Linear Axis Guide Rail Misalignment Detection and Localization Using a Novel Signal Segmentation Analysis Technique

Abstract

Maintenance of the linear axis and its components such as the linear guide can be significantly costly due to the difficult nature of the repair procedure and the downtime the machine exhibits while being repaired. This is a decision that must be made carefully and with proper justification. Therefore, it is crucial that the condition-based monitoring (CBM) system in the machine can detect and localize faults in the linear axis. The presented paper proposes a novel vibration signal segmentation analysis technique that detects and localizes misalignment in the linear guide rail, which is considered a leading root-cause failure fault. The results demonstrated that the usability of time domain features such as RMS was doubled by applying segmentation analysis. Also, evaluating both stroke directions aided in the localization of the misalignment. Overall, the practical value of the proposed technique is to function as both a localization and repair verification tool when performing linear axis maintenance.