Real-Time Damage Prediction Model for Industrial Equipment
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Solution Overview
Problem
Industrial processes often cause equipment damage due to wear and tear, which is typically monitored through periodic offline inspections, providing no real-time insight into damage levels or causes, disrupting operations and leading to potential failures.
Innovation Solution
A method and system for real-time damage prediction using a damage prediction model based on process parameters, which obtains real-time state information to determine and quantify damage to equipment components, allowing for immediate adjustments to reduce damage rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If periodic offline inspections are used to monitor equipment damage, then damage assessment can be performed, but real-time damage insight is not provided and operations are interrupted
Solution Approach 1:
The patent replaces physical offline inspections with a computational damage prediction model that processes real-time process parameters. The model mathematically predicts damage accumulation based on operating conditions, substituting mechanical inspection methods with automated computational analysis that provides continuous damage assessment without stopping equipment operation.
Solution Approach 2:
The patent introduces process parameters as intermediary variables that correlate with damage mechanisms. By measuring accessible process parameters (temperature, pressure, flow rates) that mediate between operating conditions and actual damage, the system indirectly assesses damage state without direct physical inspection, enabling continuous monitoring during normal operations.
2Reliability
If real-time damage prediction using process parameters is implemented, then continuous damage monitoring is achieved, but system complexity increases
Solution Approach 1:
The patent creates a universal damage prediction model that can assess multiple types of equipment damage using the same computational framework and process parameters. The model handles different damage mechanisms (corrosion, erosion, fatigue) through unified mathematical relationships, allowing one system to perform multiple damage assessment functions without proportionally increasing complexity.
Solution Approach 2:
The patent transforms the damage assessment problem by changing from direct physical measurement parameters to computational process parameters. Instead of measuring difficult-to-obtain damage metrics directly, the system uses readily available process operating parameters and transforms them through mathematical models to predict damage, simplifying the measurement infrastructure while improving reliability.
Data Source
AI summary
A method for real-time damage prediction includes obtaining a damage prediction model that mathematically models expected damage to equipment in an industrial process based on a plurality of process parameters. The method also includes obtaining real-time state information for at least one of the plurality of process parameters. The method further includes determining, based on the real-time state information and the damage prediction model, a real-time prediction of damage to at least one component of the equipment in the industrial process. The method may also include obtaining historical data for the plurality of process parameters, and the real-time prediction of damage can be based on the historical data, the real-time state information, and the damage prediction model. The method may further include identifying and adjusting a high limit and a low limit for the at least one of the plurality of process parameters.