improved, but industrial control safety and data security deteriorate due to potential vulnerabilities in AI systems
Solution Approach 1:
The patent introduces a safety isolation mechanism that acts as an intermediary layer between the AI control system and the industrial control network. This intermediary layer includes safety validation modules that verify AI-generated control commands before execution, and isolation firewalls that prevent direct network access to critical control systems, thereby enabling AI integration while mitigating security risks.
Solution Approach 2:
The patent implements preemptive security measures including AI model validation, control command verification, and network isolation protocols before AI technology is deployed in the industrial control system. These beforehand cushioning measures prepare the system to handle potential AI vulnerabilities by establishing safety boundaries and validation procedures in advance.
3Reliability
If continuous monitoring and adjustment by domain experts is implemented, then response to unexpected situations improves, but operational costs and time consumption increase due to the need for uninterrupted expert attention
Solution Approach 1:
The patent enables the incineration system to monitor and adjust its own operation through the digital twin and automated control system. The system continuously monitors process parameters, detects anomalies, and makes real-time adjustments without requiring continuous human intervention. This self-service capability maintains high response capability to unexpected situations while eliminating the time consumption associated with continuous expert monitoring.
Solution Approach 2:
The patent implements a closed-loop feedback system where process data is continuously collected, analyzed by the digital twin model, and used to automatically adjust control parameters. The feedback mechanism enables the system to respond to unexpected situations in real-time by detecting deviations from optimal operation and automatically correcting them, replacing the need for continuous human monitoring with an automated feedback-driven control loop.
4Productivity
If AI-driven closed-loop operations are implemented, then operational efficiency and cost reduction are achieved, but system complexity and difficulty of implementation increase
Solution Approach 1:
The patent divides the complex AI control system into modular components including the digital twin model, data collection modules, analysis engines, and control execution interfaces. Each module performs a specific function and can be independently developed, tested, and deployed. This segmentation reduces implementation complexity by breaking down the overall system into manageable units while maintaining the high operational efficiency of the integrated AI-driven closed-loop operations.
Data Source
AI summary
Provided is an artificial intelligence (AI) evaluation platform for municipal solid waste incineration (MSWI). The AI evaluation platform for municipal solid waste incineration includes: An AI-driven modeling system of multimodal data is connected to an AI optimization system for cloud-side safety isolation and a synchronous publishing system of multimodal historical data, the synchronous publishing system of multimodal historical data is connected to an AI control system for edge-side safety isolation, and the AI control system for edge-side safety isolation is connected to an AI control system of an end-side multiple-input multiple-output loop and the AI optimization system for cloud-side safety isolation. This application resolves, in conventional technologies, a problem that “AI+MSWI” digital industry clusters cannot implement safety collaboration on a cloud side, an edge side, and an end side, and a problem that MSWI plants are difficult to maintain stable optimization conditions for a long period of time.