scholarly journals A Satellite Incipient Fault Detection Method Based on Decomposed Kullback–Leibler Divergence

Entropy ◽  
2021 ◽  
Vol 23 (9) ◽  
pp. 1194
Author(s):  
Ge Zhang ◽  
Qiong Yang ◽  
Guotong Li ◽  
Jiaxing Leng ◽  
Mubiao Yan
Keyword(s):  
Time Complexity ◽  
High Sensitivity ◽  
Rayleigh Quotient ◽  
Anomalous Behavior ◽  
Local Optimum ◽  
Distribution Models ◽  
Kl Divergence ◽  
Leibler Divergence ◽  
Incipient Faults ◽  
Generalized Rayleigh Quotient

Detection of faults at the incipient stage is critical to improving the availability and continuity of satellite services. The application of a local optimum projection vector and the Kullback–Leibler (KL) divergence can improve the detection rate of incipient faults. However, this suffers from the problem of high time complexity. We propose decomposing the KL divergence in the original optimization model and applying the property of the generalized Rayleigh quotient to reduce time complexity. Additionally, we establish two distribution models for subfunctions F1(w) and F3(w) to detect the slight anomalous behavior of the mean and covariance. The effectiveness of the proposed method was verified through a numerical simulation case and a real satellite fault case. The results demonstrate the advantages of low computational complexity and high sensitivity to incipient faults.

scholarly journals A Satellite Incipient Fault Detection Method Based on Local Optimum Projection Vector and Kullback-Leibler Divergence

2021 ◽  
Vol 11 (2) ◽  
pp. 797
Author(s):  
Ge Zhang ◽  
Qiong Yang ◽  
Guotong Li ◽  
Jiaxing Leng ◽  
Long Wang
Keyword(s):  
Fault Detection ◽  
Principal Component ◽  
Local Optimum ◽  
Detection Rates ◽  
Kl Divergence ◽  
Projection Vector ◽  
Leibler Divergence ◽  
Incipient Faults ◽  
On Line ◽  
Probability Density Function Pdf

Timely and effective detection of potential incipient faults in satellites plays an important role in improving their availability and extending their service life. In this paper, the problem of detecting incipient faults using projection vector (PV) and Kullback-Leibler (KL) divergence is studied in the context of detecting incipient faults in satellites. Under the assumption that the variables obey a multidimensional Gaussian distribution and using KL divergence to detect incipient faults, this paper models the optimum PV for detecting incipient faults as an optimization problem. It proves that the PVs obtained by principal component analysis (PCA) are not necessarily the optimum PV for detecting incipient faults. It then compares the on-line probability density function (PDF) with the reference PDF for detecting incipient faults on the local optimum PV. A numerical example and a real satellite fault case were used to assess the validity and superiority of the method proposed in this paper over conventional methods. Since the method takes into account the characteristics of the actual incipient faults, it is more adaptable to various possible incipient faults. Fault detection rates of three simulated faults and the real satellite fault are 98%, 84%, 93% and 92%, respectively.

Shaped-Beam Pattern Synthesis Through the Construction of Weighted Generalized Rayleigh Quotient

2019 ◽  
Vol 28 (1) ◽  
pp. 207-214
Author(s):  
Yin Yang ◽  
Chuan Wan ◽  
Weixing Sheng ◽  
Yubing Han ◽  
Xiaofeng Ma
Keyword(s):  
Rayleigh Quotient ◽  
Beam Pattern ◽  
Pattern Synthesis ◽  
Shaped Beam ◽  
Generalized Rayleigh Quotient

scholarly journals Development of an expected possession value model to analyse team attacking performances in rugby league

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259536
Author(s):  
Thomas Sawczuk ◽  
Anna Palczewska ◽  
Ben Jones
Keyword(s):  
Markov Chains ◽  
Rugby League ◽  
Kl Divergence ◽  
Location Data ◽  
Leibler Divergence ◽  
Value Model ◽  
Super League

This study aimed to evaluate team attacking performances in rugby league via expected possession value (EPV) models. Location data from 59,233 plays in 180 Super League matches across the 2019 Super League season were used. Six EPV models were generated using arbitrary zone sizes (EPV-308 and EPV-77) or aggregated according to the total zone value generated during a match (EPV-37, EPV-19, EPV-13 and EPV-9). Attacking sets were considered as Markov Chains, allowing the value of each zone visited to be estimated based on the outcome of the possession. The Kullback-Leibler Divergence was used to evaluate the reproducibility of the value generated from each zone (the reward distribution) by teams between matches. Decreasing the number of zones improved the reproducibility of reward distributions between matches but reduced the variation in zone values. After six previous matches, the subsequent match’s zones had been visited on 95% or more occasions for EPV-19 (95±4%), EPV-13 (100±0%) and EPV-9 (100±0%). The KL Divergence values were infinity (EPV-308), 0.52±0.05 (EPV-77), 0.37±0.03 (EPV-37), 0.20±0.02 (EPV-19), 0.13±0.02 (EPV-13) and 0.10±0.02 (EPV-9). This study supports the use of EPV-19 and EPV-13, but not EPV-9 (too little variation in zone values), to evaluate team attacking performance in rugby league.

scholarly journals Performance Enhancement of the Location and Recognition of a Φ-OTDR System Using CEEMDAN-KL and AMNBP

2020 ◽  
Vol 10 (9) ◽  
pp. 3047
Author(s):  
Yanzhu Hu ◽  
Zhen Meng ◽  
Xinbo Ai ◽  
Yu Hu ◽  
Yixin Zhang ◽  
...  
Keyword(s):  
Performance Enhancement ◽  
Signal To Noise Ratio ◽  
Dead Zone ◽  
Recognition Rate ◽  
High Sensitivity ◽  
Ensemble Empirical Mode Decomposition ◽  
Time Domain Reflectometry ◽  
Long Distance ◽  
Practical Applications ◽  
Leibler Divergence

It is commonly known that for characteristics, such as long-distance, high-sensitivity, and full-scale monitoring, phase-sensitive optical time-domain reflectometry (Φ-OTDR) has developed rapidly in many fields, especially with the arrival of 5G. Nevertheless, there are still some problems obstructing the application for practical environments. First, the fading effect leads to some results falling into the dead zone, which cannot be demodulated effectively. Second, because of the high sensitivity, the Φ-OTDR system is easy to be interfered with by strong noise in practical environments. Third, the large volume of data caused by the fast responses require a lot of calculations. All the above problems hinder the performance of Φ-OTDR in practical applications. This paper proposes an integration method based on a complete ensemble empirical mode decomposition with adaptive noise and Kullback–Leibler divergence (CEEMDAN-KL) and an adaptive moving neighbor binary pattern (AMNBP) to enhance the performance of Φ-OTDR. CEEMDAN-KL improved the signal characteristics in low signal-to-noise ratio (SNR) conditions. AMNBP optimized the location and recognition via a high calculation efficiency. Experimental results show that the average recognition rate of four kinds of events reached 94.03% and the calculation efficiency increased by 20.0%, which show the excellent performance of Φ-OTDR regarding location and recognition in practical environments.

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