TY - JOUR
T1 - Displacement Self-Sensing Method for AMB-Rotor Systems Using Current Ripple Demodulations Combined with PWM Command Signals
AU - Jiang, Yinxiao
AU - Wang, Kun
AU - Sun, Maolin
AU - Xie, Jinjin
N1 - Publisher Copyright:
© 2001-2012 IEEE.
PY - 2019/7/15
Y1 - 2019/7/15
N2 - The self-sensing magnetic bearing technology offers significant cost savings and the potential advantages for dynamics performance due to its fundamental sensor-actuator collocation. Based on the active magnetic bearing (AMB) driven by a 2-level pulse width modulation (PWM) switch power amplifier, an analog circuit was designed to estimate the rotor position through extracting the fundamental component information of the current ripples. This paper addresses two key challenges on the displacement self-sensing of AMB-rotor systems: the one is how to accurately extract the fundamental frequency component from the current ripple, and another one is proposing a PWM duty cycle cancellation method to enhance the detecting accuracy of rotor displacement. First, the basic self-sensing principle of demodulation approach is presented. Second, mathematical description of PWM duty cycle cancellation method using driving voltage combined with PWM command signals was deduced. Third, the band-pass filter was designed for extracting the fundamental frequency components of ripple current, and the full-wave rectification was designed for detecting the peak envelope of the fundamental component, and the low-pass filter was designed for filtering out high-frequency noise. Finally, experiments were carried out on a magnetic suspension turbo-molecular pump to evaluate the static and dynamic performance of the designed self-sensing system. The experiment results show that the rotor can be well suspended in a static state, and its speed can reach 6000 rpm. The experiments demonstrate that the designed self-sensing system has the ability to meet the requirement of dynamic performance and stability margin.
AB - The self-sensing magnetic bearing technology offers significant cost savings and the potential advantages for dynamics performance due to its fundamental sensor-actuator collocation. Based on the active magnetic bearing (AMB) driven by a 2-level pulse width modulation (PWM) switch power amplifier, an analog circuit was designed to estimate the rotor position through extracting the fundamental component information of the current ripples. This paper addresses two key challenges on the displacement self-sensing of AMB-rotor systems: the one is how to accurately extract the fundamental frequency component from the current ripple, and another one is proposing a PWM duty cycle cancellation method to enhance the detecting accuracy of rotor displacement. First, the basic self-sensing principle of demodulation approach is presented. Second, mathematical description of PWM duty cycle cancellation method using driving voltage combined with PWM command signals was deduced. Third, the band-pass filter was designed for extracting the fundamental frequency components of ripple current, and the full-wave rectification was designed for detecting the peak envelope of the fundamental component, and the low-pass filter was designed for filtering out high-frequency noise. Finally, experiments were carried out on a magnetic suspension turbo-molecular pump to evaluate the static and dynamic performance of the designed self-sensing system. The experiment results show that the rotor can be well suspended in a static state, and its speed can reach 6000 rpm. The experiments demonstrate that the designed self-sensing system has the ability to meet the requirement of dynamic performance and stability margin.
KW - Active magnetic bearing
KW - current ripple demodulation
KW - dynamic performance
KW - self-sensing
KW - stability margin
UR - https://www.scopus.com/pages/publications/85067923624
U2 - 10.1109/JSEN.2019.2904106
DO - 10.1109/JSEN.2019.2904106
M3 - 文章
AN - SCOPUS:85067923624
SN - 1530-437X
VL - 19
SP - 5460
EP - 5469
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
IS - 14
M1 - 8664194
ER -