# Magnetic performance measurement and mathematical model establishment of main core of magnetic modulator

Title | Magnetic performance measurement and mathematical model establishment of main core of magnetic modulator |

Publication Type | Conference Paper |

Year of Publication | 2017 |

Authors | Liren, Z., Xin, Y., Yang, P., Li, Z. |

Conference Name | 2017 13th IEEE International Conference on Electronic Measurement Instruments (ICEMI) |

ISBN Number | 978-1-5090-5035-2 |

Keywords | adjusted R-square, arc-hyperbolic sine function, B-H curve mathematical model, ballistic method, coercive force, compositionality, Curve fitting, curve fitting tool, DC current comparator, degree-of-freedom adjusted coefficient of determination, electromagnetic induction, excitation source, ferromagnetic materials, induced voltage, Magnetic cores, Magnetic field measurement, Magnetic flux, magnetic hysteresis, Magnetic modulators, magnetic performance, magnetic performance measurement, magnetic permeability, magnetisation, magnetization curve, main core 1J85 permalloy, Mathematical model, MATLAB, maximum permeability, mean square error methods, multiple regression method, Permalloy, permeability curve, polynomial function, pubcrawl, regression analysis, remanence, remanent magnetic induction intensity, resilience, Resiliency, RMSE, root mean squared error, saturation magnetic induction intensity, Saturation magnetization, Sensitivity, SSE, sum of squares due to error |

Abstract | In order to investigate the relationship and effect on the performance of magnetic modulator among applied DC current, excitation source, excitation loop current, sensitivity and induced voltage of detecting winding, this paper measured initial permeability, maximum permeability, saturation magnetic induction intensity, remanent magnetic induction intensity, coercivity, saturated magnetic field intensity, magnetization curve, permeability curve and hysteresis loop of main core 1J85 permalloy of magnetic modulator based on ballistic method. On this foundation, employ curve fitting tool of MATLAB; adopt multiple regression method to comprehensively compare and analyze the sum of squares due to error (SSE), coefficient of determination (R-square), degree-of-freedom adjusted coefficient of determination (Adjusted R-square), and root mean squared error (RMSE) of fitting results. Finally, establish B-H curve mathematical model based on the sum of arc-hyperbolic sine function and polynomial. |

URL | https://ieeexplore.ieee.org/document/8265906/ |

DOI | 10.1109/ICEMI.2017.8265906 |

Citation Key | liren_magnetic_2017 |

- adjusted R-square
- arc-hyperbolic sine function
- B-H curve mathematical model
- ballistic method
- coercive force
- Compositionality
- Curve fitting
- curve fitting tool
- DC current comparator
- degree-of-freedom adjusted coefficient of determination
- electromagnetic induction
- excitation source
- ferromagnetic materials
- induced voltage
- Magnetic cores
- Magnetic field measurement
- Magnetic flux
- magnetic hysteresis
- Magnetic modulators
- magnetic performance
- magnetic performance measurement
- magnetic permeability
- magnetisation
- magnetization curve
- main core 1J85 permalloy
- Mathematical model
- MATLAB
- maximum permeability
- mean square error methods
- multiple regression method
- Permalloy
- permeability curve
- polynomial function
- pubcrawl
- regression analysis
- remanence
- remanent magnetic induction intensity
- resilience
- Resiliency
- RMSE
- root mean squared error
- saturation magnetic induction intensity
- Saturation magnetization
- Sensitivity
- SSE
- sum of squares due to error