Abstract
Machine condition monitoring and diagnosis have become increasingly important, and the application of these processes has been widely investigated. The authors previously proposed a stepwise diagnosis method for a beam structure. In that method, the location of the abnormality is first estimated using the force identification approach, and then the cause of the abnormality is identified. In this study, the stepwise diagnosis method was improved specifically for rotating machinery. The applicability of the proposed method was checked by using the experimental data. In the case of a rotor system with unbalance, it was shown that the location of the abnormality and its severity could be identified, and, in the case of a rotor system with stationary rubbing, the location of the abnormality could be accurately identified. Therefore, it was confirmed that the proposed diagnostic method is feasible for actual application.
Highlights
Machine condition monitoring and diagnosis have become increasingly important, and the application of these processes to beam structures and rotating machinery has been widely investigated
The authors developed a new diagnostic approach to increase the robustness of the stepwise diagnosis method, where the mathematical model was modified based on the difference of the response between the measurement and the simulation [12]
To construct a mathematical model, the shaft was divided into 20 elements, and the characteristic matrices were obtained by Finite Element Method (FEM) using a beam element
Summary
Machine condition monitoring and diagnosis have become increasingly important, and the application of these processes to beam structures and rotating machinery has been widely investigated. At the early stage of diagnosis, abnormality data is encountered, and a primary diagnosis is required to identify the location and cause of the abnormality. The authors previously proposed a stepwise primary diagnostic method [11] that was a modelbased approach in which the location of the abnormality is first estimated using the force identification approach. A numerical example showed that the location and cause of the abnormality could be identified with sufficient accuracy, and that this method was useful for primary diagnosis. The authors developed a new diagnostic approach to increase the robustness of the stepwise diagnosis method, where the mathematical model was modified based on the difference of the response between the measurement and the simulation [12]. The cause of the abnormality and its severity are identified
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