Multi-sources information fusion analysis of water inrush disaster in tunnels based on improved theory of evidence

2021 ◽  
Vol 113 ◽  
pp. 103948
Author(s):  
Shucai Li ◽  
Cong Liu ◽  
Zongqing Zhou ◽  
Liping Li ◽  
Shaoshuai Shi ◽  
...  
Keyword(s):  
Information Fusion ◽  
Water Inrush ◽  
Fusion Analysis ◽  
Theory Of Evidence

scholarly journals Multisource Information Risk Evaluation Technology of Mine Water Inrush Based on VWM: A Case Study of Weng’an Coal Mine

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Bo Li ◽  
Tao Li ◽  
Wenping Zhang ◽  
Zijie Liu ◽  
Lei Yang
Keyword(s):  
Information Fusion ◽  
Mine Water ◽  
Evaluation Method ◽  
Evaluation Model ◽  
Water Inrush ◽  
Fusion Technology ◽  
Control Effect ◽  
Constant Weight ◽  
Variable Weight ◽  
Weight Model

The use of multisource information fusion technology to predict the risk of water inrush from coal floor is a research hotspot in recent years, but the current evaluation method is mainly based on a constant weight evaluation model. Using constant weights to reflect the control effect of changing factor state values on water inrush evaluation has obvious limitations, and it is unable to describe the control effect of the hydrogeological condition mutation on the water inrush from the floor. In order to solve the above problems, this manuscript introduces the idea of variable weight into the field of water inrush evaluation, expounds on the significance of variable weight theory for water inrush evaluation, analyzes the characteristics of mine water inrush variable weight evaluation, and, on this basis, further combines GIS-based multisource information fusion technology and typical engineering case to compare with the evaluation effect map, evaluation unit, and comprehensive evaluation values. The differences between the variable weight model (VWM) and the constant weight model (CWM) are analyzed, which proves that the evaluation process of the variable weight evaluation model is more reasonable and can effectively improve the evaluation accuracy.

scholarly journals Data Analysis of Magnetic Flux Leakage Detection Based on Multi-Source Information Fusion

2020 ◽  
Author(s):  
Weilin Shao ◽  
Ming Sun ◽  
Yilai Ma ◽  
Jinzhong Chen ◽  
Xiaowei Kang ◽  
...  
Keyword(s):  
Data Analysis ◽  
Magnetic Flux ◽  
Information Fusion ◽  
Information Source ◽  
Magnetic Flux Leakage ◽  
Leakage Detection ◽  
Source Information ◽  
Source Data ◽  
Fusion Analysis ◽  
Flux Leakage

For the analysis of the magnetic flux leakage detection data in pipelines, a single information source data analysis method is used to determine the pipeline characteristics with uncertainty. A multi-source information fusion data analysis technology is proposed. This paper makes full use of the information collected by the multi-source sensors of the magnetic leakage internal detector, and adopts distributed and centralized multi-source information fusion analysis technology. First, pre-analyze and judge the information data of the auxiliary sensors (speed, pressure, temperature) of the internal magnetic flux leakage detector. Then, the data of the main sensor, ID / OD sensor, axial mileage sensor, and circumferential clock sensor of the magnetic flux leakage detector are analyzed separately. Finally, the RBF neural network + least squares support vector machine (LSSVM)fusion analysis technology is adopted to realize the fusion analysis of multi-source information. The results show that this method can effectively improve the quality and reliability of data analysis compared with traditional single information source data analysis.

Information Fusion of the Vibration and Acoustic Signals Based Rolling Bearing Incipient Fault Diagnosis Method

2013 ◽  
Vol 774-776 ◽  
pp. 1499-1502
Author(s):  
Ting Feng Ming ◽  
Yong Xiang Zhang ◽  
Jing Li
Keyword(s):  
Fault Diagnosis ◽  
Correlation Analysis ◽  
Information Fusion ◽  
Vibration Signal ◽  
Acoustic Resonance ◽  
Rolling Bearing ◽  
Rolling Bearings ◽  
Diagnosis Method ◽  
Incipient Fault ◽  
Fusion Analysis

The feature of correlation analysis were described and applied to analyzing the vibration signal of the gearbox. Aiming to that the diagnosis effect of the rolling bearings incipient fault was not good through the vibration spectrum and the resonance demodulation spectrum directly, the information fusion technology based on the correlation analysis is proposed to processing the vibration and acoustic resonance demodulation signal. The experimental results show that the presented correlation fusion analysis technology can be as the basis of the effective fault diagnosis method for the rolling bearings incipient defect.

scholarly journals Temporal and Causal Relations on Evidence Theory: an Application on Adverse Drug Reactions

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Luiz Alberto Pereira Afonso Ribeiro ◽  
Ana Cristina Bicharra Garcia ◽  
Paulo Sérgio Medeiros Dos Santos
Keyword(s):  
Information Fusion ◽  
Evidence Theory ◽  
Mass Function ◽  
Data Sources ◽  
Drug Reactions ◽  
Clinical Notes ◽  
Dempster Shafer Theory ◽  
Multisensor Information Fusion ◽  
Shafer Theory ◽  
Theory Of Evidence

The use of big data and information fusion in electronichealth records (EHR) allowed the identification of adversedrug reactions(ADR) through the integration of heteroge-neous sources such as clinical notes (CN), medication pre-scriptions, and pathological examinations. This heterogene-ity of data sources entails the need to address redundancy,conflict, and uncertainty caused by the high dimensionalitypresent in EHR. The use of multisensor information fusion(MSIF) presents an ideal scenario to deal with uncertainty,especially when adding resources of the theory of evidence,also called Dempster–Shafer Theory (DST). In that scenariothere is a challenge which is to specify the attribution of be-lief through the mass function, from the datasets, named basicprobability assignment (BPA). The objective of the presentwork is to create a form of BPA generation using analy-sis of data regarding causal and time relationships betweensources, entities and sensors, not only through correlation, butby causal inference.

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