Online fault detection and diagnosis of rotating machinery requires a number of transducers that can be significantly expensive for industrial processes. The sensitivity of various transducers and their appropriate positioning are dependent on different types of fault conditions. It is critical to formulate a method to systematically determine the effectiveness of transducer locations for monitoring the condition of a machine. In this article, number of independent sources analysis is used as an effective tool for reducing the number of vibration sources within the system, which is then followed by principal component analysis to identify the incoherent transducers to be employed for fault detection. This experiment is conducted on a machine fault simulator for unbalanced rotor, misaligned shaft, and cracked shaft. The validation of the proposed selection process is illustrated using spectral analysis for each defect.
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