Rail vehicle axle-box bearing damage detection considering the intensity of heating alteration

Vaičiūnas, Gediminas; Бурейка, Гинтаутас; Steišūnas, Stasys

doi:10.17531/ein.2020.4.16

Cited by 10 publications

(3 citation statements)

References 23 publications

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“…Traditional methods for rolling bearing fault diagnosis include vibration analysis [2], sound analysis [3], and temperature detection [4]. Signal processing techniques play a key role in these methods, such as time, frequency, and time-frequency domain analysis.…”

Section: Introductionmentioning

confidence: 99%

Analysis of hot spots and trends in rolling bearing fault diagnosis research based on scientific knowledge mapping

Chen,

Zhao,

Zhang

et al. 2024

Eng. Res. Express

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As a key component of mechanical equipment, real-time monitoring and diagnosis of rolling bearings play a critical role in ensuring the stable operation of equipment and the safety of operators. In order to present the current status and trends of fault diagnosis research on rolling bearings more intuitively, the scientific knowledge mapping was used to visualize and analyze the relevant literature in the article. The results show that the number of publications in this area of research has grown significantly in recent years, with China, India, the United States, and England having contributed significantly. The journals such as MECHANICAL SYSTEMS AND SIGNAL PROCESSING, MEASUREMENT, and JOURNAL OF SOUND AND VIBRATION have played an important role in disseminating cutting-edge technologies in this field. In addition, the exploration of modern methods based on data-driven and artificial intelligence, as well as their application to real-world problems, are gradually becoming the focus of research. Through summarising and analysing, the application of modern data processing techniques, the development of more efficient and practical intelligent fault diagnosis techniques, and the close integration of laboratory research and practical applications will become future research trends.

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Section: Introductionmentioning

confidence: 99%

Analysis of hot spots and trends in rolling bearing fault diagnosis research based on scientific knowledge mapping

Chen,

Zhao,

Zhang

et al. 2024

Eng. Res. Express

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“…Accurate modeling on RCF has been studied until now: some studies have focused on the mechanical and metallurgical characterization of different steels for wheel and rail [1]; while other studies present the development of analytical models [2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Monitoring the Damage Evolution in Rolling Contact Fatigue Tests Using Machine Learning and Vibrations

Provezza¹,

Bodini²,

Petrogalli³

et al. 2021

Metals

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This study shows the application of a system to monitor the state of damage of railway wheel steel specimens during rolling contact fatigue tests. This system can make continuous measurements with an evaluation of damage without stopping the tests and without destructive measurements. Four tests were carried out to train the system by recording torque and vibration data. Both statistical and spectral features were extracted from the sensors signals. A Principal Component Analysis (PCA) was performed to reduce the volume of the initial dataset; then, the data were classified with the k-means algorithm. The results were then converted into probabilities curves. Metallurgical investigations (optical micrographs, wear curves) and hardness tests were carried out to assess the trends of machine learning analysis. The training tests were used to train the proposed algorithm. Three validation tests were performed by using the real-time results of the k-means algorithm as a stop condition. Metallurgical analysis was performed also in this case. The validation tests follow the results of the training test and metallurgical analysis confirms the damage found with the machine learning analysis: when the membership probability of the cluster corresponding to the damage state reaches a value higher than 0.5, the metallurgical analysis clearly shows the cracks on the surface of the specimen due to the rolling contact fatigue (RCF) damage mechanism. These preliminary results are positive, even if reproduced on a limited set of specimens. This approach could be integrated in rolling contact fatigue tests to provide additional information on damage progression.

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“…there are such situations, when 50 % of defective shock absorbers per locomotive exist. The change of their temperature or the gradient of the heating rate of any particular object during the vehicle running is one of the important characteristics of the working shock absorbers [6][7][8][9].…”

mentioning

confidence: 99%

Proposal of a Method for Detection of a Damaged Hydraulic Shock Absorber in a Vehicle's Suspension System

Gorbunov¹,

Dižo²,

Blatnický³

et al. 2022

Komunikácie

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In principle, every vehicle is equipped by a suspension system, which usually consists of springs and shock absorbers. The main purpose of the suspension system is to eliminate vibration of sprung and unsprung masses. Therefore, the proper operation conditions of the shock absorbers affect in a fundamental way total running properties of vehicles. However, during operation, shock absorbers are being worn out or they can even be damaged. Then, such a situation is unwanted and it has to be detected as soon as possible. The content of this article is focused on analysis of vehicles’ shock absorbers defects. Methods for detection of possible shock absorbers faults are presented. Further, a proposal of the method for detection of a state of a hydraulic shock absorber during its operation is presented. The method uses identification of the temperature change of a hydraulic shock absorber during operation.

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Rail vehicle axle-box bearing damage detection considering the intensity of heating alteration

Cited by 10 publications

References 23 publications

Analysis of hot spots and trends in rolling bearing fault diagnosis research based on scientific knowledge mapping

Analysis of hot spots and trends in rolling bearing fault diagnosis research based on scientific knowledge mapping

Monitoring the Damage Evolution in Rolling Contact Fatigue Tests Using Machine Learning and Vibrations

Proposal of a Method for Detection of a Damaged Hydraulic Shock Absorber in a Vehicle's Suspension System

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