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A method of stall recognition using nonlinear feature extraction from the compressor outlet pressure
The paper presents a method for analysing the pressure signal at the compressor outlet, which allows to detect when the machine operating point approaches the area where a stall is about to occur. The signal analysis method is based on nonlinear feature extraction from the dynamic signal. The correl...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10616336/ https://www.ncbi.nlm.nih.gov/pubmed/37916116 http://dx.doi.org/10.1016/j.heliyon.2023.e20909 |
Sumario: | The paper presents a method for analysing the pressure signal at the compressor outlet, which allows to detect when the machine operating point approaches the area where a stall is about to occur. The signal analysis method is based on nonlinear feature extraction from the dynamic signal. The correlation dimension ([Formula: see text]) is used to quantify the complexity of the measured signal, its value decreasing if the analysed signal originates from deterministic processes. The results presented indicate that the correlation dimension of the signal decreases at flow rates approximately 10% above the flow rate at which negative effects on machine performance occur. This trend has been observed across multiple rotor speeds. These findings suggest that the perturbations associated with the onset of the stall can propagate to the compressor outlet, leading to less chaotic pressure behaviour that reflects the dynamics of these perturbations. The fact that stall can be identified from the pressure signal in the space between the rotor and the diffuser in its early stages is well known, but the possibility of identifying stall at the compressor outlet, where the perturbations are significantly attenuated, has not been documented in the literature. |
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