Grid Fault Diagnosis Based on Information Entropy and Multi-source Information Fusion

In order to solve the problem of misjudgment caused by the traditional power grid fault diagnosis methods, a new fusion diagnosis method is proposed based on the theory of multi-source information fusion. In this method, the fault degree of the power element is deduced by using the Bayesian network. Then, the time-domain singular spectrum entropy, frequency-domain power spectrum entropy and wavelet packet energy spectrum entropy of the electrical signals of each circuit after the failure are extracted, and these three characteristic quantities are taken as the fault support degree of the power components. Finally, the four fault degrees are normalized and classified as four evidence bodies in the D-S evidence theory for multi-feature fusion, which reduces the uncertainty brought by a single feature body. Simulation results show that the proposed method can obtain more reliable diagnosis results compared with the traditional methods

Grid Fault Diagnosis Based on Information Entropy and Multi-source Information Fusion

In order to solve the problem of misjudgment caused by the traditional power grid fault diagnosis methods, a new fusion diagnosis method is proposed based on the theory of multi-source information fusion. In this method, the fault degree of the power element is deduced by using the Bayesian network. Then, the time-domain singular spectrum entropy, frequency-domain power spectrum entropy and wavelet packet energy spectrum entropy of the electrical signals of each circuit after the failure are extracted, and these three characteristic quantities are taken as the fault support degree of the power components. Finally, the four fault degrees are normalized and classified as four evidence bodies in the D-S evidence theory for multi-feature fusion, which reduces the uncertainty brought by a single feature body. Simulation results show that the proposed method can obtain more reliable diagnosis results compared with the traditional methods

Two Optimization Ways of DDR3 Transmission Line Equal-Length Wiring Based on Signal Integrity

As we enter the 5G (5th-Generation) era, the amount of information and data has become increasingly tremendous. Therefore, electronic circuits need to have higher chip density, faster operating speed and better signal quality of transmission. As the carrier of electronic components, the design difficulty of high-speed PCB (Printed Circuit Board) is also increasing. Equal-length wiring is an essential part of PCB design. But now, it can no longer meet the needs of designers. Accordingly, in view of the shortcomings of the traditional equal-length wiring, this article proposes two optimization ways: the "spiral wiring" way and the "double spiral wiring" way. Based on the theoretical analysis of the transmission lines, the two optimization ways take the three aspects of optimizing the layout and wiring space, suppressing crosstalk and reducing reflection as the main points to optimize the design. Eventually, this article performs simulation and verification of schematic diagram and PCB of the optimal design by using HyperLynx simulation software. The simulation results show that these two ways not only improve the flexibility of the transmission line layout, but also improve the signal integrity of the transmission lines. Of course, this also proves the feasibility and reliability of the two optimized designs

Two Optimization Ways of DDR3 Transmission Line Equal-Length Wiring Based on Signal Integrity

As we enter the 5G (5th-Generation) era, the amount of information and data has become increasingly tremendous. Therefore, electronic circuits need to have higher chip density, faster operating speed and better signal quality of transmission. As the carrier of electronic components, the design difficulty of high-speed PCB (Printed Circuit Board) is also increasing. Equal-length wiring is an essential part of PCB design. But now, it can no longer meet the needs of designers. Accordingly, in view of the shortcomings of the traditional equal-length wiring, this article proposes two optimization ways: the "spiral wiring" way and the "double spiral wiring" way. Based on the theoretical analysis of the transmission lines, the two optimization ways take the three aspects of optimizing the layout and wiring space, suppressing crosstalk and reducing reflection as the main points to optimize the design. Eventually, this article performs simulation and verification of schematic diagram and PCB of the optimal design by using HyperLynx simulation software. The simulation results show that these two ways not only improve the flexibility of the transmission line layout, but also improve the signal integrity of the transmission lines. Of course, this also proves the feasibility and reliability of the two optimized designs

An Enhanced IEEE1588 Clock Synchronization for Link Delays Based on a System-on-Chip Platform

The clock synchronization is considered as a key technology in the time-sensitive networking (TSN) of 5G fronthaul. This paper proposes a clock synchronization enhancement method to optimize the link delays, in order to improve synchronization accuracy. First, all the synchronization dates are filtered twice to get the good calculation results in the processor, and then FPGA adjust the timer on the slave side to complete clock synchronization. This method is implemented by Xilinx Zynq UltraScale+ MPSoC (multiprocessor system-on-chip), using FPGA+ARM software and hardware co-design platform. The master and slave output Pulse Per-Second (PPS) signals. The synchronization accuracy was evaluated by measuring the time offset between PPS signals. Contraposing the TSN, this paper compares the performance of the proposed scheme with some previous methods to show the efficacy of the proposed work. The results show that the slave clock of proposed method is synchronized with the master clock, leading to better robustness and significant improvement in accuracy, with time offset within the range of 40 nanoseconds. This method can be applied to the time synchronization of the 5G open fronthaul network and meets some special service needs in 5G communication

An Enhanced IEEE1588 Clock Synchronization for Link Delays Based on a System-on-Chip Platform

The clock synchronization is considered as a key technology in the time-sensitive networking (TSN) of 5G fronthaul. This paper proposes a clock synchronization enhancement method to optimize the link delays, in order to improve synchronization accuracy. First, all the synchronization dates are filtered twice to get the good calculation results in the processor, and then FPGA adjust the timer on the slave side to complete clock synchronization. This method is implemented by Xilinx Zynq UltraScale+ MPSoC (multiprocessor system-on-chip), using FPGA+ARM software and hardware co-design platform. The master and slave output Pulse Per-Second (PPS) signals. The synchronization accuracy was evaluated by measuring the time offset between PPS signals. Contraposing the TSN, this paper compares the performance of the proposed scheme with some previous methods to show the efficacy of the proposed work. The results show that the slave clock of proposed method is synchronized with the master clock, leading to better robustness and significant improvement in accuracy, with time offset within the range of 40 nanoseconds. This method can be applied to the time synchronization of the 5G open fronthaul network and meets some special service needs in 5G communication

Protective effect of vanillin in streptozotocin-induced diabetes in neonatal rats via attenuation of oxidative stress and inflammation

Purpose: To evaluate the antidiabetic activity of vanillin in streptozotocin (STZ)-induced diabetic rats.Methods: Diabetes was induced in 2-day old male pups by intraperitoneal (i.p.) administration of STZ (90 mg/kg). The pups were then randomly assigned to four groups: control group which received citrate buffer only in place of STZ; negative control group, i.e., diabetic group; and vanillin-treated groups which received vanillin (100 or 200 mg/kg, p.o.) continuously from the 6th week of age to the 10th week. The antidiabetic effect of vanillin was determined by measuring the serum levels of insulin, triglycerides and glucose in the diabetic rats. Oral glucose tolerance, kidney and liver function tests were also performed at the end of the protocol. Moreover, the oxidative stress and inflammatory cytokines in liver tissues, and histopathological changes in pancreatic tissues were assessed.Results: Vanillin treatment significantly decreased serum glucose and triglyceride levels and increased the level of insulin, when compared to the negative control group. There was higher insulin sensitivity in the vanillin-treated group than in the negative control group. In addition, vanillin improved liver and renal functions in STZ-induced diabetic neonatal rats. Hepatic oxidative stress and inflammatory mediators, as well as histopathological changes in pancreas were attenuated by vanillin treatment.Conclusion: These results reveal that vanillin attenuates hyperglycemia in STZ-induced neonatal diabetic rat model by decreasing oxidative stress and inflammatory cytokines. There, further studies are required to develop the anti-diabetic potentials of vanillin for clinical applications.Keywords: Vanillin, Streptozotocin, Diabetes, Oxidative stress, Insulin, Neonata

Adaptive Policy with Wait-kk Model for Simultaneous Translation

Simultaneous machine translation (SiMT) requires a robust read/write policy in conjunction with a high-quality translation model. Traditional methods rely on either a fixed wait-$k$ policy coupled with a standalone wait-$k$ translation model, or an adaptive policy jointly trained with the translation model. In this study, we propose a more flexible approach by decoupling the adaptive policy model from the translation model. Our motivation stems from the observation that a standalone multi-path wait-$k$ model performs competitively with adaptive policies utilized in state-of-the-art SiMT approaches. Specifically, we introduce DaP, a divergence-based adaptive policy, that makes read/write decisions for any translation model based on the potential divergence in translation distributions resulting from future information. DaP extends a frozen wait-$k$ model with lightweight parameters, and is both memory and computation efficient. Experimental results across various benchmarks demonstrate that our approach offers an improved trade-off between translation accuracy and latency, outperforming strong baselines.Comment: Accept to EMNLP 2023 main conference. 17 pages, 12 figures, 5 table

A Novel Blind Source Separation Algorithm and Performance Analysis of Weak Signal against Strong Interference in Passive Radar Systems

In Passive Radar System, obtaining the mixed weak object signal against the super power signal (jamming) is still a challenging task. In this paper, a novel framework based on Passive Radar System is designed for weak object signal separation. Firstly, we propose an Interference Cancellation algorithm (IC-algorithm) to extract the mixed weak object signals from the strong jamming. Then, an improved FastICA algorithm with K-means cluster is designed to separate each weak signal from the mixed weak object signals. At last, we discuss the performance of the proposed method and verify the novel method based on several simulations. The experimental results demonstrate the effectiveness of the proposed method

Minimum BER Criterion Based Robust Blind Separation for MIMO Systems

In this paper, a robust blind source separation (BSS) algorithm is investigated based on a new cost function for noise suppression. This new cost function is established according to the criterion of minimum bit error rate (BER) incorporated into maximum likelihood (ML) principle based independent component analysis (ICA). With the help of natural gradient search, the blind separation work is carried out through optimizing this constructed cost function. Simulation results and analysis corroborate that the proposed blind separation algorithm can realize better performance in speed of convergence and separation accuracy as opposed to the conventional ML-based BSS