7-days of FREE Audio papers, translation & more with Prime
7-days of FREE Prime access
7-days of FREE Audio papers, translation & more with Prime
7-days of FREE Prime access
https://doi.org/10.1088/1361-6501/aca81c
Copy DOIJournal: Measurement Science and Technology | Publication Date: Dec 14, 2022 |
License type: iop-standard |
In view of the difficulty in identifying the state of the micro turbine blade, this paper uses the order spectral entropy analysis method to extract the characteristic information of the blade fault based on the measured micro turbine bearing vibration data. Firstly, a micro-turbine test bench was established. The normal temperature stable inlet flow was produced by a blower, the high temperature and pressure unstable airflow was generated by turbojet combustion chamber, and the working inlet mode of a micro-turbine with a wide range of speed changes was simulated. The vibration signal of the bearing was collected by shell drilling, a variety of time-frequency domain feature analysis methods based on vibration signal are difficult to effectively identify blade faults under the combined action of unstable airflow and frequent variable speed. In this paper, the bearing vibration data in time domain is converted to the vibration data in angle domain, and then the order amplitude and entropy were compared and analyzed. The results show that the proposed method can effectively identify the blade fracture and fouling faults under the driving of stable and unstable airflow in the speed range of 0–20 000 r min−1. This method provides a new method for micro turbine blade condition monitoring through bearing vibration data.
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.