Compressor Flow Control Using Vibration Feedback for Noise Reduction
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Solution Overview
Problem
Existing flow-generating devices, particularly electrically driven ones, experience torque ripple leading to undesirable noise generation due to deviations in electromagnetic flux and load changes, which existing methods have not adequately addressed.
Innovation Solution
A method and device utilizing sensors to detect vibrations caused by torque ripple, employing artificial intelligence and machine learning to determine adaptive control parameters that reduce or eliminate noise by optimizing the operation of the flow-generating device based on real-time input parameters and environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If conventional control methods are used for electric motors in flow-generating devices, then the device operates with standard control parameters, but torque ripple occurs leading to audible noise
Solution Approach 1:
The patent implements feedback control by detecting torque ripple through current sensor measurements of phase currents. The detected torque ripple information is fed back to the controller, which then generates disturbance wave correction instructions to compensate for the ripple, thereby reducing audible noise while maintaining reliable operation.
Solution Approach 2:
The patent changes control parameters by introducing disturbance wave correction instructions based on detected torque ripple. These correction instructions modify the standard control parameters (phase currents) to compensate for torque fluctuations, thereby reducing noise without sacrificing operational reliability.
2Object-affected harmful factors
If standard control parameters are used without adaptation, then the control system remains simple, but noise reduction is insufficient under changing operating conditions
Solution Approach 1:
The control system incorporates feedback mechanisms that detect torque ripple through current sensors and automatically generate correction instructions. This feedback-based approach enables adaptive noise reduction without requiring complex manual tuning or redesign of the control system architecture.
Solution Approach 2:
The control system performs self-adjustment by automatically detecting torque ripple and generating its own correction instructions. The system serves itself by using its own operational data (phase currents) to identify and correct noise-causing torque fluctuations, eliminating the need for external intervention or complex external control systems.
3Object-affected harmful factors
If torque ripple correction is implemented using phase current analysis, then noise can be reduced, but the control system requires additional sensors and processing
Solution Approach 1:
The system uses feedback from existing current sensors to detect torque ripple by analyzing phase current minima and maxima. This approach leverages already-present sensors rather than adding new hardware, reducing the complexity increase while still achieving effective torque ripple correction and noise reduction.
Solution Approach 2:
The patent uses phase current analysis as an intermediary method to indirectly measure torque ripple without requiring direct torque sensors. By analyzing the relationship between phase currents and torque production, the system can detect and correct torque ripple using electrical measurements that are already available in the motor control system.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Effectively reduces or eliminates noise generated by flow-generating devices by continuously adapting control parameters to changing conditions, such as aging and environmental factors, using AI and machine learning to optimize operation.
Implementation Method 1
at least one sensor which is configured to generate and provide a sensor signal that describes a vibration
Implementation Method 2
an electric motor configured to drive the flow generation unit
Data Source
Figure 1
Figure 2
Figure 3~4
AI summary
A method (V) and a device (10) for controlling a flow-generating device (11), in particular a compressor (12), are provided. During operation of the flow-generating device (11), a vibration and/or oscillation is generated, which is detected by at least one sensor (22, 23) and described by at least one sensor signal (S1, S2). In a control device (16, 19), a relationship (F) between input parameters (PIN) and at least one control parameter (CO) is determined based on the at least one sensor signal (S1, S2) and a current operating point (AP) of the flow-generating device (11). The relationship (F) can, for example, be a parameter matrix (MX) or any other mathematical and/or logical structure that links the input parameters (PIN) with the at least one control parameter (CO), for example, an adaptive or machine-learning-modifiable logical structure.This allows for the consideration of changing circumstances, in particular aging effects. The at least one control parameter (CO) determined based on the relationship (F) is used for the control of the flow-generating device (11), in particular an electric motor (13).