Application of Non Filtering Analytic Wavelet Transform for the Investigation of Rotating Stall Inception in Low Speed Compressor
2016 7th International Conference on Mechanical and Aerospace Engineering (ICMAE): Proceedings 2016
Ali Arshad, Qiushi Li, Tianyu Pan

Rotating stall inception in low speed axial compressor is experimentally investigated by using temporal casing pressure signals from the circumferentially distributed pressure transducers. At first, fundamental technique of visual inspection is implemented by the application of series of low pass frequency filters. Only small filter ranges reveal rotating stall disturbance, each exhibiting different rotating speed of stall disturbance and stall cell. Results are highly dependent on filter size, which found to be a critical limitation. In the next step, results of filtered signals are compared by using a newly developed non-filtering AWT program. AWT offers a beneficial tool for providing rotating stall inception information without employing any pre-filtering limitation. One-step execution technique with features of FFT and wavelet transform, AWT successfully verified the results from the filtered signals obtained after the application of different filter ranges. Verification of filtered signal results with AWT can be a useful approach in stall inception study.


Atslēgas vārdi
Compressor, Stall inception, Wavelet transform, Filter range, Non-filtering
DOI
10.1109/ICMAE.2016.7549582
Hipersaite
https://ieeexplore.ieee.org/document/7549582

Arshad, A., Li, Q., Pan, T. Application of Non Filtering Analytic Wavelet Transform for the Investigation of Rotating Stall Inception in Low Speed Compressor. No: 2016 7th International Conference on Mechanical and Aerospace Engineering (ICMAE): Proceedings, Lielbritānija, London, 18.-20. jūlijs, 2016. Piscataway: IEEE, 2016, 448.-453.lpp. ISBN 978-1-4673-8830-6. e-ISBN 978-1-4673-8829-0. Pieejams: doi:10.1109/ICMAE.2016.7549582

Publikācijas valoda
English (en)
RTU Zinātniskā bibliotēka.
E-pasts: uzzinas@rtu.lv; Tālr: +371 28399196