Application and Evaluation of Image-based Information Acquisition in Railway Transportation

Song, Haifeng; Song, Xiying; Dong, Hailiang

doi:10.1007/s10846-022-01652-x

Cited by 5 publications

(3 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Manual monitoring requires labor costs and cannot avoid observation errors caused by long-term continuous work. Therefore, camera equipment can be used to capture pantograph images, and computer vision technology intelligent recognition technology can be introduced to achieve automated and intelligent monitoring of abnormal pantograph conditions (Song, Wang, & Ren, 2023). In the field of computer vision image recognition, VGG (Karen & Andrew, 2014) is a mainstream convolutional neural network model.…”

Section: Operation Monitoringmentioning

confidence: 99%

Research and design of an expert diagnosis system for rail vehicle driven by data mechanism models

Li,

Wang,

Xiao

2024

View full text Add to dashboard Cite

PurposeThe aim of this work is to research and design an expert diagnosis system for rail vehicle driven by data mechanism models.Design/methodology/approachThe expert diagnosis system utilizes statistical and deep learning methods to model the real-time status and historical data features of rail vehicle. Based on data mechanism models, it predicts the lifespan of key components, evaluates the health status of the vehicle and achieves intelligent monitoring and diagnosis of rail vehicle.FindingsThe actual operation effect of this system shows that it has improved the intelligent level of the rail vehicle monitoring system, which helps operators to monitor the operation of vehicle online, predict potential risks and faults of vehicle and ensure the smooth and safe operation of vehicle.Originality/valueThis system improves the efficiency of rail vehicle operation, scheduling and maintenance through intelligent monitoring and diagnosis of rail vehicle.

show abstract

Section: Operation Monitoringmentioning

confidence: 99%

Research and design of an expert diagnosis system for rail vehicle driven by data mechanism models

Li,

Wang,

Xiao

2024

View full text Add to dashboard Cite

show abstract

“…In signal processing, the IKF algorithm is used for image processing, audio processing, and radar processing. In finance, the IKF algorithm is used for portfolio optimization, risk management, and asset pricing [25].…”

Section: Insensitive Kalman Filter Algorithmmentioning

confidence: 99%

Application of Adaptive UKF Algorithm in Multi-target Tracking and Positioning System

Liu

2023

J. Appl. Data Sci.

View full text Add to dashboard Cite

Adaptive filtering algorithms are widely used in various fields, such as signal processing, control engineering, and communication systems. The Finite Impulse Response (FIR) adaptive filtering algorithm is a design method used for adaptive variable target tracking systems based on a probability density distribution model. The main goal of the FIR adaptive filtering algorithm is to track the movement of a target within a global range. To achieve this, the algorithm estimates the parameters of different regions in the image. By doing so, the algorithm can adaptively adjust its parameters to cope with the changes in the target's movement pattern. This adaptive behavior improves the algorithm's real-time performance and effectiveness in tracking the target. The FIR adaptive filtering algorithm operates by taking input signals and applying a linear filter to them. The filter coefficients are adjusted continuously in response to changes in the target's movement. This adjustment is done by minimizing the error between the estimated target position and the actual position. As the target moves, the algorithm updates its estimate and adjusts its parameters accordingly. The FIR adaptive filtering algorithm is based on a probability density distribution model. This model assumes that the input signal is a random process with an unknown probability density function. The algorithm estimates this probability density function and uses it to adjust its filter coefficients. Overall, the FIR adaptive filtering algorithm is an effective method for tracking variable targets in real-time. Its adaptive nature allows it to adjust to changes in the target's movement, making it useful in a variety of applications where tracking moving objects is necessary.

show abstract

“…Artificial neuron structureArtificial neural networks are formed by connecting artificial neurons and other neurons. According to the different connection methods, neural networks are divided into feedforward neural networks and feedback neural networks[23]-[25]. Feedforward neural networks are currently widely used.…”

mentioning

confidence: 99%

Design and Realization of Computer Image Intelligent Recognition System

2023

J. Appl. Data Sci.

View full text Add to dashboard Cite

The use of intelligent image recognition technology is rapidly expanding in various aspects of life. This technology has found significant applications in the fields of computer and multimedia. With the increasing demand for information processing, the research of machine vision systems has become more mature. This article aims to provide an in-depth analysis of the fundamental concepts of digital images based on computer technology. It covers the basic knowledge of digital images, including their characteristics, types, and properties. Additionally, the article explains the fundamental concepts of image filtering, which involves the manipulation of images to enhance their quality or extract specific information. Furthermore, this article discusses the image recognition algorithms that form the backbone of intelligent image recognition systems. These algorithms involve the use of mathematical models and techniques to identify and classify objects and patterns in digital images. Finally, the article explores the design and implementation of computer image intelligent recognition systems. This involves combining various techniques such as image acquisition, image processing, feature extraction, and classification to develop a robust and efficient recognition system. Overall, this article highlights the importance of intelligent image recognition technology in modern society and provides readers with a comprehensive understanding of the underlying concepts and techniques that drive this technology.

show abstract

Application and Evaluation of Image-based Information Acquisition in Railway Transportation

Cited by 5 publications

References 38 publications

Research and design of an expert diagnosis system for rail vehicle driven by data mechanism models

Research and design of an expert diagnosis system for rail vehicle driven by data mechanism models

Application of Adaptive UKF Algorithm in Multi-target Tracking and Positioning System

Design and Realization of Computer Image Intelligent Recognition System

Contact Info

Product

Resources

About