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Vibration-based condition monitoring (VBCM) is widely utilized in variousapplications due to its non-destructive nature. Recent advancements in sensortechnology, the Internet of Things (IoT), and computing have enabled thefacilitation of reliable distributed VBCM where sensor nodes are deployed atmultiple locations and connected wirelessly to monitoring centers. However,sensor nodes are typically constrained by limited power resources,necessitating control over the peak-to-average power ratio (PAPR) of thegenerated vibration signals. Effective control of PAPR is crucial to preventnonlinear distortion and reduce power consumption within the node.Additionally, avoiding nonlinear distortion in the vibration signal andpreserving its waveform is essential to ensure the reliability of conditionmonitoring. This paper conducts an in-depth analysis of the PAPR of vibrationsignals in VBCM systems, evaluates the impact of nonlinear power amplificationon the system performance, and proposes a lightweight autoencoder-based signalcompanding scheme to control the PAPR to improve power efficiency and mitigatethe impact of nonlinear distortion. The proposed scheme employs a lightweightreconstruction autoencoder with a compression-based activation function in thesource to compress the vibration signals and avoid increasing the average powerof the compressed signal. In the destination, the proposed scheme uses adenoising-expansion autoencoder to expand the compressed signals whileminimizing noise enhancement during the expansion process. The experimentalresults demonstrate the effectiveness of the proposed companding scheme inpreventing nonlinear distortion, improving the efficiency of poweramplification in the source, and restoring the PAPR characteristics in thedestination while avoiding the undesired effect of noise expansion.

On the Peak-to-Average Power Ratio of Vibration Signals: Analysis and Signal Companding for an Efficient Remote Vibration-Based Condition Monitoring