Pre-filtered and post-filtered 1-bit delta sigma modulator for fronthaul downlinks

Xie, Xiaoran; Zhang, Xiupu

doi:10.1016/j.optcom.2022.127908

Cited by 4 publications

(1 citation statement)

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“…There are many traditional filtering methods, including classical low-pass, high-pass, and band-pass filters, as well as empirical modal decomposition and variational modal decomposition [20,21]. All of these methods can denoise signals to a certain extent, but at the same time, there are some drawbacks which may lead to the loss of detailed information on the signals, produce serious modal aliasing phenomena, and only have a better denoising effect on specific types of signals [22][23][24]. Combining low-pass filtering and sparse-based denoising results in better denoising [25].…”

Section: Introductionmentioning

confidence: 99%

Signal Spectrum Analysis of Sediment Water Impact of Hydraulic Turbine Based on ICEEMDAN-Wavelet Threshold Denoising Strategy

Bai,

Zeng,

Dao

et al. 2023

Water

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Studies show that sediment erosion is one of the main factors attributing to hydraulic turbine failure. The present paper represents an investigation into acoustic vibration signals generated by the water flow impacting the hydraulic turbine runner under three different operating conditions. Collected signals were denoised using the ICEEMDAN-wavelet threshold method, and then the spectral characteristics and sample entropy characteristics of the signals for the three operating conditions were analyzed. The results show that when clean water flows through the hydraulic turbine, the sample entropy reaches its smallest values and the dominant frequency component in the spectrogram is 59.39 Hz. When transitioning from clean water to the flood flow containing 2–4 mm sediment particles, the sample entropy is increasing and a high-frequency component higher than 59.39 Hz becomes the prominent frequency of the spectrogram. Meanwhile, the formation of high-frequency components increases with the sand-containing particle size. Based on the spectral characteristics and sample entropy characteristics of the acoustic vibration signals under different operating conditions, it can provide a reference for the sand avoidance operation of the hydraulic turbine during flood season. In addition, it provides a supplement to the existing hydraulic turbine condition’s monitoring systems and a new avenue for subsequent research on early warning of hydraulic turbine failure.

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