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

机译:接近传感器信号的全向再生(ODR),可对轴颈轴承系统进行可靠的诊断

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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.
机译:轴颈轴承转子系统的某些异常状态是方向性的(例如,摩擦,未对准)。在这些情况下,振动信号会根据传感器的方向和健康状况而变化。这使得传统诊断方法难以诊断。本文提出了一种全向再生方法,以开发一种鲁棒的转子系统诊断算法。所提出的方法可以在任意方向上产生振动信号,而无需使用额外的传感器。在这种方法中,围绕转子的整个圆周生成信号以考虑所有可能的方向。然后,通过数学证明每种状态的方向性,并使用提出的度量标准对其进行评估。当确定方向状态时,对所有生成的信号进行分类。当找到非定向状态时,仅对所生成的信号之一执行分类,以在不牺牲精度的情况下最小化计算负荷。使用实验数据验证了提出的ODR方法。分类结果表明,该方法总体上优于传统分类方法。结果支持所提出的在轴颈轴承系统的诊断过程中使用ODR信号的概念。

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