Omnidirectional regeneration (ODR) of proximity sensor signals for robust diagnosis of journal bearing systems. (June 2017)

• Record Type: Journal Article
• Authors: Jung, Joon Ha; Jeon, Byung Chul; Youn, Byeng D.; Kim, Myungyon; Kim, Donghwan; Kim, Yeonwhan
• Is Part Of: Mechanical systems and signal processing. Volume 90(2017)
• Page Start: 189
• Page End: 207
• Publication Date: 2017-06
• Subjects: Journal bearing rotor system -- Anomaly diagnosis -- Gap sensor -- Vibration signal -- Directionality of anomaly; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2016.12.030
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: We propose the omnidirectional regeneration (ODR) of gap sensor signals of journal bearing rotor systems. The directionality of health states is studied, and the metric is proposed. The ODR generates vibration signals without placing extra sensors. The ODR signals help obtain reliable diagnose results for the directional health states. The proposed method is validated by the experiment data. Abstract: Some anomaly states of journal bearing rotor systems are direction-oriented (e.g., rubbing, misalignment). In these situations, vibration signals vary according to the direction of the sensors and the health state. This makes diagnosis difficult with traditional diagnosis methods. This paper proposes an omnidirectional regeneration method to develop a robust diagnosis algorithm for rotor systems. The proposed method can generate vibration signals in arbitrary directions without using extra sensors. In this method, signals are generated around the entire circumference of the rotor to consider all possible directions. Then, the directionality of each state is proved by mathematically and is evaluated using a proposed metric. When a directional state is determined, the classification is carried out on all of the generated signals. When a non-directional state is found, the classification is performed on only one of the generated signals to minimize computational load without sacrificing accuracy. The proposed ODR method was validated using experimental data. The classification results show that the proposed method generally outperforms the conventional classification method. The results support the proposed concept of using ODR signals in diagnosis procedures for journal bearing systems.