Search

Wheel polygonal wear is a common and severe defect, which seriously threatens the running safety and reliability of a railway vehicle especially a locomotive. Due to non-stationary running conditions (e.g., traction and braking) of the locomotive, the passing frequencies of a polygonal wheel will exhibit time-varying behaviors, which makes it too difficult to effectively detect the wheel defect. Moreover, most existing methods only achieve qualitative fault diagnosis and they cannot accurately identify defect levels. To address these issues, this paper reports a novel quantitative method for fault detection of wheel polygonization under non-stationary conditions based on a recently proposed adaptive chirp mode decomposition (ACMD) approach. Firstly, a coarse-to-fine method based on the time–frequency ridge detection and ACMD is developed to accurately estimate a time-varying gear meshing frequency and thus obtain a wheel rotating frequency from a vibration acceleration signal of a motor. After the rotating frequency is obtained, signal resampling and order analysis techniques are applied to an acceleration signal of an axle box to identify harmonic orders related to polygonal wear. Finally, the ACMD is combined with an inertial algorithm to estimate polygonal wear amplitudes. Not only a dynamics simulation but a field test was carried out to show that the proposed method can effectively detect both harmonic orders and their amplitudes of the wheel polygonization under non-stationary conditions.

Gear system is usually lubricated to generate an oil film to avoid dry contact at the mesh interface. As the oil film separates the engaging gear teeth, its effect on the transmission error (TE) is opposite to the teeth elasticity. How to consider the combined influence of the oil film and the tooth elasticity on the TE, and further on the dynamic performance of gears, is still not revealed completely. In this paper, a new mesh stiffness (MS) involving the effect from the oil film and the tooth elasticity is defined, and a nonlinear dynamic model of a spur gear system with developed MS and drive-side and back-side contact is proposed. The effect of the oil film on the dynamic responses of the gear pair is revealed by comparing the received results with that from the dry contact situation and the experiment. It is indicated that the oil film will affect the effective MS and dynamic transmission error (DTE) of the gear system, especially under the situation with the light load. For a tip relived gear pair, the dynamic load sharing ratio (DLSR) between teeth pairs changes significantly when the lubrication is considered.

Gear tooth profile deviations are usually inevitable due to the application of intentional tooth profile modification, the existence of undesired gear manufacturing errors and the tooth surface defects during operation, and they have been demonstrated to have significant effect on the vibration and noise level of gear transmissions. How to calculate the gear mesh forces accurately is crucial for gear dynamic simulation, especially in the presence of gear tooth profile deviations that will complicate the interactions at the gear mesh interface. This paper presents a spur gear dynamic model where the detailed deformations of individual teeth are considered, including the tooth flexible deformations, gear body deformations, the local teeth contact deflections, and the tooth deformations due to its neighboring loaded tooth. This dynamic model is validated by experimental test results with and without tooth tip reliefs. Then, the optimization of the tooth tip relief is performed. Finally, it is compared with three traditional dynamic models to reveal their discrepancies and applicability which could supply theoretical guidance for selection of gear dynamic models.

The traction motor is the power source of the locomotive. If the surface waviness occurs on the races of the motor bearing, it will cause abnormal vibration and noise, accelerate fatigue and wear, and seriously affect the stability and safety of the traction power transmission. In this paper, an excitation model coupling the time-varying displacement and contact stiffness excitations is adopted to investigate the effect of the surface waviness of the motor bearing on the traction motor under the excitation from the locomotive-track coupled system. The detailed mechanical power transmission path and the internal/external excitations (e.g., wheel–rail interaction, gear mesh, and internal interactions of the rolling bearing) of the locomotive are comprehensively considered to provide accurate dynamic loads for the traction motor. Effects of the wavenumber and amplitude of the surface waviness on the traction motor and its neighbor components of the locomotive are investigated. The results indicate that controlling the amplitude of the waviness and avoiding the wavenumber being an integer multiple of the number of the rollers are helpful for reducing the abnormal vibration and noise of the traction motor.

For railway locomotive, its motor bearing is one of the key components, which is likely to be damaged due to the intensified vibration conditions caused by the wheel-rail interaction and gear mesh....

Coupler jack-knifing and derailment of slave control locomotives in 20,000-tonne heavy-haul trains usually occur due to the combinations of large in-train forces with poor track conditions. This paper presents an experimental investigation on the dynamic performance of slave control locomotive couplers in 20,000-tonne heavy-haul trains. A field test method for measuring and monitoring the dynamic behavior of heavy-haul locomotive couplers is proposed. The on-track tests involved coupler forces, coupler yaw angles, and coupler dynamic motion monitoring of the test locomotive in the whole traveling process. The dynamic process of coupler jack-knifing is exhibited, and the distribution characteristics of the coupler forces and yaw angles are investigated. The test results indicate that the front and rear couplers of the slave locomotive group respectively suffer the largest draw (tensile) and buffing (compressive) forces, and the maximum yaw angle appears at the middle coupler between the slave locomotives. The maximum draw and buffing forces attain 1551 kN and 2067 kN, respectively. The maximum absolute yaw angle is about 13 degrees. During the cycle braking operation conditions, the intense buffing forces and the excessive coupler yaw angles are more likely to appear in the release process. The coupler instability generally occurs under train run in buffing forces. Moreover, the coupler status, the track conditions as well as the duration of buffing forces are also supposed to have an important effect on the coupler stability of slave control locomotives.

Development of railway transportation capabilities towards high-power, high-speed and heavy axle-load makes the dynamic interactions between the electric drive subsystem and the mechanical subsyste...

Development of railway locomotive towards high-speed and high-power has a higher requirement on traction motor bearing under the intensified wheel–rail interactions since the dynamic performance of...

Size and weight limitations mean that ordinary railway vehicles with two double-axle bogies cannot deliver some extremely heavy cargo and products. Thus, a newly designed high-speed freight electric multiple unit (EMU) equipped with two bogie groups each with two double-axle bogies connected by a transition frame is an alternative means of transporting heavy products because of its greater load capacity. However, because it is still in the design stage, its dynamic performance is yet to be researched, something that is urgently required because of the more-complicated structure and more-intensive wheel-rail interactions than those of traditional high-speed railway vehicles Therefore, to reveal the dynamic performance, this study establishes a three-dimensional dynamic model of a trailer vehicle in a high-speed freight EMU equipped with four double-axle bogies based on the classical theory of vehicle-track coupled dynamics. In this dynamic model, the vertical, horizontal, rolling, pitching, and yaw motions of the major components excited by random irregularities in the track geometry are considered fully. The results indicate that the derailment coefficient and stability index of this vehicle are both at excellent levels for the simulated conditions. The wheel unloading ratio appears to be larger but still within the safety range when the vehicle runs in a straight line, but it is close to or can even exceed the limit value when the vehicle runs at 400 km/h on a specified curved line.

Railway faults are usually observed as impulses in the vibration signal, but they are mostly immersed in noise. To effectively remove noise and identify the impulses, an improved morphological filter is proposed in this article. The proposal focuses on two aspects: a novel gradient convolution operator is proposed for feature extraction, and a new fault sensitivity measurement algorithm is proposed for scale selection because a morphological filter’s effectiveness is mainly determined by these two elements. The performance of the improved morphological filter is evaluated with real vibration signals measured from train’s axle bearings and cardan shafts. From the analysis of three sets of railway faults, the results indicate that the proposed morphological filter effectively detects the faults. Compared with three reported morphological filters, the proposed method has better diagnosis effectiveness.

Wheel flat can cause a large impact between the wheel and rail and excites a forced vibration in the locomotive and track structure systems. The working conditions and fatigue life of the motor bearings are significantly affected by the intensified wheel–rail interaction via the transmission path of the gear mesh. In this study, a fatigue life prediction method of the traction motor bearings in a locomotive is proposed. Based on the L−P theory or ISO 281 combined with the Miner linear damage theory and vehicle–track coupled dynamics, the irregular loads induced by the track random irregularity and gear mesh are considered in this proposed method. It can greatly increase the accuracy of predictions compared with the traditional prediction models of a rolling bearing life whose bearing loads are assumed to be constant. The results indicate that the periodic impact forces and larger mesh forces caused by the wheel flat will reduce the fatigue life of the motor bearings, especially when the flat length is larger than 30 mm. Using this method, the effects of the flat length and relatively constant velocity of the locomotive are analyzed. The proposed method can provide a theoretical basis to guarantee safe and reliable working for motor bearings.

Rotor eccentricity is a common fault in traction motors that directly affects the stability of the locomotive system. A locomotive-track coupled spatial dynamics model with traction power transmissions was established by considering the effect of rotor eccentricity in this study. The time-varying gear mesh forces, nonlinear wheel-rail contact forces, internal interactions between the components of the motor bearing, and dynamic forces induced by the rotor eccentricity, namely centrifugal force of the rotor, rotor-motor rub-impact force, and unbalanced magnetic pull (UMP), were comprehensively considered in the proposed model. The results indicated that rotor eccentricity affects the vibrations of the traction motor significantly. Additionally, the working condition of motor bearings was deteriorated by the rotor eccentricity, which was reflected by the increase in contact forces between the roller and races. The load region of the non-driving end bearing varies with the angular position of the rotor under the effect of rotor eccentricity. The proposed dynamics model will contribute in understanding and controlling the nonlinear dynamic behavior of locomotive traction motors.

Gear transmission is a key element in a locomotive for delivery of traction power from the electric motor to the wheelset. Its dynamic performance has a direct effect on the operational reliability or even safety of the locomotive or the train. In this paper, based on the classical vehicle–track coupled dynamics theory and the gear dynamics theory, a locomotive-track coupled spatial dynamics model is established where the dynamic effects from the gear transmissions are considered. In this model, the gear transmission system and the classical locomotive–track system are coupled with each other via wheel–rail contact interface and the gear mesh interface. The dynamic interactions between the rotational motions of the power transmission system, the vertical, lateral, longitudinal, roll, yaw and pitch motions of the components in a locomotive are fully included. This more comprehensive dynamics model of the locomotive–track system enables detailed investigations on the system dynamic performance under the complicated excitations from both the track geometrical irregularity and the internal mesh process of gear pairs (e.g. time-varying mesh stiffness, gear errors), especially the dynamic responses of the gear transmission in the complete vehicle vibration environment. This model is finally validated by comparisons with the field test data in the time- and time-frequency domains. And it is capable of being used for dynamics related assessment, such as vibration, fatigue and damage of the powered railway vehicles considering gear transmissions, especially for traction and/or braking conditions.

A locomotive is usually powered by the electromagnetic torque which is transmitted from the traction motor to the wheelset by gear transmission. In order to investigate the dynamic coupling effects from the gear transmission subsystems on the entire locomotive dynamics system, a comprehensive spatial locomotive dynamics model that considers the dynamic coupling effect of the gear transmissions is developed based on the multibody dynamics theory. In this model, the moved Marker technique is employed to calculate the dynamic mesh force of the gear pairs through which more accurate time-varying gear mesh stiffness excitations could be imported, which is the core of this dynamic model. Then, the established locomotive dynamics model is validated by comparing with the experimental test results. Finally, the dynamic effects of the gear transmissions are revealed by comparing with the results from the traditional locomotive dynamics model without considering the dynamic excitations from the gear transmissions. The results indicate that the gear transmissions have negligible effects on the vibrations of the carbody and the bogie frame, and on the lateral vibrations of the motor and the wheelset. However, the gear transmissions have significant effects on the vertical and, in particular, the longitudinal vibrations of the motor and the wheelset. Thus, it is suggested that the dynamic effects of the gear transmissions are considered in the locomotive dynamics modeling, especially when the vibrations of the motors and the wheelsets are taken into account.

As the prompt development of modern railway transportation towards high-speed and high load-capacity, the high-power locomotive is urgently required. Under this situation, the wheel–rail dynamic interaction is becoming more and more intensified which will deteriorate the vibration condition of the key elements of locomotive, such as the gear transmissions. Once gear failures are present, such as gear tooth crack or breakage, it is likely to threaten the operation safety of the locomotive. Thus, deep insight into the fault features of the locomotive gear transmission is urgently necessary for prevention of the induced disastrous consequences. This paper is concentrated on the fault vibration feature extraction of a locomotive in presence of gear tooth root crack under the complicated dynamic excitations from both the gear transmissions and the nonlinear wheel–rail interactions. The locomotive–track coupled dynamics model considering the dynamic effect of the mechanical power transmission path is employed, and the time-varying mesh stiffness of the gear pair with tooth root crack fault and the rail geometric irregularities are then incorporated into the dynamics model to obtain the vibration responses. Then, angular synchronous average technique is proposed to enhance the fault vibration features, and the statistical indicators extracted in frequency domain are developed to reveal the evolution law for the crack propagation scenarios along crack depth or tooth width. The analyzed results indicate that the angular synchronous average technique could effectively reveal the fault vibration feature, and the M8A in the selected statistical indicators is most sensitive to the tooth crack propagation in frequency domain.

Based on the theory of vehicle-track coupled dynamics and gear system dynamics, a locomotive-track coupled spatial dynamics model is established by considering the dynamic effects of the gear transmission system. The vibration responses of a locomotive’s major components are then simulated using three locomotive-track models, namely the proposed dynamics model with the gear transmissions, a locomotive-track coupled dynamics model that considers the traction motor, and the classical Zhai’s model. The locomotive dynamic responses of the three models are extracted and compared to reveal discrepancies between them so as to explore the dynamic effects of the power transmission system and clarify potential applications of these models. The results indicate that the dynamic effects of the gear transmissions have a negligible influence on the lateral vibrations of the locomotive components. However, they have obvious effects on the vertical and longitudinal vibrations of the wheelset and the traction motor. Another advantage of the locomotive dynamics model that considers the dynamic effects of the gear transmissions is that the dynamic performance of the drive system can be assessed in the vehicle vibration environment. This study provides theoretical references that can assist researchers in choosing the most appropriate locomotive dynamics model according to their specific research purpose.

Time-varying contact line and mesh stiffness are important parameters for dynamic investigation of helical gear pair with profile modification; however, the calculation methods of the time-varying mesh with high accuracy and high efficiency are also very limited currently. A new mesh stiffness calculation method for helical gear pairs with profile modification is proposed. The new method is conducted by cutting the helical gear tooth into slices to obtain the change of the contact line and the time-varying mesh stiffness with considering the change of each slice's engagement performance introduced by the profile modification. Then, the mesh stiffness of the assumed three different modification cases is calculated by using the proposed method. The calculated results indicate that the proposed method can be used to calculate the mesh stiffness of helical gear pairs, especially of those with tooth profile modification.

The axle box bearing is a critical component to support the vehicle and reduce the friction effect between the wheelset and the axle box. As one of the major failure modes, the localized defect in the outer race of the axle box bearing is a great threat to the operation safety of railway vehicles. Therefore, it is helpful to investigate the dynamic features of locomotive with effect of a localized defect of axle box bearing so as for better understanding of the bearing fault mechanism. In this paper, a locomotive-track coupled dynamics model with traction transmissions is proposed where the dynamics sub-model of the axle box rolling bearing is included. And the impact effect between the roller and the defect region is described as the time-varying displacement excitation and the time-varying contact stiffness excitation of the fault bearing. The results show that the passing frequency of roller and its harmonics of the vertical acceleration vibration of the axle box could be good indicators for the diagnosis of this localized defect, even if the fault feature could not be observed in the time history signals under the wheel-rail interaction. This work can provide some guidance for the early localized defect detection and diagnosis for the axle box bearing.

Ridge extraction is an effective tacholess order tracking technique for the fault detection of bearings under time-varying speed conditions. Cost function ridge detection (CFRD) is the most widely used ridge detection method. However, improper bandwidth selection and unreasonable cost function construction significantly restrict the performance of the CFRD. To address the two shortcomings of the CFRD, an improved CFRD (ICFRD) method is firstly proposed in this paper. The ICFRD integrates an adaptive search bandwidth determination technique that varies the search region with signal signatures, as well as a novel cost function that comprehensively considers the trade-off between ridge amplitude and smoothness. An iterative characteristic ridge extraction (ICRE) strategy is then presented based on the ICFRD to extract multiple characteristic ridges in a time-frequency plane automatically. The average frequency ratios between the extracted characteristic ridges are calculated to estimate bearing fault characteristic orders and therefore detect bearing faults. The performance of the proposed method was tested using simulated signals and experimental vibration signals collected from a machinery test rig. Results show that the ICRE outperforms the conventional CFRD in terms of detecting bearing faults under variable speed conditions. The average relative errors between the extracted instantaneous frequencies and the theoretical ones of the ICRE are 0.85%, 2.11% and 0.63% for inner race fault, outer race fault, and healthy bearing vibration signal, respectively. These values are much smaller than the results of using the CFRD.

Mechanical fault diagnosis is an indispensable part of the modern industrial production process. The application scenario of fault diagnosis according to a neural network from theory to practical application is worth exploring. Most existing work focuses on remaining life prediction and fault classification, treating these two steps independently. This study aims at coherent real-time monitoring of bearing status and proposes a gated recurrent unit -based fault monitoring structure to obtain timely response and preliminary classification of sudden faults. In the existing fault classification research, more attention is paid to the classification accuracy of the fault details. The time sequence law followed by the sudden fault and the short-term prediction of that fault are easily overlooked. The proposed method is trained by key-frames of bearing data. These data frames first pass through the feature extraction layer which consists of two layers of 1D convolution. Then, the reset gates and update gates of developed units keep the valid information at the last moment and update the unit state at that instant. A sudden fault will trigger the detection network, and the detected fault frame will be extracted for further classification by the independently trained fault classification network. During the test, a prediction of the moment of failure occurrence is directly obtained. When the status is judged to be faulty, the fault frame is directly extracted and used as the input of the classification network. Experimental results confirm that the network quickly responds to sudden failures under an operating environment, and the classification accuracy rate can stably reach more than 98%.

This paper aimed to investigate the effect of the lateral stiffness of secondary suspensions on the stability capacity and running safety of heavy-haul locomotives during braking based on the dynamic model and the field braking tests. The dynamic model of heavy-haul locomotives included two double-unit locomotives and five coupler systems. Simulation results indicate that the increasing of the lateral stiffness of secondary suspensions can improve the stability capacity and running safety of heavy-haul locomotives. Then, the field braking experiments were conducted to validate the dynamic model. Comparing the experiment results of different locomotives, the coupler and carbody yaw angles are respectively decreased by 31.8 and 29.5%, which is consistent with the simulation results. It is worthy to be noted that lateral vibration behaviour of the carbody increases with the increasing of the lateral stiffness of secondary suspensions. For the improved locomotive, the main frequency of lateral acceleration is 1…2Hz. However, the main frequency of lateral acceleration is 0.5…1Hz in the original locomotive tests. Moreover, the high-frequency vibration is increased, especially in 10…12.5Hz. According to the simulation and experiment results, the reasonable lateral stiffness of secondary suspensions is 400kN/m for the test locomotive.