Stacked Transformer Core Elasticity Modeling for Vibration Noise Analysis
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Solution Overview
Problem
Transformers with stacked iron cores experience vibration noise due to magnetostriction, leading to inefficiencies in noise reduction despite using electrical steel sheets with low magnetostriction properties, primarily due to resonance phenomena and inaccuracies in calculating mechanical vibration properties.
Innovation Solution
A method to determine the elasticity matrix of a stacked iron core by acquiring frequency spectra of noise and magnetostriction, calculating vibration response functions, and optimizing transverse elastic moduli to reduce noise, involving a multi-step process to find local maximum values for accurate elasticity matrix determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional vibration analysis methods are used with assumed elastic moduli, then analysis can be performed quickly, but accuracy of vibration property calculation is insufficient
Solution Approach 1:
The patent implements an iterative feedback mechanism where the calculated vibration properties are compared with measured values, and the transverse elastic moduli are adjusted based on the degree of coincidence between calculated and measured frequency spectra. This feedback loop continues until optimal accuracy is achieved, resolving the contradiction between calculation speed and accuracy.
Solution Approach 2:
The system uses the transformer's own measured vibration data to determine its own elasticity matrix parameters. By utilizing the transformer's actual vibration properties as reference, the method enables self-calibration without requiring external testing equipment or complex experimental setups, thus improving accuracy while maintaining practical simplicity.
2Measurement precision
If different elastic moduli are assumed for different portions of the iron core, then vibration analysis accuracy improves, but the complexity of determining elasticity matrices increases
Solution Approach 1:
The iron core is divided into multiple portions (e.g., yoke and column sections) with different transverse elastic moduli. Each portion is assigned its own elasticity matrix based on its specific geometric and material properties. This segmentation allows the patent to capture local variations in vibration characteristics, significantly improving analysis accuracy while the automated optimization process keeps the determination process manageable.
Solution Approach 2:
Different portions of the iron core are assigned different elastic moduli reflecting their local properties. The yoke portion and column portion have distinct transverse elastic moduli (G1 and G2) determined through the optimization process. This local quality approach ensures that each region's specific mechanical behavior is accurately represented in the vibration analysis.
3Reliability
If resonance phenomena are not considered in the analysis model, then calculations are simpler, but noise reduction design effectiveness decreases
Solution Approach 1:
The patent explicitly models mechanical vibration phenomena including resonance by using the determined elasticity matrices in vibration analysis calculations. The system calculates natural frequencies and mode shapes, and evaluates resonance conditions by comparing operating frequencies with natural frequencies. This enables accurate prediction of resonance-induced noise and facilitates effective noise reduction design.
Solution Approach 2:
The elasticity matrix determination and vibration analysis are performed during the design phase before the transformer is manufactured. By preliminarily identifying resonance conditions and optimizing the structure accordingly, the patent prevents resonance-related noise problems rather than attempting to address them after construction, thereby improving noise reduction effectiveness while keeping the overall process efficient.
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
This approach reduces discrepancies between measured and calculated vibration properties, enhancing the accuracy of vibration analysis and noise reduction in transformers.
Implementation Method 1
vibration of the iron core caused by magnetostriction generates noise
Data Source
AI summary
A transformer stacked iron core elasticity matrix determination method including: acquiring a frequency spectrum of excitation noise; acquiring a frequency spectrum of excitation magnetostriction; calculating a frequency spectrum of a vibration response function when first and second provisional values of transverse elastic moduli are applied to an elasticity matrix; calculating a frequency spectrum of excitation vibration based on frequency spectrum data of the excitation magnetostriction and the frequency spectrum of the vibration response function; calculating a degree of coincidence between a frequency spectrum of noise and the frequency spectrum of the excitation vibration; calculating the degree of coincidence for each combination of the first provisional value and the second provisional value; and adopting the first and second provisional values as the transverse elastic moduli when the degree of coincidence is a local maximum value.