A Survey on Fault Diagnosis Approaches for Rolling Bearings of Railway Vehicles

Yan, Guangxi; Jiang, Chen; Bai, Yu; Yu, Chengqing; Yu, Chengming

doi:10.3390/pr10040724

Cited by 41 publications

(19 citation statements)

References 140 publications

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“…Results of spent researches provide the organisation of rational service of engines on the basis of the analysis of engine oil. Similar approaches to estimation of intensity of wear on condition of lubricating oil are applied also for other technical systems [10,11], that confirms their efficiency. The most promising directions of development of methods of diagnosing of internal combustion engines, as well as other complex technical systems, are application of probabilistic methods [12,13], machine learning in the process of diagnosing [14], monitoring of engine oil condition in the process of operation of engines in real time [15].…”

Section: Methodssupporting

confidence: 56%

Spectrometric investigation of internal combustion engine oil

et al. 2022

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One of the ways to improve the efficiency of internal combustion engines is by reducing fuel and lubricant costs. The major cost of engine oil is due to the need to replace it regularly. Extending the service life of the oil based on the evaluation of its actual condition provides a significant reduction in operating costs. The article presents the results of the evaluation of changes in oil performance using spectrometric methods of oil sample analysis. Spectrometric methods allow to estimate promptly the intensity of accumulation of wear products, impurities, additives degradation degree, its viscosity index, oxidation, alkalinity in the oil. The results of spectrometric analyzes can also be used to assess the technical condition of the engine and the intensity of wear of its main parts. Results of researches confirm a possibility of scientific substantiation of prolongation of term of use of engine oils of internal combustion engines that provides decrease in operational expenses. The application of spectrometric methods of engine oil analysis also provides perfection of the engine maintenance system based on an objective estimation of the condition of the knots and mechanisms of the engine and the exception of not forced repairs and service. To increase the efficiency of the use of spectrometric methods of engine oil analysis, it is necessary to accumulate and generalize experience of their practical application and increase the duration of tests.

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Section: Methodssupporting

confidence: 56%

Spectrometric investigation of internal combustion engine oil

et al. 2022

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“…In very general terms, applied procedures and methods for monitoring and early fault diagnosis of rolling bearings and related industrial processes are mainly supported by time–frequency–amplitude analysis of occurring vibrations [ 28 , 29 , 30 , 31 ], occasionally integrated with information on temperature fluctuations [ 32 , 33 ], noise levels [ 34 , 35 ] and other degradative harsh working environmental conditions affecting the functionality [ 36 , 37 , 38 , 39 ].…”

Section: Vibration-based Rolling Bearings Fault Diagnosis: a Brief Su...mentioning

confidence: 99%

Highly Reliable Multicomponent MEMS Sensor for Predictive Maintenance Management of Rolling Bearings

et al. 2023

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In the field of vibration monitoring and control, the use of low-cost multicomponent MEMS-based accelerometer sensors is nowadays increasingly widespread. Such sensors allow implementing lightweight monitoring systems with low management costs, low power consumption and a small size. However, for the monitoring systems to provide trustworthy and meaningful data, the high accuracy and reliability of sensors are essential requirements. Consequently, a metrological approach to the calibration of multi-component accelerometer sensors, including appropriate uncertainty evaluations, are necessary to guarantee traceability and reliability in the frequency domain of data provided, which nowadays is not fully available. In addition, recently developed metrological characterizations at the microscale level allow to provide detailed and accurate quantification of the enhanced technical performance and the responsiveness of these sensors. In this paper, a dynamic calibration procedure is applied to provide the sensitivity parameters of a low-cost, multicomponent MEMS sensor accelerometer prototype (MDUT), designed, developed and realized at the University of Siena, conceived for rolling bearings vibration monitoring in a broad frequency domain (from 10 Hz up to 25 kHz). The calibration and the metrological characterization of the MDUT are carried out by comparison to a reference standard transducer, at the Primary Vibration Laboratory of the National Institute of Metrological Research (INRiM).

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“…As rolling bearings are in a working environment with frequent load changes, short start-stop cycles and many sources of interference for long periods of time [4] . Therefore, the study of rolling bearing fault diagnosis has been a hot topic of research [5] .…”

Section: Introductionmentioning

confidence: 99%

An Intelligent diagnosis method for rolling bearings based on Ghost module and adaptive weighting module

Qiang

Zhao

2023

Preprint

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The vibration signals of rolling bearings are inevitably influenced by noise as well as by working conditions. The use of one-dimensional original signals converted into images for rolling bearing fault diagnosis has achieved good results, but ignores the large size of the model and the speed of diagnosis, so it is not suitable for practical fault diagnosis. To address this problem, we propose a neural network based on Ghost modules and dynamic attention mechanisms. The method uses the Ghost module and coordinate attention to compress model size and reduce computational effort while improving the network's perception of the input signals. In addition, to enable efficient use of similar feature maps generated by convolution, an adaptive weighting module is proposed to further simplify the learning process and reduce network training time. The validity of the proposed method was verified on a dataset provided by Case Western Reserve University and the Mechanical Failure Prevention Technology Society. The results show that the proposed method not only has good noise immunity in noisy environments, but also has good diagnostic performance and good generalization performance under different loads. Under the same experimental conditions, the method proposed in this paper is compared with some methods and the results show the superiority of the proposed method in the diagnosis of rolling bearing faults.

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A Survey on Fault Diagnosis Approaches for Rolling Bearings of Railway Vehicles

Cited by 41 publications

References 140 publications

Spectrometric investigation of internal combustion engine oil

Spectrometric investigation of internal combustion engine oil

Highly Reliable Multicomponent MEMS Sensor for Predictive Maintenance Management of Rolling Bearings

An Intelligent diagnosis method for rolling bearings based on Ghost module and adaptive weighting module

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