An Evaluation Method of Underwater Ocean Environment Safety Situation Based on D-S Evidence Theory

Zhao, Yuxin; Jia, Renfeng; Liu, Chang

doi:10.1155/2015/207656

Cited by 6 publications

(3 citation statements)

References 22 publications

(20 reference statements)

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“…According to the evidence theory, the sum of the basic probability assignment functions of the fused signal, given the symbol A F ( n ) , is equal to 1. 43 The A F ( n ) is convoluted by equation (1) and the sum of the convolution result is expressed in equation (2).…”

Section: The Ipre Methodsmentioning

confidence: 99%

Thruster fault identification using improved peak region energy and multiple model least square support vector data description for autonomous underwater vehicle

Yin

Zhang

Zhou

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part O:

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This article investigates a novel fault identification approach to determine the percentage of the thrust loss for autonomous underwater vehicle thrusters. The novel approach is developed from a combination of the peak region energy (PRE) and support vector data description (SVDD) by considering that PRE is able to acquire a primary feature in low dimensions from signals without any secondary process and that SVDD can establish a hypersphere boundary for a class of fault samples even in the case of a small number of training samples. Three improvements, namely removing the fusion, an energy leakage and a homomorphic transform are applied to the PRE. It forms an improved PRE to increase the area under the curve. Furthermore, another three new contents, namely the least square, a multiple model fusion and a dead zone are added to the SVDD. It constructs a multiple model least square SVDD to increase the overall identification accuracy. Experiments are performed on an experimental prototype autonomous underwater vehicle in a pool. The experimental results indicate the effectiveness of the proposed method.

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Section: The Ipre Methodsmentioning

confidence: 99%

Thruster fault identification using improved peak region energy and multiple model least square support vector data description for autonomous underwater vehicle

Yin

Zhang

Zhou

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…D-S evidence theory introduces the probability distribution function, confidence function and likelihood function, lessening the reliance on traditional probability theory's prerequisites of prior probabilities, conditional probability and unified identification framework. The D-S evidence theory has wide application in fault detection [29] as well as in safety evaluation for the ocean environment [30] and the cloud platform [31]. In the field of hydraulic engineering, Chen et al [32] enhanced the evidence distance measure method in D-S evidence theory by utilizing the belief Wasserstein-1 distance (BWD) and applied it to dam health diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Vibration Prediction and Evaluation System of the Pumping Station Based on ARIMA–ANFIS–WOA Hybrid Model and D-S Evidence Theory

Wang

Zhang

Yin

2023

Water

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Research on the vibration response prediction and safety early warning is of great significance to the operation and management of pumping station engineering. In the current research, a hybrid prediction method was proposed to predict vibration responses of the pumping station based on a single model of autoregressive integrated moving average (ARIMA), a combined model of the adaptive network-based fuzzy inference system (ANFIS) and whale optimization algorithm (WOA). The performance of the developed models was studied based on the effective stress vibration data of the blades in a shaft tubular pumping station. Then, the D-S evidence theory was adopted to perform safety early warning of the operation state by integrating the displacement, velocity, acceleration and stress indicators of the vibration responses of the pumping station. The research results show that the proposed prediction model ARIMA–ANFIS–WOA exhibited better accuracy in obtaining both linear and nonlinear characteristics of vibration data than the single prediction model and hybrid model with different optimization algorithms. The D-S evidence fusion results quantitatively demonstrate the safe operation state of the pumping station. This research could provide a scientific basis for the real-time analysis and processing of data in pumping station operation and maintenance systems.

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“…As a method of uncertainty reasoning, Dempster-Shafer (D-S) evidence theory [1,2] can model and reason in uncertain problems and realize the fusion of no a priori information, and has been widely used in target recognition tracking , fault diagnosis, network security assessment and other areas [3][4][5][6][7][8][9]. However, when the evidence is highly conflicting, the results of the fusion of evidence often appear contrary to the facts.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Method to Measure Evidence Conflict

Liu¹,

Yang²,

Wu³

et al. 2017

Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)

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Abstract-Dempster Shafer evidence theory, as an uncertain information fusion technology, is widely used in various fields of information fusion. However, when there is a highly conflict between two pieces of evidence, counterintuitive results are obtained by classical Dempster's combination rule. Therefore, it is very important to measure the conflict between two pieces of evidence. Based on the analysis of some typical conflict measurement methods, a new model to represent conflict was constructed with the Euclidean distance function and the Jaccard similarity coefficient. Some numerical examples illustrate that the proposed method can measure the degree of conflict between the two pieces of evidence and overcome the shortcomings of the classical conflictive coefficient, Jousselme evidence distance and Pignistic probability distance to a certain extent.

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An Evaluation Method of Underwater Ocean Environment Safety Situation Based on D-S Evidence Theory

Cited by 6 publications

References 22 publications

Thruster fault identification using improved peak region energy and multiple model least square support vector data description for autonomous underwater vehicle

Thruster fault identification using improved peak region energy and multiple model least square support vector data description for autonomous underwater vehicle

Vibration Prediction and Evaluation System of the Pumping Station Based on ARIMA–ANFIS–WOA Hybrid Model and D-S Evidence Theory

An Efficient Method to Measure Evidence Conflict

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