Design Model Validation Using Test Signals and Disturbance Estimation
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Solution Overview
Problem
Existing design models for technical systems, such as control systems, may not accurately reflect real-world conditions, leading to potential instability and safety issues when stability and safety guarantees are based on assumptions that do not match real conditions.
Innovation Solution
A method for validating design models by applying test signals to technical systems, detecting outputs, determining system states and disturbances, and comparing these values with the allowable ranges specified in the design model, thereby validating the model's accuracy under real conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If design models use assumed parameter ranges and disturbance variables to provide stability and safety guarantees, then stability and safety can be ensured under assumed conditions, but the model accuracy deteriorates when real conditions deviate from assumptions
Solution Approach 1:
The validation method performs preliminary checks by comparing assumed parameter ranges and disturbance variables against actual measured values before the technical system operates. This preliminary validation ensures that the design model's assumptions match real conditions, preventing stability and safety issues before they occur.
Solution Approach 2:
The invention implements a feedback mechanism where actual parameter values and disturbance variables measured during operation are continuously compared with the assumed ranges in the design model. This feedback loop validates whether the model remains accurate under real conditions and triggers alerts or corrective actions when deviations occur, maintaining both reliability and model accuracy.
2Device complexity
If design models assume fixed parameter ranges and disturbance variables during development, then the design process becomes manageable and stable, but the system's adaptability to real-world variations deteriorates
Solution Approach 1:
The invention transforms the static design model into a dynamic validation system. While the design phase maintains fixed parameter ranges for manageability, the operational phase dynamically validates whether actual parameters within those ranges match assumptions. This dynamic approach preserves design simplicity while adapting to real-world variations through continuous validation.
Solution Approach 2:
The method allows parameter ranges and disturbance variables to be updated based on validation results. When real conditions consistently differ from assumptions, the assumed parameter ranges in the design model can be adjusted to reflect actual operating conditions, thereby improving model adaptability while maintaining a structured design process.
3Productivity
If no validation is performed on design model assumptions, then the system can operate continuously without additional validation steps, but stability and safety guarantees deteriorate when assumptions do not match real conditions
Solution Approach 1:
The validation method is designed to operate continuously alongside the technical system without interrupting normal operations. Validation checks are performed in real-time using data already being collected during operation, ensuring both continuous productivity and ongoing reliability verification.
Solution Approach 2:
The system performs self-validation by using its own operational data to verify whether its design model assumptions hold true. The technical system validates itself by comparing measured parameters and disturbances against assumed ranges, eliminating the need for external validation processes and maintaining continuous operation.
Data Source
AI summary
A method for validating a design model for a technical system includes (i) providing the design model, wherein the design model models the technical system, and wherein the design model indicates an allowable range for at least one parameter of the technical system and for at least one disturbance variable, (ii) initiating an application of a test signal to the technical system, (iii) initiating a capture of an output of the technical system triggered by the test signal, (iv) determining a state of the technical system based on the test signal and the captured output, a respective value for the at least one parameter of the technical system being determined based on the state, (v) determining a disturbance in the technical system based on the test signal, the captured output, and the determined state, wherein a respective value for the at least one disturbance variable is determined, and (vi) validating the design model for the technical system, wherein the respective value for the at least one parameter of the technical system and the respective value for the at least one disturbance variable are compared with the allowable range of the design model. A computer program, a device, and a storage medium for this purpose is also disclosed.