Electric Rotational Machine Speed Calculation From Vibration Spectra
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Solution Overview
Problem
Existing methods for calculating the mechanical speed of electric rotational machines are inaccurate due to changing parameters in mathematical motor models caused by temperature, wear, and load changes, leading to faulty rotor position estimation and speed control.
Innovation Solution
A method that calculates the mechanical speed by extracting a frequency component greater than a threshold from vibration sensor data, using this component to update motor model parameters and adjust control parameters for precise speed estimation and control, minimizing noise and accounting for changing machine characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If parameters of mathematical motor model are measured during commissioning, then initial speed estimation can be performed, but parameters become inaccurate over time due to temperature, wear, and load changes
Solution Approach 1:
The patent transforms the static motor model parameters into dynamic parameters that automatically adapt to changing operating conditions. Vibration sensor data continuously updates the mechanical speed component, which in turn adjusts the motor model parameters in real-time, resolving the contradiction between initial measurement capability and long-term parameter stability.
Solution Approach 2:
The patent implements a feedback mechanism where vibration sensor measurements are continuously processed to extract mechanical speed components. This extracted information feeds back to update the motor model parameters, creating a closed-loop system that maintains accuracy despite temperature, wear, and load variations.
2Measurement precision
If frequency spectrum analysis is performed on vibration sensor data, then mechanical speed can be extracted, but background noise affects the accuracy of speed calculation
Solution Approach 1:
The patent applies extraction by isolating the mechanical speed component from the overall vibration signal through frequency spectrum analysis. By identifying and extracting only the frequency components corresponding to mechanical speed (greater than threshold frequencies), the method separates the useful signal from background noise and irrelevant vibrations.
Solution Approach 2:
The patent changes parameters by applying frequency domain transformation to the time-domain vibration signal. This parameter transformation allows the system to identify mechanical speed components based on their frequency characteristics, effectively filtering out low-frequency background noise and isolating the relevant speed information.
3Measurement precision
If additional sensors are added to improve speed measurement accuracy, then measurement precision increases, but device complexity and cost increase
Solution Approach 1:
The patent makes the vibration sensor multi-functional by using it for both condition monitoring and speed measurement. The same sensor that detects mechanical faults also provides the frequency spectrum data needed to extract mechanical speed components, eliminating the need for separate speed sensors and reducing overall system complexity.
Solution Approach 2:
The patent enables the vibration sensor to serve itself by using its own output signal for speed measurement. The mechanical speed information is extracted from the vibration signal that the sensor already generates during normal operation, without requiring additional measurement resources.
Data Source
AI summary
A method (100) for calculation of a mechanical speed of an electric rotational machine (400) including calculating (101) a frequency spectrum from signals measured by at least one vibration sensor (403) attached to the rotational machine (400); extracting (103) a mechanical speed component from the calculated frequency spectrum; calculating (105) the mechanical speed of the rotational machine (400) as a function of the mechanical speed component, wherein the mechanical speed component is extracted as a function of a frequency component that is greater than a given threshold (303).


