Design of fluid bearing spindle motors with controlled unbalanced magnetic forces

Chen, Shixin; Zhang, Qide; Liu, Zhejie; Lin, H.

doi:10.1109/20.617433

Cited by 10 publications

(4 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A very complete definition of eccentricity fault for AFPM machine has been presented in [92] which covers static angular misalignment, dynamic angular misalignment, SE misalignment, and DE misalignment. Various studies have focused on analytical [93][94][95][96][97][98][99][100][101][102], numerical [103][104][105], and hybrid [106] modelling aspect of eccentric RFPM machines. The same has been done for AFPM machines [92,[107][108][109].…”

Section: Eccentricity Fault Diagnosis Indices For Axial Flux Pm Machinesmentioning

confidence: 99%

Eccentricity fault diagnosis indices for permanent magnet machines: state‐of‐the‐art

Faiz

Nejadi-Koti

2019

IET Electric Power Applications

View full text Add to dashboard Cite

Eccentricity fault with 10% severity is probably the only existing fault in a brand new healthy electrical machine that is acceptable as a manufacturing tolerance. This fault can be developed due to a continuous pull between stator and rotor, even in a de-energized machine. So, it must be diagnosed,and its severity monitored. The authors introduced and criticized various indices for eccentricity fault diagnosis. Advantages, drawbacks, and ambiguous points of each index and potential ground for improvement of these techniques are addressed. Moreover, different eccentric PM machine modelling techniques are reviewed and environmental factors affecting the eccentricity fault detection process are discussed. This survey covers all direct current and alternating current PM machines. It provides information about the researches performed since 1986 and it is helpful to newcomers to this field, artisans, and protection system designers. Considering the given information, the readers achieve enough understanding of the weaknesses and strong points of each eccentricity fault diagnosis index. Then, these indices are evaluated through assigning weight coefficients under various scenarios. Interested individuals can modify these weight coefficients based on the specifics of the application and decide which index is the most appropriate.

show abstract

Section: Eccentricity Fault Diagnosis Indices For Axial Flux Pm Machinesmentioning

confidence: 99%

Eccentricity fault diagnosis indices for permanent magnet machines: state‐of‐the‐art

Faiz

Nejadi-Koti

2019

IET Electric Power Applications

View full text Add to dashboard Cite

show abstract

“…Under the assumption of white measurement noise, for the system described by (1) and 2, it can be proved that a pair of controller parameters makes also makes [see (21) in the Appendix]. This means the minima (local or global) of the measured TMR are also the minima (local or global) of true TMR.…”

Section: White Measurement Noise Casementioning

confidence: 99%

A gradient-based track-following controller optimization for hard disk drive

Hao

Chen²,

Guo³

et al. 2003

IEEE Trans. Ind. Electron.

View full text Add to dashboard Cite

This paper presents a gradient-based parameter optimization method to find the optimal compensator that minimizes the standard deviation (PES) of the position error signal (PES) in a hard disk drive servo system. By using the plant response data and the PES gradient information based on the nominal plant model, optimal digital controllers that minimized the 3 PES of a plant with uncertainty were selected within a pre-found robust stable region. As a result, an optimal track-following controller that minimized the standard deviation of the measured PES (PESm) was able to be obtained without the prior knowledge of the disturbance and noise model. Furthermore, we proved that if the measurement noise is white, an optimal controller that minimizes the 3 PESm also minimizes the 3 PES. Both simulation and implementation results suggest that such a gradient-based search process is faster than nongradient optimization methods such as Random Neighborhood Search and genetic algorithms. Index Terms-Gradient method, hard disk drive (HDD) servo, optimization, track mis-registration (TMR). I. INTRODUCTION I MPROVING the servo system performance for lower track mis-registration (TMR) is one of the prerequisites of moving to higher recording density in hard disk drives (HDDs). To cope with the challenge of the actuator pivot nonlinearity, high-frequency uncertainty, the effects of various external disturbances and noises, many efforts on the spindle motor, air flow, and arm/suspension designs have been made to reduce disturbance level and increase the actuator resonance frequency [1]. In addition, the improved servo control designs, such as proportional-integral-derivative (PID), LQG/LTR [2], [3], multirate control [4], [5], disturbance observer [6], and mode-switching control [7] also have been studied extensively as a cost-effective way toward higher track density. However, due to the limitation of the accuracy and uncertainty of the plant and disturbance models, system sampling frequency, controller order, stable margin requirements, and plant input saturation, the real servo system could not increase its bandwidth to an arbitrarily high value and achieve the best disturbance rejection.

show abstract

“…Since UMF is determined by both PM and armature fields, the superposition method investigated in [23] must be extended to include the armature field influence for UMF prediction. Finite-element analysis (FEA) is the most widely used method in the machine analysis aspect recently [24][25][26], since it can precisely consider the saturation of each part of the machine. The problem for the FEA is time consuming, especially for large machine calculation and 3D analysis situation.…”

Section: Introductionmentioning

confidence: 99%

Unbalanced magnetic force prediction in permanent magnet machines with rotor eccentricity by improved superposition method

Zhu

2017

IET Electric Power Applications

View full text Add to dashboard Cite

An improved superposition method accounting for both permanent magnet (PM) and armature field is proposed to predict the unbalanced magnetic force (UMF) of PM machines having static/dynamic eccentricity. It virtually divides the original eccentric machine into a number of sections along the circumferential direction. Then, a series of concentric machine models are established with equivalent air-gap lengths corresponding to those air-gap sections. From the electromagnetic field of each concentric machine predicted by subdomain method, the air-gap field of the original eccentric machine can be synthesised. Finally, the UMF can be easily obtained by the integral of force density along the air-gap circumference. The effectiveness of the proposed method is validated on bothr o t a t i n ga s y m m e t r i ca n d symmetrical PM machines by direct finite-element analysis and experiment, with particular emphasis of rotor eccentricity influence on the UMF of later one.

show abstract

Design of fluid bearing spindle motors with controlled unbalanced magnetic forces

Cited by 10 publications

References 3 publications

Eccentricity fault diagnosis indices for permanent magnet machines: state‐of‐the‐art

Eccentricity fault diagnosis indices for permanent magnet machines: state‐of‐the‐art

A gradient-based track-following controller optimization for hard disk drive

Unbalanced magnetic force prediction in permanent magnet machines with rotor eccentricity by improved superposition method

Contact Info

Product

Resources

About