scholarly journals Train Wheelset Bearing Multifault Impulsive Component Separation Using Hierarchical Shift-Invariant Dictionary Learning

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Zhao-heng Zhang ◽  
Jian-ming Ding ◽  
Jian-hui Lin
Keyword(s):  
High Speed ◽  
Singular Value ◽  
Model Decomposition ◽  
Different Types ◽  
High Speed Trains ◽  
Value Decomposition ◽  
Envelope Spectrum ◽  
Fault Information ◽  
Types Of Faults ◽  
Key Parameter

A wheelset bearing is a crucial energy transmission element in high-speed trains. Any parts of the wheelset bearing that have faults may endanger the safety of the railway service. Therefore, it is important to monitor the running condition of a wheelset bearing. The multifault on a wheelset bearing is very common, and these impulsive components generated by different types of faults may interact with each other, which increases the difficulty of entirely identifying those faults. To solve the multifault problem, this paper proposed a hierarchical shift-invariant K-means singular value decomposition (H-SI-K-SVD) to hierarchically separate those multifault impulsive components based on their fault power levels. Each of the separated impulse signals contains only one fault impulse, and the fault information could be highlighted both in time domain and frequency domain. In addition, the sparsity of envelope spectrum (SES) is introduced as an indicator to adaptively tune a key parameter in this method. The effectiveness of the proposed method is verified by both simulation and experimental signals. Compared with ensemble empirical model decomposition (EEMD), the proposed method exhibits better performance in separating the multifault impulsive components and detecting the faults of a wheelset bearing.

scholarly journals Determination of Necessary Subsidiary Track According to Train Operation Frequency in a Heterogeneous Train Pattern

2020 ◽  
Vol 10 (12) ◽  
pp. 4164
Author(s):  
Hyoung June Kim
Keyword(s):  
Genetic Algorithm ◽  
Waiting Time ◽  
High Speed ◽  
The Third ◽  
Railway Construction ◽  
Different Types ◽  
High Speed Trains ◽  
Train Operation ◽  
Operation Frequency

In this study, a genetic algorithm was used to calculate the scheduled waiting time according to the train operation frequency of heterogeneous trains operating on one track. The acquired data were then used to determine the appropriate subsidiary track at which high-speed trains can load or release cargo away from low-speed trains. A metaheuristic genetic algorithm was applied and implemented using Javascript/jQuery. Six cases were investigated, which provided values of subsidiary track that vary according to the operation frequencies of different types of trains, and solutions were derived through 100 simulations using a stochastic method. The analysis results showed that the train overtaking frequency was the highest at the third intermediate station within the simulation, suggesting that this particular station requires a subsidiary track, even if the operating frequency of each train differs across the entire track considered in this study. The results of this study are expected to facilitate objective and practical planning during railway construction.

Research on Rolling Element Bearing Fault Diagnosis Based on Singular Value Decomposition and Kurtosis Criterion

2013 ◽  
Vol 432 ◽  
pp. 304-309 ◽  
Author(s):  
Xiao Lin Wang ◽  
Yong Xiang Zhang ◽  
Jie Ping Zhu ◽  
Zhong Qi Shi
Keyword(s):  
Singular Value Decomposition ◽  
Vibration Signal ◽  
Singular Value ◽  
Rolling Element Bearing ◽  
Feature Extraction Method ◽  
Bearing Fault Diagnosis ◽  
Rolling Element ◽  
New Feature ◽  
Value Decomposition ◽  
Fault Information

In order to extract the faint fault information from complicated vibration signal of bearing, a new feature extraction method based on singular value decomposition (SVD) and kurtosis criterion is proposed in my work. According to the method, a group of component signals are obtained firstly using SVD, then component signals with equal kurtosis are selected to be summed together, and the weak fault signal is clearly extracted. The effectiveness of the method is demonstrated on both simulated signal and actual data.

scholarly journals On Fixed-Point Smoothing for Descriptor Systems with Multiplicative Noise and Single Delayed Observations

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Xiao Lu ◽  
Xin Dong ◽  
Haixia Wang ◽  
Baoye Song
Keyword(s):  
Fixed Point ◽  
Singular Value Decomposition ◽  
Multiplicative Noise ◽  
Singular Value ◽  
Descriptor Systems ◽  
Multiplicative Noises ◽  
Different Types ◽  
Delayed System ◽  
Reorganized Innovation ◽  
Value Decomposition

Optimal fixed-point smoothing problem for the descriptor systems with multiplicative noises is considered, where instantaneous and delayed observations are available. Standard singular value decomposition is used to give the restricted equivalent delayed system, where the observations also include two different types of measurements. Reorganized innovation lemma and projection theorem are used to give the fixed-point smoother for the restricted equivalent delayed system. The fixed-point smoother is given in terms of recursive Riccati equations.

Sensitivity Analysis of the Rectangular Trenches Employed in Suppression of the High-Speed Train-Induced Ground Vibrations

2010 ◽  
Author(s):  
Davood Younesian ◽  
Mehran Sadri
Keyword(s):  
High Speed ◽  
Vibration Reduction ◽  
Moving Loads ◽  
High Speed Train ◽  
Ground Vibrations ◽  
Infinite Domain ◽  
Aspect Ratios ◽  
Different Types ◽  
High Speed Trains ◽  
Train Speed

Ground vibrations generated by high-speed trains are studied in this paper. Open trenches are included in modeling and the problem is formulated using elasticity theory. The ground is modeled by a semi-infinite domain and the embankment with finite layers and the high-speed train is simulated by moving loads. The analytical solution is obtained in frequency domain and the peak particle velocity (PPT) is then achieved for different types of open trenches with different aspect ratios and distance from the track centerline. A parametric study is then carried out and effects of different parameters including the train speed and ground properties on vibration reduction factors are investigated.

scholarly journals Vision-Based Faint Vibration Extraction Using Singular Value Decomposition

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Xiujun Lei ◽  
Jie Guo ◽  
Chang’an Zhu
Keyword(s):  
Singular Value Decomposition ◽  
High Speed ◽  
Singular Value ◽  
Vibration Measurement ◽  
Displacement Sensor ◽  
Remote Measurement ◽  
Engineering Structures ◽  
High Speed Rail ◽  
Sound Barrier ◽  
Value Decomposition

Vibration measurement is important for understanding the behavior of engineering structures. Unlike conventional contact-type measurements, vision-based methodologies have attracted a great deal of attention because of the advantages of remote measurement, nonintrusive characteristic, and no mass introduction. It is a new type of displacement sensor which is convenient and reliable. This study introduces the singular value decomposition (SVD) methods for video image processing and presents a vibration-extracted algorithm. The algorithms can successfully realize noncontact displacement measurements without undesirable influence to the structure behavior. SVD-based algorithm decomposes a matrix combined with the former frames to obtain a set of orthonormal image bases while the projections of all video frames on the basis describe the vibration information. By means of simulation, the parameters selection of SVD-based algorithm is discussed in detail. To validate the algorithm performance in practice, sinusoidal motion tests are performed. Results indicate that the proposed technique can provide fairly accurate displacement measurement. Moreover, a sound barrier experiment showing how the high-speed rail trains affect the sound barrier nearby is carried out. It is for the first time to be realized at home and abroad due to the challenge of measuring environment.

FRACAS Based Failure Information Management for High-Speed Train

2014 ◽  
Vol 620 ◽  
pp. 569-574
Author(s):  
Bao Zhang Qu ◽  
Bing Hai Zhang ◽  
Bi Hong Lu
Keyword(s):  
Information Management ◽  
Product Life Cycle ◽  
High Speed ◽  
Closed Loop ◽  
High Speed Train ◽  
Enterprise Information ◽  
Information Platform ◽  
High Speed Trains ◽  
Enterprise Information Platform ◽  
Fault Information

Failure, because of the important role in the product life cycle for improving product design and manufacturing, is becoming important data information and being taken seriously. High-speed trains are complex electromechanical integration systems, and its failure occurred in operation may directly relate to people's life and property safety. FRACAS is a reliability engineering method, which allows the product fault information to follow Discovering, Report, Analysis,Correct andConfirm closed-loop management process, provides data and information to support effectively for improving the reliability of the train. This paper analyzed the fault information management needs of high-speed trains, combines high-speed trains product structure tree and fault model base to generate a high-speed train fault information database, by customizing and developing Relex FRACAS software. Then high-speed trains (CRH3) closed-loop management system is established. High-speed train FRACAS can easily build enterprise information platform for product reliability. Through the establishment of a unified failures database and solutions knowledge base, standardized information transferring and sharing are achieved. The train products faults can be timely reported and corrected. The accumulated data of troubleshooting in the whole process can be used in the failure statistical analysis and reliability prediction, which can effectively avoid major failures and repeated failures.

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