Measurements and statistical analyses of electromagnetic noise for industrial wireless communications. Issue 3 (21st December 2020)

• Record Type: Journal Article
• Authors: Zhang, Jiachi; Liu, Liu; Wang, Kai; Fan, Yuanyuan; Qiu, Jiahui
• Is Part Of: International journal of intelligent systems. Volume 36:Issue 3(2021)
• Page Start: 1304
• Page End: 1330
• Publication Date: 2020-12-21
• Subjects: frequency shadow effect -- industrial electromagnetic noise -- Markov model -- statistical distribution -- time‐frequency‐domain characterization; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; 006.3
• DOI: 10.1002/int.22343
• Languages: English
• ISSNs: 0884-8173

Abstract

Abstract: In this paper, we performed a series of measurement campaigns on the wireless electromagnetic noise for two typical industrial welding scenarios. On this basis, we investigate the characterization of the impulsive noise mainly from two aspects, that is, frequency and time domains. To start with, a novel denoising method based on the dynamic threshold is proposed to identify the desirable impulse noise from the background noise. Then, in the frequency domain, we focus on the power distribution of impulsive noise at different frequency bands. Results exhibit a shadow effect with regard to different frequency bands and we characterize it by using a linear function with a Gaussian distribution. Besides, analyses on the power spectrum correlation for different polarization modes and scenarios are also provided. In the time domain, we performed a series of statistical analyses from aspects of pulse amplitude, duration, and elapse interval to characterize the impulsive noise. Furthermore, three empirical distributions are employed to depict the parameters' variation tendency, that is, Cauchy distribution for amplitude, Gamma distribution for pulse duration, and exponential distribution for pulse interval. Finally, a first‐order two‐states Markov method is proposed to model the industrial noise. Simulation results are proved to be consistent with the actual measured results in terms of the amplitude distribution.