Digital Twin Fatigue Solver for Polymeric Asset Damage Tracking
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Solution Overview
Problem
Current fatigue analysis methods, particularly for polymeric physical assets, face challenges in accurately predicting maintenance needs due to limited access to historical data and inefficiencies in detecting damage, leading to unexpected failures and safety issues.
Innovation Solution
A digital twin system that combines Finite Element Analysis (FEA) with real-time sensor data to predict maintenance requirements by updating a damage model with operational information, generating status reports, and providing warnings based on residual life calculations using a fatigue solver algorithm.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional reactive maintenance methods with manual sensor data review are used, then device complexity is reduced, but measurement precision and reliability of damage detection deteriorate
Solution Approach 1:
The patent creates a digital twin (virtual copy) of the physical asset that replicates its operational characteristics and damage accumulation behavior. This digital replica allows for precise damage detection through virtual simulations without requiring complex physical inspection systems, thereby improving measurement precision while managing device complexity through information-based rather than purely physical means.
Solution Approach 2:
The patent replaces manual mechanical inspection methods with automated computational simulations. The fatigue solver algorithm and digital twin system substitute human engineers' manual analysis with automated computational processes, significantly improving measurement precision and reliability while reducing the complexity of manual data review processes.
2Loss of information
If historical data is accessed from vendor servers, then information completeness improves, but loss of time in data access and productivity increases
Solution Approach 1:
The patent performs preliminary actions by pre-computing and storing damage accumulation results in the digital twin during normal operations. When maintenance decisions are needed, the system already has pre-calculated damage states and predictions available, eliminating the need for time-consuming historical data retrieval and re-analysis, thus improving both information accessibility and productivity.
Solution Approach 2:
The digital twin system serves itself by automatically tracking and updating its own damage state through continuous simulations. The system maintains its own historical data and damage accumulation records without requiring external vendor server access, enabling self-sufficient damage assessment that improves both information completeness and operational productivity.
3Reliability
If visual inspection of physical assets is performed, then ease of operation is maintained, but measurement precision and reliability of damage detection deteriorates
Solution Approach 1:
The patent creates a digital replica (digital twin) of the physical asset that can be inspected and analyzed without physically accessing the actual component. This virtual copy provides reliable damage detection through computational simulations while maintaining ease of operation, as engineers can access and analyze the digital model remotely without needing to physically locate or inspect the actual asset.
Solution Approach 2:
The digital twin acts as an intermediary between the physical asset and the engineer. Instead of directly inspecting the physical component, engineers interact with the digital replica that mediates the inspection process, providing reliable damage information while maintaining ease of operation through remote access to the virtual model.
Data Source
AI summary
A digital twin system for predicting a residual life of a physical asset includes at least one user computer and at least one server. The user computer has a graphical user interface permitting a user to receive damage event warnings, end of life warnings, and status reports. The server communicates with the user computer and includes an administration subsystem that is in communication with a data source. The administration subsystem includes at least one database. The administration subsystem is configured to receive the physical asset's operating history data transmitted by the data source and store the operating history data into the database. The server further includes a simulator. The simulator is in communication with the administration subsystem and is configured to perform several functions, for example, updating the digital twin and generating residual life predictions.