Dynamic Simulation for Rotating Machine Imbalance Detection
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Solution Overview
Problem
Existing methods for detecting imbalances in rotating machine elements, such as turbines and generators, are cumbersome and require manual analysis of sensor data, leading to inefficiencies and increased costs, especially at high rotational speeds where imbalances can indicate damage.
Innovation Solution
A method involving continuous recording of sensor data and dynamic simulation of the rotating machine element to automatically detect and quantify imbalances, using simulated sensor data to minimize the distance between detected and simulated data, allowing for precise localization of imbalances along the axis of rotation, orientation, and distance from the axis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual analysis of sensor data is used to detect imbalances, then measurement precision can be maintained, but loss of time increases due to time-consuming manual analysis
Solution Approach 1:
The patent creates a virtual copy of the rotating machine element through dynamic simulation, generating simulated sensor data that mirrors real sensor data. This virtual model allows automated analysis without manual intervention, resolving the contradiction by enabling both precise measurement and time efficiency through digital replication and automated comparison of sensor signals.
Solution Approach 2:
The patent replaces manual mechanical analysis with automated computational analysis. Instead of experts manually examining sensor data, the system uses dynamic simulation and automated signal processing to detect imbalances, substituting human analysis with algorithmic processing that maintains precision while eliminating time loss.
2Productivity
If dynamic simulation with variable dynamic load is used to detect imbalances, then productivity increases through automated detection, but device complexity increases due to simulation requirements
Solution Approach 1:
The dynamic simulation model serves multiple functions simultaneously: it replicates the mechanical behavior of the rotating element, generates expected sensor data under various imbalance conditions, and enables automated comparison with actual sensor data. This multi-functionality increases productivity while managing complexity by consolidating multiple detection tasks into a single simulation framework.
Solution Approach 2:
The system varies parameters in the dynamic simulation, such as imbalance magnitude, position, and rotational speed, to generate a comprehensive set of reference sensor data. By systematically changing simulation parameters to match real operating conditions, the system achieves high detection productivity without requiring overly complex simulation models, as parameter variation provides diverse detection scenarios within a unified framework.
Data Source
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AI summary
To detect an imbalance in a rotating machine element (ME), sensor data (SD) is continuously acquired and fed into a dynamic simulation (SIM) of the rotating machine element (ME), which is run in parallel with the machine element's operation. The simulation (SIM) uses the acquired sensor data (SD) to determine a dynamic state (STAT) of the rotating machine element (ME), simulating a variable dynamic load (F) acting on the rotating machine element (ME). Based on the determined dynamic state (STAT), simulated sensor data (SSD) is generated. The dynamic load (F) is varied to reduce the difference (D) between the simulated sensor data (SSD) and the acquired sensor data (SD). Furthermore, the magnitude (|Fu|) of the imbalance is derived from the dynamic load (RF) resulting from this variation and output.