Magnetostriction (MS) caused by the global magnetization of limbs and yokes and magnetic forces are the undisputed causes of the vibration and noise in power transformer cores. This paper presents a novel way to reduce the vibration and noise, in which nanocrystalline soft magnetic composite (NSMC) material with high permeability is used to fill the step-lap joint gaps of the power transformer magnetic cores. In order to numerically predict the effectiveness of the proposed method, a 3-D magneto-mechanical strong coupled model including MS and magnetic anisotropy of steel sheet was founded. Then, the numerical model was applied to analyze the step-lap joint region of the corner of magnetic cores. The analysis results illustrated that the deformation and noise of core with NSMC are lower than with the traditional epoxy damping material. Moreover, the validity of the proposed new way was verified by the simplified step-lap joint cores, which were achieved based on Epstein Frames.

In order to seek new vibration reduction method for magnetically controlled saturable reactors (MCSRs), this paper studies the stress characteristic which is the inherent reason of vibration and noise. Under the practical working condition, dc and ac excitations make iron cores work in a magnetic saturation state. Meanwhile, the stress in reactor cores always exists and influences on magnetic properties of the core material. Because the core material shows different magnetization and magnetostrictive properties under dc bias and stress, a database of magnetization and magnetostrictive curves of silicon steel under different tensile stresses with different dc bias excitations is tested. Based on the measured constitutive relations, an electromagneto-mechanical two-way coupled numerical model for MCSRs is presented. Vibrations considering magnetostrictive effect, electromagnetic force effect, and the combination of them are calculated to compare the influence of the two forces on MCSR vibration. From the computation results, it can be seen that the total vibration stress is not a simple superposition of electromagnetic stress and magnetostrictive stress. Finally, vibration stress of an MCSR prototype under working conditions is tested to prove the validity of the proposed model.

Magnetically controlled reactors (MCRs) are widely used as reactive power compensation equipment owing to their favorable properties of smoothly adjusting their inductance value through dc bias. However, the dc bias and the rotational magnetization at corner and T-joint areas make the cores of MCRs saturated, resulting in high magnetostriction and vibration. Thus, the electromagnetic vibration analysis of MCRs must consider the vector hysteretic magnetostriction effect. In this article, a vector hysteretic magnetostriction model of silicon steel is proposed by combining the quadratic domain rotation model with the vector inverse Jiles–Atherton model firstly. Then, based on the measured magnetization and magnetostrictive characteristics curves of silicon steel, the model’s parameters are optimized by velocity controllable particle swarm optimization (VCPSO). Finally, the vector hysteretic magnetostriction model is combined with the finite element method (FEM) to simulate the vector vibration characteristics of MCR under dc bias. The simulation results show that the vector property of electromagnetic vibration and magnetic field at the T-joint area is higher than that at other areas. And the MCR vibration test results are consistent with the simulation results, which verify the accuracy of the proposed model in simulating electromagnetic vibration.

The main factors of stress distribution in MCRs are the magnetostriction effect of the core materials and the magnetic force between gaps under DC bias excitation. This paper developed a coupling model for MCRs considering Maxwell magnetic force and magnetostriction under DC flux density biases. The constitutive equations of the magnetic field and strain field are constructed based on the magnetic property curves with a new measured and analyzed method to consider DC magnetic flux biases, which is the key contributions of this study. Then, the electromagnetic vibration properties of the MCR model are calculated and analyzed. To prove the validity of the proposed method, the vibration of a 4.4 kVar-220 V MCR is tested and analyzed.

The rail inductance gradient is an important parameter of the electromagnetic launcher. The calculation of its value is important for the design of the launcher structure and for predicting the motion behavior of the armature. The current research on the inductance gradient analysis method of the electromagnetic rail launcher mostly does not take into account the effects of launcher size and current diffusion. This method cannot describe its dynamic characteristics, and it results in a large error compared with the actual launch. Therefore, the paper first establishes an electromagnetic rail launcher armature motion model to obtain the rail velocity skin depth under a U-shaped armature. Second, an analytical method for calculating the inductance gradient based on the dynamic skin depth of the rail is obtained, which takes into account the launcher size and velocity skin effect. Finally, the experimental results verify the correctness and accuracy of the method to achieve an accurate prediction of armature speed.

In order to study and analyze the rotating magnetic properties for nanocrystalline material, an improved 2-D high-frequency magnetic properties tester with step-shaped excitation windings and composite sensing structure is designed and modeled. Magnetic concentration and core poles optimization are performed in 2-D tester construction, which can generate relatively uniform and strong magnetic field in the testing area. By using the composite sensing structure of sensing coil combined with needle probe method, B and H signals can accurately be detected. Meanwhile, feedback control algorithm and harmonic compensation are established to obtain the desired magnetization curves and improve the measurement precision.