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Pasquale Arpaia (1) , Alessandro Masi (2) , Giovanni Spiezia (2) , Antonio Zanesco (1)

Dynamic Characterization of Nonlinear Magnets by Modeling and Measuring Magnetic Field Phase Spectrum. Pasquale Arpaia (1) , Alessandro Masi (2) , Giovanni Spiezia (2) , Antonio Zanesco (1) Università del Sannio, Dipartimento di Ingegneria, Italy CERN, AT-MTM Group, Switzerland.

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Pasquale Arpaia (1) , Alessandro Masi (2) , Giovanni Spiezia (2) , Antonio Zanesco (1)

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  1. Dynamic Characterization of Nonlinear Magnets by Modeling and Measuring Magnetic Field Phase Spectrum • Pasquale Arpaia(1), Alessandro Masi(2), Giovanni Spiezia(2), Antonio Zanesco(1) • Università del Sannio, Dipartimento di Ingegneria, Italy • CERN, AT-MTM Group, Switzerland

  2. State of the art investigation of magnet macroscopic behavior in industrial applications • New digital measurement systems to determine magnetic characteristics • Development of adequate nonlinear models for transfer functions when imposing a flux for generating currents

  3. Measurement method: basic ideas • Analytic relationship between dynamic hysteresis and current phase spectrum • Decomposition of nonlinear material behavior in a hysteretic component and a non-hysteretic component

  4. Relationship between hysteresis and current phase spectrum Non-hysteretic behavior Symmetrical hysteretic behavior ai= 0, ai= p, "i=1…nk Asymmetrical hysteretic behavior

  5. Common-mode component Differential component Material non linearity decomposition Asymmetrical hysteretic characteristic

  6. Dynamic model of hysteretic material

  7. nh NI(t) Characterization of the measurement method MEASUREMENT METHOD ^ rms[NI-NI] Model estimate Measurementuncertainty Noise

  8. Sigma=0.0010 Sigma=0.0008 Sigma=0.0005 Sigma=0.0003 Sigma=0.0001 Simulation results rms of the model error in estimating NI for an added white noise

  9. Sigma=0.001 Sigma=0.0008 Sigma=0.0005 Sigma=0.0003 Sigma=0.0001 Simulation results rms of the model error in estimating NI for an added LF noise

  10. Sigma=0.001 Sigma=0.0008 Sigma=0.0005 Sigma=0.0003 Sigma=0.0001 Simulation results rms of the model error in estimating NI for an added HF noise

  11. nh= 15 n = 30 Classical method Proposed method Comparison with classical algorithm Comparison between polynomial interpolation and proposed method in case of white noise Classical method Proposed method Noise Standard Deviation

  12. nh= 15 n = 30 Classical method Proposed method Comparison with classical algorithm Comparison between polynomial interpolation and proposed method in case of LF noise Classical method Proposed method Noise Standard Deviation

  13. nh= 15 n = 30 Classical method Proposed method Comparison with classical algorithm Comparison between polynomial interpolation and proposed method in case of HF noise Proposed method Classical method Noise Standard Deviation

  14. Experimental results Lab measurement station

  15. Ferrite (Mn-Zn) Frequency 200 Hz Maximum flux density nh= 15 fc = 25.6 kHz Df=25 Hz nc= 1024 Bmax= 0.08 T Bmax= 0.17 T Bmax= 0.28 T Method application to an actual case Measurement conditions

  16. Proposed method performance for Bmax= 0.08T Experimental points Proposed method Campo magnetico H (A/m) Induzione magnetica B (T) Results Magnetic Field – H (A/m) Magnetic Field - H Magnetic flux density - B(T)

  17. Proposed method performances for Bmax= 0.17T Experimental points Proposed method Campo magnetico H (A/m) Induzione magnetica B(T) Results Magnetic Field – H (A/m) Magnetic flux density - B(T)

  18. Experimental points Proposed method Results Proposed method performances for Bmax= 0.28T Campo magnetico H (A/m) Magnetic Field – H (A/m) Magnetic flux density - B(T)

  19. Conclusions • Method to characterize magnet dynamic behavior by modeling and measuring current phase spectrum • Preliminary validation on digital signals affected by different noises • Comparison in simulation with results obtained by a classical estimation method • Experimental verification by a lab measurement station • Satisfactory results à Good alternative at classical methods suitable for DSP implementation

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