1.College of Mechanical
Engineering and Applied Electronics Technology, Beijing University
of Technology, Beijing 100022, China; 2.College of Mechanical
and Electrical Engineering, China University of Petroleum, Beijing
102249, China;
Abstract:The structure and principle of a new type of a diphase opposition giant magnetostrictive self-sensing actuator is introduced. A bridge analysis model based on variable inductance is established. Dynamic balance separation technology for the giant magnetostrictive self-sensing actuator comes true by the least means square (LMS) self-adapting algorithm. The scheme design of one important part of the circuit with the real-time separation circuit of the dynamic balance signal based on a digital signal processor is obtained. The part of the signal separated circuit is designed, which includes logarithmic-antilog practical multiplication circuit, amplifying circuit, filter circuits, and amplifier circuit. Based on the embedded system simulation software—PROTUES, the simulation effect of the circuit that separates the sensing signal from the mixed signals is obvious, which indicates that the circuit can rapidly and stably work. Moreover, the structure is simple, reliable, and meets the practical requirement.
Jenner A G, Greenough R D, Wilkinson A J, Parvinmher A. Performance of magnetostrictive rare earth iron compoundsfor device. IEEE Transactions on Magnetics, 1990, 26(5): 2589–2591 doi: 10.1109/20.104807
Ben H S, Martin L. Self-sensing applications for electromagnetic actuators. Sensors and Actuators A: Physical, 2004, 116(2): 345–351 doi: 10.1016/j.sna.2004.05.003
Tzou H S, Anderson G L, Natori M C. Active Structure, Device, and Systems: Chapter authored by Gacia E and Jones L D. Singapore: World Science Publishing Company, 1997
Hall D L. Dynamics and vibrations of magnetostrictive transducer. PhD Dissertation, Ames: Iowa State University, 1994, 56–78
John P, Alison B F. Development and analysis of a self-sensing magnetostrictive actuator design. In: Proceedings of SPIE, Smart Structures and IntelligentSystems, VOL 1917, 1993, 952–961
Vipperman J S. Adaptive piezoelectric sensorial actuators for activestructural acoustic control. PhD Dissertation, Durham: Duke University, 1997, 67–86
Wong K K, Cheng R S K, Letaief K B, Murch R D. Adaptive antennas at the mobile and base stations inan OFDM/TDMA system. IEEE Transactionson Communications, 2001, 49(1): 195–206 doi: 10.1109/26.898262
Julie E G. Modified LMS algorithms for speech processing with anadaptive noise cancelle. IEEE Transactions on Speech and Audio Processing, 1998, 6(4): 338–351 doi: 10.1109/89.701363
Widrow B, Duvall K, Gooch R, Newman W. Signal cancellation phenomena in adaptive antennas: causes and cures. IEEE Transactions on Antennas and Propagation, 1982, 30(3): 469–478 doi: 10.1109/TAP.1982.1142804
Gorriz J M, Ramirez J, Cruces-Alvarez S, Puntonet C G, Lang E W, Erdogmus D. A novel LMS algorithm applied to adaptivenoise cancellation. IEEE Signal ProcessingLetters, 2009, 16(1): 34–37 doi: 10.1109/LSP.2008.2008584