Stable subspace dimension reduced MUSIC for blade tip timing

Yang, Zhi-BoXi An Jiao Tong Univ, Sch Mech Engn, Xian 710049, Peoples R China. (författare)

Multiple signal classification (MUSIC) is a parameter extraction method for blade tip timing to suppress the under-sampled problem. Its faster version, subspace dimension reduced MUSIC (SDR-MUSIC), has been proposed, which uses a single noise vector instead of the whole noise subspace to reduce computational complexity. However, the principle of random noise vector selection leads to instability in frequency identification. Therefore, we replace the random vector with the min-norm vector to obtain a stable SDR-MUSIC (SSDR-MUSIC). The superiority of the min-norm vector can be mathematically proven by the location of the zeros of the polynomial. Simulated and experimental tests indicate that SSDR-MUSIC gains stability when the min-norm vector is used while maintaining computational efficiency.

Wang, Zeng-KunUppsala universitet,Avdelningen för systemteknik,Xi An Jiao Tong Univ, Sch Mech Engn, Xian 710049, Peoples R China.(Swepub:uu)zenwa681 (författare)
Li, Hao-QiXi An Jiao Tong Univ, Sch Mech Engn, Xian 710049, Peoples R China. (författare)
Tian, Shao-HuaXi An Jiao Tong Univ, Sch Mech Engn, Xian 710049, Peoples R China. (författare)
Chen, Xue-FengXi An Jiao Tong Univ, Sch Mech Engn, Xian 710049, Peoples R China. (författare)
Xi An Jiao Tong Univ, Sch Mech Engn, Xian 710049, Peoples R China.Avdelningen för systemteknik (creator_code:org_t)

Av författaren/redakt...: Yang, Zhi-Bo; Wang, Zeng-Kun; Li, Hao-Qi; Tian, Shao-Hua; Chen, Xue-Feng

Om ämnet

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.