From 581e4e97e1c53cfd51189fab1f60b2fa61f9dcc4 Mon Sep 17 00:00:00 2001 From: Sebastian Schachten Date: Thu, 22 Aug 2024 10:11:39 +0200 Subject: [PATCH] added data of all 15 MagNet materials (all by a H-DC of 0 A/m) added names of manufacturer and materials as enumerations included a table with an overview of the material data in the database updated README file --- README.rst | 6 +- .../figures/Material_Database_Overview.png | Bin 192535 -> 210347 bytes .../figures/Material_Database_Overview.svg | 3346 ++++++++--------- .../figures/Material_Database_Overview.xlsx | Bin 13387 -> 13102 bytes materialdatabase/data/material_data_base.json | 2 +- materialdatabase/enumerations.py | 14 + .../material_data_base_functions.py | 19 +- ..._MagNet_permeability_data_into_database.py | 78 +- 8 files changed, 1616 insertions(+), 1849 deletions(-) diff --git a/README.rst b/README.rst index 9a20aec..0c280a1 100644 --- a/README.rst +++ b/README.rst @@ -16,7 +16,8 @@ Usable features ~~~~~~~~~~~~~~~~~ * Human-readable database based on a .json-file - * The database currently contains 19 different materials as shown in the following table + * The database currently contains 19 different ferrite materials as shown in the following table + * The database includes data from manufacturer datasheets,the Princeton MagNet project and self measured data |material_overview| @@ -41,9 +42,6 @@ Usable features * Get the magnetic parameters from the database * Providing permeability and permittivity data for `FEMMT `__ -* Simulation features: - * All the material-data in the database can be used in the FEM-Magnetics-Toolbox for FEM-Simulations - * Interpolation of material data (both electric and magnetic parameters) * GUI features (included in `FEMMT `__): diff --git a/docs/source/figures/Material_Database_Overview.png b/docs/source/figures/Material_Database_Overview.png index 3b4da333e3c259d70191606077053379bdcc6b80..3951b7b1e5ef0386c77d5ec673743f105672a694 100644 GIT binary patch literal 210347 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zhBpWm;TPQts|gz|eluGA^Q{@T_K%)Sig>@^Y9-`P&G#I}#u4BahxT|k^u%0#vY5)C;k(HKi zCMz;Oq`xy%gMzTd+OclIqTmZyS5rB@iwWEEPkhjheFc!^sp zagF!q+_Pp9?+uwP=wcV-b$v#7geJ1$UuyI;v@0J!IWSog3U4AmyVX*bOKArC5KVO2 zF_JxNcYVhEUAoOmT(_$4XM9Cl-Z2|;R}BUH&2}UZ!`FG^`V3YkIH*b=H_5%|_O*{rA?siPwl> zK2RqxM!!!nQvZTLbFTdQWco<_PnPRBIMfk<|6NPLLb=rtgU|o~SS=bEOo11N{NJx{ z0D$B#Ve{{4gi-Lw!|xEmE{O^U)$>^ZX6| EA6}UzegFUf diff --git a/materialdatabase/data/material_data_base.json b/materialdatabase/data/material_data_base.json index 2147ca8..24c22dd 100644 --- a/materialdatabase/data/material_data_base.json +++ b/materialdatabase/data/material_data_base.json @@ -31450,7 +31450,7 @@ } }, "ML95S": { - "Manufacturer": "Hitachi", + "Manufacturer": "Proterial", "manufacturer_datasheet": { "initial_permeability": 1100, "resistivity": 8, diff --git a/materialdatabase/enumerations.py b/materialdatabase/enumerations.py index 0856f56..5271715 100644 --- a/materialdatabase/enumerations.py +++ b/materialdatabase/enumerations.py @@ -42,6 +42,8 @@ class Manufacturer(str, Enum): Ferroxcube = "Ferroxcube" DMEGC = "DMEGC" SUMIDA = "Sumida" + FairRite = "Fair-Rite" + Proterial = "Proterial" class MeasurementDataType(str, Enum): @@ -151,7 +153,19 @@ class Material(str, Enum): TEST = "TEST" # FOR TESTING STUFF _3F46 = "3F46" + _3C90 = "3C90" + _3C92 = "3C92" + _3C94 = "3C94" _3C95 = "3C95" + _3E6 = "3E6" + _3F4 = "3F4" + _77 = "77" + _78 = "78" + _79 = "79" + ML95S = "ML95S" + T37 = "T37" + N27 = "N27" + N30 = "N30" N49 = "N49" N87 = "N87" N95 = "N95" diff --git a/materialdatabase/material_data_base_functions.py b/materialdatabase/material_data_base_functions.py index 6e6c91c..d041c2c 100644 --- a/materialdatabase/material_data_base_functions.py +++ b/materialdatabase/material_data_base_functions.py @@ -186,16 +186,17 @@ def interpolate_a_b_c(a, b, c, no_interpolation_values=20): # Load Permeability -------------------------------------------------------------------------------------------------------------------------------------------- -def updates_x_ticks_for_graph(x_data: list, y_data: list, x_new: list): +def updates_x_ticks_for_graph(x_data: list, y_data: list, x_new: list, kind: str = "linear"): """ Update the x-values of the given (x_data,y_data)-dataset and returns y_new based on x_new. :param x_data: x-data given :param y_data: y-data given :param x_new: new x-values + :param kind: kind of interpolation :return: y_new-data corresponding to the x_new-data """ - f_linear = interp1d(x_data, y_data, fill_value="extrapolate") + f_linear = interp1d(x_data, y_data, kind=kind, fill_value="extrapolate") return f_linear(x_new) @@ -608,13 +609,13 @@ def process_permeability_data(b_ref_raw, mu_r_raw, mu_phi_deg_raw, b_min: float fig, ax = plt.subplots(3) # Amplitude Plot - # ax[0].plot(b_ref_raw, mu_r_raw, label=f) + ax[0].plot(b_ref_raw*1000, mu_r_raw, label="raw") ax[0].plot(1000*b_ref, mu_r, "-x", label=f"{f=}, {T=}") ax[0].grid(True) ax[0].set_ylabel("rel. permeability") # Phase Plot - # ax[1].plot(b_ref_raw, mu_phi_deg_raw) + ax[1].plot(b_ref_raw*1000, mu_phi_deg_raw, label="raw") # if smooth_data: ax[1].plot(1000*b_ref, mu_phi_deg, "-x", label=f"{f=}, {T=}") ax[1].grid(True) @@ -1477,10 +1478,10 @@ def get_bh_integral(b, h, f): """ Calculate the hysteresis loss density. - :param b: magnetic flux density - :param h: magnetic field strength - :param f: frequency - :return: hysteresis loss density + :param b: magnetic flux density in T + :param h: magnetic field strength in A/m + :param f: frequency in Hz + :return: hysteresis loss density in W/m^3 """ return f * 0.5 * np.abs(np.sum(b * (np.roll(h, 1, axis=0) - np.roll(h, -1, axis=0)), axis=0)) # shoelace formula @@ -1589,7 +1590,7 @@ def calc_electric_field_strength_from_lecroy_voltage_data(voltage: np.array = No return electric_field_strength -def eps_phi_deg__from_eps_r_and_p_hyst(frequency, e_peak, eps_r, p_eddy): +def eps_phi_deg__from_eps_r_and_p_eddy(frequency, e_peak, eps_r, p_eddy): """ Calculate the angle of the permittivity. diff --git a/materialdatabase/scripts/write_MagNet_permeability_data_into_database.py b/materialdatabase/scripts/write_MagNet_permeability_data_into_database.py index 25a1d8b..882c77d 100644 --- a/materialdatabase/scripts/write_MagNet_permeability_data_into_database.py +++ b/materialdatabase/scripts/write_MagNet_permeability_data_into_database.py @@ -7,7 +7,7 @@ import pandas as pd import math import os -from scipy import constants +# from scipy import constants import materialdatabase as mdb material_db = mdb.MaterialDatabase() @@ -24,12 +24,13 @@ INSTRUCTIONS TO PUT DATA INTO DATABASE: 0. CHOOSE SIGNAL-SHAPE, TO LOAD OR PROCESS THE DATA AND TO WRITE THE DATA INTO THE DATABASE - 1. INPUT MATERIAL NAME AS ENUMERATION (Material.XXX.value) - 2. INPUT MANUFACTURER NAME AS ENUMERATION (Manufacturer.XXX) - 3. INPUT BASIC DATASHEET PARAMETERS FOR MATERIAL - 4. INPUT PATH TO FOLDER CONTAINING MagNet-DATA - 5. CHANGE ENUMERATION IN VARIABLE datadict TO DESIRED MATERIAl (MagNetFileNames._XXX.value) - 6. RUN SCRIPT + 1. SET MINIMUM NUMBER OF MEASUREMENT POINTS (START WITH LOW VALUE) + 2. INPUT MATERIAL NAME AS ENUMERATION (Material.XXX.value) + 3. INPUT MANUFACTURER NAME AS ENUMERATION (Manufacturer.XXX) + 4. INPUT BASIC DATASHEET PARAMETERS FOR MATERIAL + 5. INPUT PATH TO FOLDER CONTAINING MagNet-DATA + 6. CHANGE ENUMERATION IN VARIABLE datadict TO DESIRED MATERIAl (MagNetFileNames._XXX.value) + 7. RUN SCRIPT """ @@ -38,19 +39,21 @@ TRIANGLE = False # SET TRUE TO RUN TRIANGULAR DATA # TODO NOT IMPLEMENTED TRAPEZOID = False # SET TRUE TO RUN TRAPEZOIDAL DATA # TODO NOT IMPLEMENTED # PROCESS OF DATA -PROCESS_DATA = True # SET TRUE TO PROCESS DATA IF NOT DATA IS LOADED FROM GIVEN PATH +PROCESS_DATA = False # SET TRUE TO PROCESS DATA IF NOT DATA IS LOADED FROM GIVEN PATH # WRITE DATA INTO DATABASE -WRITE = False # SET TRUE TO WRITE DATA INTO DATABASE +WRITE = True # SET TRUE TO WRITE DATA INTO DATABASE -material = Material.N87.value # 1. -manufacturer = Manufacturer.Ferroxcube # 2. -initial_permeability = 2200 # 3. -resistivity = 10 # 3. -max_flux_density = 0.53 # 3. -volumetric_mass_density = 4850 # 3. +min_number_of_measurements = 7 # 1. -path = os.path.join(pt.my_MagNet_data_path, material) # 4. -data_dict = mat73.loadmat(os.path.join(path, MagNetFileNames._N87.value)) # 5. +material = Material._3F4.value # 2. +manufacturer = Manufacturer.Ferroxcube # 3. +initial_permeability = 900 # 4. +resistivity = 10 # 4. +max_flux_density = 0.41 # 4. +volumetric_mass_density = 4700 # 4. + +path = os.path.join(pt.my_MagNet_data_path, material) # 5. +data_dict = mat73.loadmat(os.path.join(path, MagNetFileNames._3F4.value)) # 6. cross_section = data_dict["Data"]["Effective_Area"] l_mag = data_dict["Data"]["Effective_Length"] @@ -92,46 +95,44 @@ permeability_amplitude = [calc_mu_r_from_b_and_h_array(b=b, h=h) for b, h in zip(mag_flux_density, mag_field_strength_without_offset)] # B_DC = np.array(H_DC_Bias) * mu - B_DC = np.array(H_DC_Bias) * constants.mu_0 * np.array(permeability_amplitude) - mag_flux_density_offset = [b + offset for b, offset in zip(mag_flux_density, B_DC)] + # B_DC = np.array(H_DC_Bias) * constants.mu_0 * np.array(permeability_amplitude) + # mag_flux_density_offset = [b + offset for b, offset in zip(mag_flux_density, B_DC)] - powerloss = [get_bh_integral(b=b, h=h, f=f) for b, h, f in zip(mag_flux_density_offset, mag_field_strength_offset, frequency)] + powerloss = [get_bh_integral(b=b, h=h, f=f) for b, h, f in zip(mag_flux_density, mag_field_strength_without_offset, frequency)] permeability_angle = [mu_phi_deg__from_mu_r_and_p_hyst(frequency=f, b_peak=abs(max(b, key=abs)), mu_r=mu, p_hyst=p) - for f, b, mu, p in zip(frequency, mag_flux_density_offset, permeability_amplitude, powerloss)] + for f, b, mu, p in zip(frequency, mag_flux_density, permeability_amplitude, powerloss)] np.savetxt(os.path.join(path, "sine/Voltage[V].csv"), voltage, delimiter=",") np.savetxt(os.path.join(path, "sine/Current[A].csv"), current, delimiter=",") np.savetxt(os.path.join(path, "sine/Frequency[Hz].csv"), frequency, delimiter=",") np.savetxt(os.path.join(path, "sine/Temperature[C].csv"), temperature, delimiter=",") - np.savetxt(os.path.join(path, "sine/H_waveform[Am-1].csv"), mag_field_strength_offset, delimiter=",") + np.savetxt(os.path.join(path, "sine/H_waveform[Am-1].csv"), mag_field_strength_without_offset, delimiter=",") np.savetxt(os.path.join(path, "sine/H_DC_Bias[Am-1].csv"), H_DC_Bias, delimiter=",") - np.savetxt(os.path.join(path, "sine/B_waveform[T].csv"), mag_flux_density_offset, delimiter=",") - np.savetxt(os.path.join(path, "sine/B_DC[T].csv"), B_DC, delimiter=",") + np.savetxt(os.path.join(path, "sine/B_waveform[T].csv"), mag_flux_density, delimiter=",") np.savetxt(os.path.join(path, "sine/Volumetric_losses[Wm-3].csv"), powerloss, delimiter=",") np.savetxt(os.path.join(path, "sine/Permeability_amplitude[_].csv"), permeability_amplitude, delimiter=",") np.savetxt(os.path.join(path, "sine/Permeability_angle[°].csv"), permeability_angle, delimiter=",") dict_sine = {"temperature": temperature, - "mag_flux_density": [abs(max(x, key=abs)) for x in mag_flux_density_offset], + "mag_flux_density": [abs(max(x, key=abs)) for x in mag_flux_density], "frequency": (np.array(frequency)/1000).astype(int)*1000, # round up to kHz "powerloss": powerloss, "H_DC_Bias": H_DC_Bias, - "B_DC": B_DC, "permeability_amplitude": permeability_amplitude, "permeability_angle": permeability_angle} df_sine = pd.DataFrame.from_dict(dict_sine) df_sine.to_csv(os.path.join(path, "sine/data_sine.csv"), index=False) - print("Sine data processed and saved!") + print("\n Sine data processed and saved!") else: df_sine = pd.read_csv(os.path.join(path, "sine/data_sine.csv"), encoding='latin1') unique_frequency = sorted(set(df_sine["frequency"])) - unique_H_DC_offset = sorted(set(df_sine["H_DC_Bias"])) + # unique_H_DC_offset = sorted(set(df_sine["H_DC_Bias"])) + unique_H_DC_offset = [0] # only the data for an H_DC of 0 A/m unique_temperature = sorted(set(df_sine["temperature"])) - min_number_of_measurements = 8 # Init the database entry if WRITE: @@ -146,9 +147,8 @@ for H_DC in unique_H_DC_offset: for frequency in unique_frequency: print("Number of measurement points: ", df_sine.query(filter_string).shape[0]) - if df_sine.query(filter_string).shape[0] > min_number_of_measurements: - b_ref = np.array(df_sine.query(filter_string).sort_values('mag_flux_density')["mag_flux_density"]) - \ - np.array(df_sine.query(filter_string).sort_values('mag_flux_density')["B_DC"]) + if df_sine.query(filter_string).shape[0] >= min_number_of_measurements: + b_ref = np.array(df_sine.query(filter_string).sort_values('mag_flux_density')["mag_flux_density"]) mu_r = np.array(df_sine.query(filter_string).sort_values('mag_flux_density')["permeability_amplitude"]) mu_phi_deg = np.array(df_sine.query(filter_string).sort_values('mag_flux_density')["permeability_angle"]) @@ -189,13 +189,13 @@ permeability_amplitude = [calc_mu_r_from_b_and_h_array(b=b, h=h) for b, h in zip(mag_flux_density, mag_field_strength_without_offset)] # B_DC = np.array(H_DC_Bias) * mu - B_DC = np.array(H_DC_Bias) * constants.mu_0 * np.array(permeability_amplitude) - mag_flux_density_offset = [b + offset for b, offset in zip(mag_flux_density, B_DC)] + # B_DC = np.array(H_DC_Bias) * constants.mu_0 * np.array(permeability_amplitude) + # mag_flux_density_offset = [b + offset for b, offset in zip(mag_flux_density, B_DC)] - powerloss = [get_bh_integral(b=b, h=h, f=f) for b, h, f in zip(mag_flux_density_offset, mag_field_strength_offset, frequency)] + powerloss = [get_bh_integral(b=b, h=h, f=f) for b, h, f in zip(mag_flux_density, mag_field_strength_offset, frequency)] permeability_angle = [mu_phi_deg__from_mu_r_and_p_hyst(frequency=f, b_peak=abs(max(b, key=abs)), mu_r=mu, p_hyst=p) - for f, b, mu, p in zip(frequency, mag_flux_density_offset, permeability_amplitude, powerloss)] + for f, b, mu, p in zip(frequency, mag_flux_density, permeability_amplitude, powerloss)] np.savetxt(os.path.join(path, "triangle/Voltage[V].csv"), voltage, delimiter=",") np.savetxt(os.path.join(path, "triangle/Current[A].csv"), current, delimiter=",") @@ -204,18 +204,16 @@ np.savetxt(os.path.join(path, "triangle/Duty_cycle[_].csv"), duty_cycle, delimiter=",") np.savetxt(os.path.join(path, "triangle/H_waveform[Am-1].csv"), mag_field_strength_offset, delimiter=",") np.savetxt(os.path.join(path, "triangle/H_DC_Bias[Am-1].csv"), H_DC_Bias, delimiter=",") - np.savetxt(os.path.join(path, "triangle/B_waveform[T].csv"), mag_flux_density_offset, delimiter=",") - np.savetxt(os.path.join(path, "triangle/B_DC[T].csv"), B_DC, delimiter=",") + np.savetxt(os.path.join(path, "triangle/B_waveform[T].csv"), mag_flux_density, delimiter=",") np.savetxt(os.path.join(path, "triangle/Volumetric_losses[Wm-3].csv"), powerloss, delimiter=",") np.savetxt(os.path.join(path, "triangle/Permeability_amplitude[_].csv"), permeability_amplitude, delimiter=",") np.savetxt(os.path.join(path, "triangle/Permeability_angle[°].csv"), permeability_angle, delimiter=",") dict_triangle = {"temperature": temperature, - "mag_flux_density": [abs(max(x, key=abs)) for x in mag_flux_density_offset], + "mag_flux_density": [abs(max(x, key=abs)) for x in mag_flux_density], "frequency": (np.array(frequency)/1000).astype(int)*1000, # round up to kHz "powerloss": powerloss, "H_DC_Bias": H_DC_Bias, - "B_DC": B_DC, "duty_cycle": duty_cycle, "permeability_amplitude": permeability_amplitude, "permeability_angle": permeability_angle}