The Symmetry/Asymmetry Phenomenon in the Fault Diagnosis Process of Industrial Machinery
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Engineering and Materials".
Deadline for manuscript submissions: 30 September 2024 | Viewed by 1955
Special Issue Editors
Interests: non-stationary signal processing; time-frequency analysis; mechanical dynamics analysis; mechanical fault diagnosis
Interests: machine fault diagnosis under non-stationary conditions; time-frequency analysis; adaptive mode decomposition
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Industrial machinery often undergoes inevitable health degradation. Vibration-signal-based monitoring for machinery has always played an important role in the diagnosis and prognosis of industrial machinery. Vibration signals collected in healthy machinery usually appear to have good symmetry, even in the early fault stage. With the development of the fault, the symmetry of vibration signals gradually degenerates until it breaks. Therefore, it is important to detect the asymmetry/asymmetry of the signal for the timely diagnosis and prognosis of the machinery. The intention of this Special Issue is to present methods dealing mainly (but not exclusively) with state-of-the-art solutions for signal processing and dynamics modeling to deeply explore the symmetry/asymmetry phenomenon in the process of machinery diagnostics and prognostics.
Dr. Gang Yu
Dr. Shiqian Chen
Guest Editors
Manuscript Submission Information
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Keywords
- symmetry/asymmetry
- vibration signal processing
- machinery diagnostics and prognostics
- machinery monitoring
- early fault diagnosis
Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Identification of modal parameters using an improved sparse blind source separation
Authors: Gang Yu
Affiliation: School of Electrical Engineering, University of Jinan, Jinan 250022, China
Abstract: During the last decade, blind source separation (BSS) method has become an effective tool to characterize and identify modal parameters of linear systems. However, in practical engineering, the assumptions of guaranteeing conventional BSS method successful application cannot be satisfied frequently, which lead to some challenging issues. One of these challenges is how to deal with the modal identification issue in the under-determined case, which means the number of sensors being less than that of the active modals. In this paper, we explore an efficient under-determined BSS method called sparse BSS (SBSS). The drawbacks of conventional SBSS are first listed and an improved SBSS method is proposed to deal with the mentioned problems, which is shown to be more suitable for engineering applications. A 5-degrees-of-freedom numerical system and two experiments are employed to validate the effectiveness of the proposed method. The identified results of modal parameters show highly satisfied accuracy via comparative analysis, which illustrates the proposed SBSS having a potential application in structural engineering.
Key words: Modal identification; Sparse blind source separation; Under-determined