scholarly journals Leakage Detection of CFRDs Based on a Multi-source Information Fusion Method

2020 ◽  
Vol 510 ◽  
pp. 052055
Author(s):  
Jinzhang Tian ◽  
Dashui Gao ◽  
Yi Xu ◽  
Yantao Zhu ◽  
Lixian Huang
Keyword(s):  
Information Fusion ◽  
Fusion Method ◽  
Leakage Detection ◽  
Source Information

Research on Evaluation of Vehicle Dangerous Traveling State Based on Information Fusion Method

2013 ◽  
Vol 791-793 ◽  
pp. 1018-1022
Author(s):  
Peng Wang ◽  
Zhi Qiang Liu
Keyword(s):  
Information Fusion ◽  
Evaluation System ◽  
Evidence Theory ◽  
Recognition System ◽  
Fusion Method ◽  
Source Information ◽  
State Recognition ◽  
Research On Evaluation ◽  
Lane Departure ◽  
Level Information

An evaluation system of vehicle traveling state was proposed,and an unsafe vehicle traveling state recognition system was established using multi-level information fusion method. In view of the effects of the complexity of the driving environment, a variety of working conditions and the diversity of vehicle traveling characteristics, combing BP neural network with Dempster-Shafer evidence theory technique, the multi-information decision-level fusion was proposed to estimate the different kind model of the vehicle status. To verify the proposed strategies,the vehicle traveling posture evaluation system was established. The lane departure parameters and the relative distance parameters were studied in order to get the characterization of the vehicle traveling status information. The simulation results indicate that the adaptability and accuracy and the intelligence level of driving characterization estimation are significantly improved by using the pattern classification and decision technology of multi-source information fusion.

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.

Multi-Source Information Fusion Based on Kalman Filtering

2015 ◽  
Vol 727-728 ◽  
pp. 863-866
Author(s):  
Meng Meng Zhou ◽  
G.M. Gao ◽  
Hong Bo Yang
Keyword(s):  
Kalman Filtering ◽  
Information Fusion ◽  
Attitude Determination ◽  
Low Frequency ◽  
Fusion Method ◽  
Source Information ◽  
Satellite Platform ◽  
Pointing Accuracy ◽  
Micro Vibration ◽  
Better Than

Thehigh-frequency angular micro-vibration on satellite platform results in theoptical axis pointing decreasing accuracy. The Kalman filtering based on attitudeinformation fusion method is presented to solve this case and improve the pointing accuracy of attitude determination. Thesimulation results indicate that the estimated accuracy of Kalman filteringattitude information fusion method is better than the result only fromconventional low frequency sensor. Accordingly, the attitude information fusionmethod is verified and accuracy.

scholarly journals Latent Leakage Fault Identification and Diagnosis Based on Multi-Source Information Fusion Method for Key Pneumatic Units in Chinese Standard Electric Multiple Units (EMU) Braking System

2019 ◽  
Vol 9 (2) ◽  
pp. 300
Author(s):  
Jianyong Zuo ◽  
Jingxian Ding ◽  
Furen Feng
Keyword(s):  
Support Vector Machine ◽  
Information Fusion ◽  
Small Sample ◽  
Support Vector ◽  
Ratio Test ◽  
Fusion Method ◽  
Source Information ◽  
Braking System ◽  
Chinese Standard ◽  
Multiple Units

To identify and diagnose the latent leakage faults of key pneumatic units in the Chinese standard Electric Multiple Units (EMU) braking system, a multi-source information fusion method based on Kalman filtering, sequential probability ratio test (SPRT), and support vector machine (SVM) is proposed. The relay valve is taken as an example for research. Firstly, Kalman's state estimation function is used to obtain the innovation sequence, and the innovation sequence is input into the SPRT model to help recognize latent leakage faults of the relay valve. Using this method, the problem of the incomplete training set of the traditional SPRT method due to the change of the braking level and the vehicle load is solved. Secondly, the eight time-domain parameters of the relay valve input and the output pressure signal are extracted as fault characteristics, and then input to the support vector machine to realize the internal and external leakage fault diagnosis of the relay valve, which provides a reference for maintenance. Finally, this method is verified by the fault simulation data by quickly identifying latent leakage faults and diagnosing the internal and external leakage at a fault recognition rate of 100% by SVM under small sample conditions.

Multi-source Information Fusion Method Based on Anisotropic Bivariate Shrinkage

2013 ◽  
Vol 13 (1) ◽  
pp. 126-132 ◽  
Author(s):  
Xiaoxia Wang ◽  
Fengbao Yang ◽  
Hong Wei ◽  
Linna Ji ◽  
Dongmei Shi
Keyword(s):  
Information Fusion ◽  
Fusion Method ◽  
Source Information ◽  
Bivariate Shrinkage

Fault Classification of Hydroelectric Generating Unit Based on Improved Evidence Theory

2014 ◽  
Vol 7 (1) ◽  
pp. 78-83 ◽  
Author(s):  
Jiatang Cheng ◽  
Li Ai ◽  
Zhimei Duan ◽  
Yan Xiong
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Evidence Theory ◽  
Fault Classification ◽  
Fusion Method ◽  
Inconsistent Result ◽  
High Conflict

Aiming at the problem of the conventional vibration fault diagnosis technology with inconsistent result of a hydroelectric generating unit, an information fusion method was proposed based on the improved evidence theory. In this algorithm, the original evidence was amended by the credibility factor, and then the synthesis rule of standard evidence theory was utilized to carry out information fusion. The results show that the proposed method can obtain any definitive conclusion even if there is high conflict evidence in the synthesis evidence process, and may avoid the divergent phenomenon when the consistent evidence is fused, and is suitable for the fault classification of hydroelectric generating unit.

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