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Application of Uniform Experimental Design in Optimizing Excitation Parameters for Magnetic Frequency Mixing Measurements

Yu Chang et al · KeAi Communications Co., Ltd · 2020

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Abstract Excitation parameter preferences are key factors affecting the performance of magnetic frequency mixing detection. A uniform experimental design method was used to analyze this influence. Using fuzzy theory, a comprehensive model is established for evaluating the effect of magnetic frequency mixing. A polynomial is selected as the regression function to express explicitly the correlation between the excitation parameters and the frequency-mixing effect. The excitation parameters were then optimized using genetic algorithm. Magnetic frequency mixing experiments were conducted to measure the surface hardness of some ferromagnetic materials. Frequency mixing is further enhanced under the optimal settings, resulting in an improvement in the measurement sensitivity. The results of this study support the application of the magnetic frequency mixing technique in non-destructive testing.

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APA 7

al, Y. C. E. (2020). Application of Uniform Experimental Design in Optimizing Excitation Parameters for Magnetic Frequency Mixing Measurements. https://doi.org/10.1186/s10033-020-0430-y

MLA

al, Yu Chang et. "Application of Uniform Experimental Design in Optimizing Excitation Parameters for Magnetic Frequency Mixing Measurements." 2020. https://doi.org/10.1186/s10033-020-0430-y.

Chicago

al, Yu Chang et. 2020. "Application of Uniform Experimental Design in Optimizing Excitation Parameters for Magnetic Frequency Mixing Measurements.". https://doi.org/10.1186/s10033-020-0430-y.

Harvard

al, Y. C. E. 2020, Application of Uniform Experimental Design in Optimizing Excitation Parameters for Magnetic Frequency Mixing Measurements, KeAi Communications Co, Ltd, available at: https://doi.org/10.1186/s10033-020-0430-y [Accessed 7 Aug. 2026].

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Title
Application of Uniform Experimental Design in Optimizing Excitation Parameters for Magnetic Frequency Mixing Measurements
Author / contributors
Yu Chang et al
Publisher
KeAi Communications Co., Ltd
Publication year
2020
ISSN
1000-9345
ISSN
1000-9345
Language
English

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