scholarly journals Safety Assessment Method of Bridge Crane Based on Cluster Analysis and Neural Network

2018 ◽  
Vol 131 ◽  
pp. 477-484 ◽  
Author(s):  
Zhiping Chen ◽  
Zhewei Li ◽  
Chaoliang Huang ◽  
Guoan Zhang ◽  
Huanwei Yu
Keyword(s):  
Neural Network ◽  
Cluster Analysis ◽  
Safety Assessment ◽  
Assessment Method ◽  
Bridge Crane

Research on Safety Comprehensive Assessment Method for Air Traffic Control Based on RBF Neural Network

2014 ◽  
Vol 989-994 ◽  
pp. 2671-2674
Author(s):  
Xu Sheng Gan ◽  
Hua Ping Li
Keyword(s):  
Neural Network ◽  
Traffic Control ◽  
Air Traffic Control ◽  
Safety Assessment ◽  
Rbf Neural Network ◽  
Assessment Method ◽  
Air Traffic ◽  
Comprehensive Assessment ◽  
Assessment Index ◽  
Assessment Index System

To assess the safety situation in air traffic control effectively, a comprehensive assessment method based on RBF neural network is proposed. At first, the safety assessment principle based on RBF neural network is introduced, and then the safety assessment index system for air traffic control is established from four aspects of human, machine, environment and management. Simulation example of ATC safety assessment gives us a satisfactory result for RBF neural network.

No-Reference Image Quality Assessment Based on Multi-Order Gradients Statistics

2020 ◽  
Vol 64 (1) ◽  
pp. 10505-1-10505-16
Author(s):  
Yin Zhang ◽  
Xuehan Bai ◽  
Junhua Yan ◽  
Yongqi Xiao ◽  
C. R. Chatwin ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Assessment Method ◽  
Image Distortion ◽  
Image Feature ◽  
Reference Image ◽  
Gradient Magnitude ◽  
Distortion Type

Abstract A new blind image quality assessment method called No-Reference Image Quality Assessment Based on Multi-Order Gradients Statistics is proposed, which is aimed at solving the problem that the existing no-reference image quality assessment methods cannot determine the type of image distortion and that the quality evaluation has poor robustness for different types of distortion. In this article, an 18-dimensional image feature vector is constructed from gradient magnitude features, relative gradient orientation features, and relative gradient magnitude features over two scales and three orders on the basis of the relationship between multi-order gradient statistics and the type and degree of image distortion. The feature matrix and distortion types of known distorted images are used to train an AdaBoost_BP neural network to determine the image distortion type; the feature matrix and subjective scores of known distorted images are used to train an AdaBoost_BP neural network to determine the image distortion degree. A series of comparative experiments were carried out using Laboratory of Image and Video Engineering (LIVE), LIVE Multiply Distorted Image Quality, Tampere Image, and Optics Remote Sensing Image databases. Experimental results show that the proposed method has high distortion type judgment accuracy and that the quality score shows good subjective consistency and robustness for all types of distortion. The performance of the proposed method is not constricted to a particular database, and the proposed method has high operational efficiency.

A Novel Safety Assessment Method based on Fault Dependent Matrix

2019 ◽  
Vol 15 (9) ◽  
pp. 2392 ◽  
Author(s):  
Dong Haiyong ◽  
Gu Qingfan ◽  
Wang Guoqing ◽  
Zhai Zhengjun ◽  
Lu Yanhong
Keyword(s):  
Safety Assessment ◽  
Assessment Method

scholarly journals Deformation Inspection and Safety Assessment Method of Buried Flexible Pipeline in Service

2021 ◽  
Vol 1043 (4) ◽  
pp. 042043
Author(s):  
Zhu Xinmin ◽  
Feng Shaokong ◽  
Huang Tao ◽  
Shang Feng ◽  
Yang Lufei
Keyword(s):  
Safety Assessment ◽  
Assessment Method

An Online Quantified Safety Assessment Method for Train Service State Based on Safety Region Estimation and Hybrid Intelligence Technologies

2015 ◽  
Vol 25 (03) ◽  
pp. 493-511
Author(s):  
Yong Qin ◽  
Shan Yu ◽  
Yuan Zhang ◽  
Limin Jia ◽  
Xiaoqing Cheng
Keyword(s):  
Safety Assessment ◽  
Safety Analysis ◽  
Assessment Method ◽  
Rolling Bearings ◽  
Safety Risk ◽  
Hybrid Intelligence ◽  
Local Mean ◽  
Interval Type ◽  
Service State

Facing the important issues of safety analysis and assessment for the train service state, an online quantified safety assessment method based on the safety region estimation and hybrid intelligence technologies was proposed in this paper. First, the previous researches on the safety analysis and assessment were briefly reviewed for the train itself and its key equipment, and the existential problems were further pointed out. Then, using the safety monitoring data and the safety region estimation theory, a new online safety assessment method with data-driven was put forward, which was followed by a detailed description of the concrete implementation steps including the EMD (Local Mean Decomposition) and EM (Energy Moment) based safety risk evaluation index selection, Interval Type 2 Fuzzy C-Means (IT2FCM) clustering based safety region boundary calculation modeling and safety risk grading. Finally, in order to verify its performance through experiments, the above method was applied in analyzing and evaluating service states of the rolling bearings, the key equipment of the train, on the basis of mass field data. The experimental results indicate that this method is valid.

Mathematical Approaches in Functional Safety Assessment for E/E/PE Safety-Related Software

2021 ◽  
pp. 2150043
Author(s):  
Shinji Inoue ◽  
Takaji Fujiwara ◽  
Shigeru Yamada
Keyword(s):  
Software Reliability ◽  
Safety Assessment ◽  
Assessment Method ◽  
Functional Safety ◽  
Reliability Modeling ◽  
Software Failure ◽  
Safety Integrity Level ◽  
Iec 61508 ◽  
Systematic Failure ◽  
Quantitative Safety Assessment

Safety integrity level (SIL)-based functional safety assessment is widely required in designing safety functions and checking their validity of electrical/electronic/programmable electronic (E/E/PE) safety-related systems after being issued IEC 61508 in 2010. For the hardware of E/E/PE safety-related systems, quantitative functional safety assessment based on target failure measures is needed for deciding or allocating the level of SIL. On the other hand, IEC 61508 does not provide any quantitative safety assessment method for allocating SIL for the software of E/E/PE safety-related systems because the software failure is treated as a systematic failure in IEC 61508. We discuss the needfulness of quantitative safety assessment for software of E/E/PE safety-related systems and propose mathematical fundamentals for conducting quantitative SIL-based safety assessment for the software of E/E/PE safety-related systems by applying the notion of software reliability modeling and assessment technologies. We show numerical examples for explaining how to use our approaches.

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