Research on Standard and Automatic Judgment of Press-fit Curve of Locomotive Wheel-set Based on AAR Standard

Lü, Jun; Jun, Xiao; Gao, Dong; Zong, Shu Yu; Zhu, Li

doi:10.1088/1757-899x/326/1/012010

Cited by 3 publications

(3 citation statements)

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“…At present, the connection strength analysis mainly adopts the pull-out method 2,3 and the pressing forcebased method. [4][5][6] The pull-out method is characterized by damage detection, high cost, and does not cover the entire product. Therefore, this method is often used for the analysis of connection strength in the design stage and the determination of static friction coefficient.…”

Section: Introductionmentioning

confidence: 99%

Connection force measurement of precision small interference components using ultrasound

Wang

Liu

Lü

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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Precision small interference components are mainly assembled using the press-fit method. Interface wear is inevitable in the press-fit process, which will reduce the connection strength. Pull-out experiments are the main means of measuring the connection force, but they are not available in the production process for its destructive characteristics. In this study, a nondestructive testing method for connection force based on ultrasound is proposed. An acoustic model was constructed based on the virtual layer model and statistical microcontact theory, which can be used to obtain the R- Kn- P mapping relationship. An ultrasonic measurement device was built manufactured and calibrated to achieve accurate alignment of the ultrasonic transducer with the interference component and accurate measurement of contact stress. The coaxiality error between the fixture and the turntable is less within ±5.9 μm. The parallelism errors between the turntable and Z-axis stage in the xoz- and yoz-plane are 0.0894° and 0.0662°, respectively. The measurement error due to the transducer positioning error is less than 1.5%. The equivalent static friction coefficient was proposed to compensate R- Kn- P calibration error and measurement error. The integral expression of the connection force was given. Finally, the connection force of the interference components was measured and verified by pull-out experiments. The measurement error is within ±10%.

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Section: Introductionmentioning

confidence: 99%

Connection force measurement of precision small interference components using ultrasound

Wang

Liu

Lü

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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“…Wheelsets are key to ensuring the safe operation of trains because the failure of an axle, a wheel, or one of its bearings will inevitably lead to accidental derailment [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Intelligent System for Railway Wheelset Press-Fit Inspection Using Deep Learning

et al. 2021

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Railway wheelsets are the key to ensuring the safe operation of trains. To achieve zero-defect production, railway equipment manufacturers must strictly control every link in the wheelset production process. The press-fit curve output by the wheelset assembly machine is an essential indicator of the wheelset’s assembly quality. The operators will still need to manually and individually recheck press-fit curves in our practical case. However, there are many uncertainties in the manual inspection. For example, subjective judgment can easily cause inconsistent judgment results between different inspectors, or the probability of human misinterpretation can increase as the working hours increase. Therefore, this study proposes an intelligent railway wheelset inspection system based on deep learning, which improves the reliability and efficiency of manual inspection of wheelset assembly quality. To solve the severe imbalance in the number of collected images, this study establishes a predicted model of press-fit quality based on a deep Siamese network. Our experimental results show that the precision measurement is outstanding for the testing dataset contained 3863 qualified images and 28 unqualified images of press-fit curves. The proposed system will serve as a successful case of a paradigm shift from traditional manufacturing to digital manufacturing.

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“…Benuzzi and Donzella analysed the contact pressure and speed related to lubrication and predicted a press-fitting curve using an FEM model and a simplified theoretical model [7]. Lu et al constructed and tested a mathematical model for the press-fit curve based on the AAR standard [8]. Saad et al predicted the residual stress and plastic strain for forging, machining, and assembling [9].…”

Section: Introductionmentioning

confidence: 99%

Railway Axle and Wheel Assembly Press-Fitting Force Characteristics and Holding Torque Capacity

Nwe

Pimsarn

2021

Applied Sciences

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Nowadays, press-fitting is widely used in the manufacturing industry because it allows easy and fast installation and is repetitive, strong, and inherently reliable. The quality of a press-fitting assembly can be verified from the press-fitting curves and forced monitoring. This study aims to investigate the characteristics of the press-fitting curve with various interference railway wheelset models and determine the interference limit that axles can withstand at the maximum holding torque without slipping and without plastic deformation. A three-dimensional finite element analysis examined the maximum press-fitting force and stress distributions using Abaqus FEA software. The press-fitting curves of the railway wheel and axle assembly obtained from finite element simulation were classified following European Standard EN 13260. The press-fitting curves showed whether they fell within the boundary limits in the EN standard to allow their practical application. This study also showed when plastic deformation would occur, within the recommended interferences in the EN standard. Moreover, the effect of interference was numerically simulated for the maximum holding torque capacity within the EN standard interference range. Numeric simulation was compared with the theory: the deviation was 15–6%.

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Research on Standard and Automatic Judgment of Press-fit Curve of Locomotive Wheel-set Based on AAR Standard

Cited by 3 publications

References 0 publications

Connection force measurement of precision small interference components using ultrasound

Connection force measurement of precision small interference components using ultrasound

Intelligent System for Railway Wheelset Press-Fit Inspection Using Deep Learning

Railway Axle and Wheel Assembly Press-Fitting Force Characteristics and Holding Torque Capacity

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