An analysis of captured industrial vehicular noise signals for ZigBee communications

This paper addresses a scheme to measure the robustness of the ZigBee protocol as deployed in industrial machinery under the influence of electromagnetic noise. The scheme is based on a multiscale signal processing to analyze the time domain characteristics of the pulsative and other noise signals. The variance fractal dimension of the captured noise signals sequence shows that these signals exhibit fractal characteristics. In particular, the starter noise burst portion of the captured signal is more correlated compared to the background noise portion in all the acquired data, and the noise burst is multifractal in time. These findings support and verify the fractal model of noise in industrial machinery.