Hunting Motion Research Articles

Effect of Track Spectrum on the Dynamic Responses of Passenger–Train–Bridge System

To study the influence of the Chinese high-speed railway ballastless track spectrum and the German low-interference spectrum on riding comfort, a long-span highway-railway suspension bridge is studied as an example, and a passenger–train–bridge coupling model is established based on the structural dynamics. The vibration responses of the passenger–train–bridge system during the CRH2C train running on the bridge are studied by a combination of the self-written computer program and general finite element software, considering the hunting movement, and the riding comfort of trains and passengers is evaluated using [Formula: see text] and ISO-2631 standard, respectively. The results show that track irregularity has a few effects on the lateral vibration of the bridge. Compared with the German low-interference spectrum, the Chinese high-speed railway ballastless track spectrum has less exciting effects on the vibration of the passenger–train–bridge system and better riding comfort. Passengers in the middle of the train and on the middle seats of the same train have better riding comfort, and with the increase of train speed, the riding comfort of passengers will gradually reduce. Instead of passenger responses, the riding comfort classification based on the car body is overestimated.

Influence of nonlinear motor suspension parameters on Hopf bifurcation characteristics of high-speed bogie

A dynamic model of the bogie was established to investigate the influence of the elastic suspension of the motor and some nonlinear terms on the stability of vehicle hunting motion. Linear analysis was conducted based on the root locus method and other methods, and the influence of the elastic suspension of the motor on the linear critical speed was studied. Then, based on research on linear stability, the impact of the first Lyapunov coefficient of the model on the Hopf bifurcation type was analyzed. Subsequently, the influence of the stiffness and damping cubic terms in the motor suspension on the first Lyapunov coefficient was studied, and the possibility of controlling the Hopf bifurcation type by changing the stiffness and damping cubic terms in the motor suspension was analyzed, and relevant research was conducted. The results show that the increase of the cubic term of stiffness increased the corresponding speed when the amplitude of the limit cycle was 8 mm by about 3.4 km/h, and the increase of the cubic term of damping increased the corresponding speed when the amplitude of the limit cycle was 8 mm by about 8.9 km/h. Finally, a time-domain diagram corresponding to systems with different motor suspension stiffness and damping cubic terms was presented, further explaining the role of the motor suspension cubic terms and conducting relevant validation, providing reference opinions for the design of the motor elastic suspension of multiple units.

Integration of bio-inspired limb-like structure damping into motor suspension of high-speed trains to enhance bogie hunting stability

Hunting stability is an important performance criterion in railway vehicles. This study proposes an incorporation of a bio-inspired limb-like structure (LLS)-based nonlinear damping into the motor suspension system for traction units to improve the nonlinear critical speed and hunting stability of high-speed trains (HSTs). Initially, a vibration transmission analysis is conducted on a HST vehicle and a metro vehicle that suffered from hunting motion to explore the effect of different motor suspension systems from on-track tests. Subsequently, a simplified lateral dynamics model of an HST bogie is established to investigate the influence of the motor suspension on the bogie hunting behavior. The bifurcation analysis is applied to optimize the motor suspension parameters for high critical speed. Then, the nonlinear damping of the bio-inspired LLS, which has a positive correlation with the relative displacement, can further improve the modal damping of hunting motion and nonlinear critical speed compared with the linear motor suspension system. Furthermore, a comprehensive numerical model of a high-speed train, considering all nonlinearities, is established to investigate the influence of different types of motor suspension. The simulation results are well consistent with the theoretical analysis. The benefits of employing nonlinear damping of the bio-inspired LLS into the motor suspension of HSTs to enhance bogie hunting stability are thoroughly validated.

The Two-Parameter Bifurcation and Evolution of Hunting Motion for a Bogie System

The complex service environment of railway vehicles leads to changes in the wheel–rail adhesion coefficient, and the decrease in critical speed may lead to hunting instability. This paper aims to reveal the diversity of periodic hunting motion patterns and the internal correlation relationship with wheel–rail impact velocities after the hunting instability of a bogie system. A nonlinear, non-smooth lateral dynamic model of a bogie system with 7 degrees of freedom is constructed. The wheel–rail contact relations and the piecewise smooth flange forces are the main nonlinear, non-smooth factors in the system. Based on Poincaré mapping and the two-parameter co-simulation theory, hunting motion modes and existence regions are obtained in the parameter plane consisting of running speed v and the wheel–rail adhesion coefficient μ. Three-dimensional cloud maps of the maximum lateral wheel–rail impact velocity are obtained, and the correlation with the hunting motion pattern is analyzed. The coexistence of periodic hunting motions is further revealed based on combined bifurcation diagrams and multi-initial value phase diagrams. The results show that grazing bifurcation causes the number of wheel–rail impacts to increase at a low-speed range. Periodic hunting motion with period number n = 1 has smaller lateral wheel–rail impact velocities, whereas chaotic motion induces more severe wheel–rail impacts. Subharmonic periodic hunting motion windows within the speed range of chaotic motion, pitchfork bifurcation, and jump bifurcation are the primary forms that induce the coexistence of periodic motion.

Experimental and numerical study on bogie hunting motion of metro vehicles induced by wheel concave wear

In the long-term operation of metro vehicles, the obvious concave wear of the wheel profile will occur and will lead to poor wheel-rail contact conditions. Consequently, the bogie hunting instability arises and the bogie hunting motion would be excited under certain excitation, leading to the abnormal vibration phenomenon in metro vehicles. This paper presents experimental and numerical research on the bogie hunting motion of metro vehicles induced by wheel concave wear. The features of the abnormal vibration and wheel concave wear of a metro vehicle are revealed through comprehensive field tests. A three-dimensional metro vehicle-track coupled model is established to investigate the mechanism of the bogie hunting motion resulting from the wheel concave wear. The influences of the wheel concave wear and the operating speed of the metro vehicle on the bogie hunting stability are discussed. The results show that the bogie hunting motion resulting from the wheel concave wear is the root cause of the abnormal vibration of the metro vehicle. Re-profiling the wheel profile and reducing the operating speed of the metro vehicle can significantly eliminate the abnormal vibration phenomenon.

Adaptive nonlinear damping control of active secondary suspension for hunting stability of high-speed trains

This study employs an active secondary suspension with adaptive nonlinear damping to enhance the hunting stability of high-speed trains. Adjusting passive suspension parameters to optimize ride comfort and hunting stability simultaneously in varied extreme operational conditions poses a significant challenge for high-speed trains. This research integrates high-order displacement-dependent nonlinear damping into the secondary lateral suspension, drawing on insights from field test data. We analyze three typical hunting motion bifurcations: carbody hunting and both subcritical and supercritical bifurcations of bogie hunting. Theoretical analysis demonstrates that (a) the adaptive nonlinear damping narrows the unstable speed range and reduces the amplitude of the limit cycle in carbody hunting, (b) while it does not increase the critical speed for supercritical bogie hunting bifurcation, it substantially reduces the amplitude of the limit cycle, and (c) it increases the nonlinear critical speed for subcritical bogie hunting bifurcation, with the potential to alter the bifurcation from subcritical to supercritical, which holds considerable practical significance. Implementing such nonlinear damping directly through passive structure is challenging. Therefore, in view of this underactuated control problem, the constraint-following control is applied in the active suspension system to inherit the benefits of adaptive nonlinear damping. The simulation results show that the proposed active suspension system can effectively suppress the abnormal vibration caused by hunting motions.

The bifurcation of the forced hunting motion and its interaction with the self-excited hunting motion

The bifurcation of the forced hunting motion and its interaction with the self-excited hunting motion

The effect of yaw damper performance degradation on carbody hunting of high-speed trains

The yaw damper is an integral and pivotal component in guaranteeing the carbody hunting stability of high-speed trains (HSTs). However, it is reported that the occurring incidences of low-frequency carbody hunting frequently have been observed in HSTs, a predicament attributed to the degradation of yaw damper performance resulting from the obstruction of the damping valve by foreign particulates. Given these circumstances, the objective of this study is to investigate the impact of yaw damper performance degradation on the intricate phenomenon of carbody hunting motion. A HST dynamic model is developed, incorporating a detailed physical parameter model of the yaw damper, which enables the reproduction of abnormal low-frequency swaying arising from the deterioration in yaw damper performance. The findings of this study demonstrate that the obstruction of the damping valve significantly augments the damping force and dynamic stiffness of the yaw damper, thereby potentially instigating the occurrence of severe low-frequency hunting motion and consequent deterioration in the ride comfort of HSTs.

Dynamics of a Rail Vehicle in Transition Curve above Critical Velocity with Focus on Hunting Motion Considering the Review of History of the Stability Studies

The most general purpose of the current paper is to trace and discuss the history and state of the art of studies on vehicle motion (dynamics) in a transition curve above the critical velocity, with the aim of potentially increasing the circle of researchers involved in studying this issue and strengthening the will of the authors to continue their studies. This general goal is achieved in two ways: first, through a profiled literature analysis, showing the historical progress and current state of the research; and second, through reference to the history of stability studies as an example of selected studies’ development. In addition, this work has two more specific goals. Together, they consist of collecting the literature in a related field in one place and analyzing it on site to accomplish the review. Both specific goals are attained by dividing the literature into two corresponding parts. In the first part, the current issues of rail vehicle stability are analyzed and divided into four problems. The second part includes works that deal with the subject of the motion and dynamics of a rail vehicle on a transition curve section. Here, the works are divided into five groups and discussed. They are put in order from the closest to the furthest from this paper’s main subject; however, the last group includes the most recent references. In addition, information on the authors’ approach to the problem is provided, including the methods and models used, as well as example results. Based on the analysis of the literature and the state of the art, a summary of the analysis is presented at this paper’s end. It highlights the small number of works on the subject of interest, and based on the review of stability studies, it seeks to encourage present and potential authors to study this field and share their results with society.

Dynamic Modeling, Dynamic Characteristics, and Slight Self-Guidance Ability at High Speeds of Independently Rotating Wheelset for Railway Vehicles

For better small-radius curve negotiation performance, the independently rotating wheelset has the potential to be equipped in urban rail transit. As a crucial part of the running gear, its dynamic characteristics directly affect the railway vehicle’s stability and curve negotiation ability. This study follows a model–simulation–experiment method to delve into the dynamic process and steady convergent process of the independently rotating wheelset. An improved mathematical dynamic model of the independently rotating wheelset is established, considering the gravitational restoring forces of the wheelset and different creepages between the left and right wheels. In addition, the gyroscopic effects on the independently rotating wheelset with positive wheel tread conicity and at high speeds are introduced and analyzed. With variations in the longitudinal speed and yaw suspension coefficients, three kinds of motions, derailment, hunting, and offset running, occur on the independently rotating wheelset. We find that the gyroscopic effects contribute to the slight self-guidance ability of the independently rotating wheelset, causing a hunting motion at high speeds. Through sufficient simulations, the improved mathematical dynamic model is verified to be closer to the dynamic model built in the general multibody system simulation software SIMPACK 2018 than the classical mathematical dynamic model. Further, we perform experiments on a scaled independently rotating wheelset experiment system. The dynamic characteristics derived from theoretical analysis, especially the slight self-guidance ability at high speeds, are verified.

3D-Printed Origami Actuators for a Multianimal-Inspired Soft Robot with Amphibious Locomotion and Tongue Hunting.

The field of soft robotics is rapidly evolving, and there is a growing interest in developing soft robots with bioinspired features for use in various applications. This research presented the design and development of 3D-printed origami actuators for a soft robot with amphibious locomotion and tongue hunting capabilities. Two different types of programmable origami actuators were designed and manufactured, namely Z-shaped and twist tower actuators. In addition, two actuator variations were developed based on the Z-shaped actuator, including the pelvic fin and the coiling/uncoiling types. The Z-shaped actuators were used for the rear legs to facilitate the locomotion of the water-like frogs. Meanwhile, the twisted tower actuators were used for the rotation joints in the forelegs and for locomotion on land. The pelvic fin actuator was developed to imitate the land locomotion of the mudskipper, and the coiling/uncoiling actuator was designed for tongue hunting motion. The origami actuators and soft robot prototype were tested through a series of experiments, which showed that the robot was capable of efficiently moving in water and on land and performing tongue hunting motions. Our results demonstrate the effectiveness of these actuators in producing the desired motions and provide insights into the potential of applying 3D-printed origami actuators in the development of soft robots with bioinspired features.

A novel dimensionality reduction approach by integrating dynamics theory and machine learning

This paper aims to introduce a technique that utilizes both dynamical mechanisms and machine learning to reduce dimensionality in high-dimensional complex systems. Specifically, the method employs Hopf bifurcation theory to establish a model paradigm and use machine learning to train location parameters. The effectiveness of the proposed method is evaluated by testing the Van Der Pol equation and it is found that it possesses good predictive ability. In addition, simulation experiments are conducted using a hunting motion model, which is a well-known practice in high-speed rail, demonstrating positive results. To ensure the robustness of the proposed method, we tested it on noisy data. We introduced simulated Gaussian noise into the original dataset at different signal-to-noise ratios (SNRs) of 10 db, 20 db, 30 db, and 40 db. All data and codes used in this paper have been uploaded to GitHub.

Bio‐inspired structure constraints following control for enhancing hunting stability of high‐speed trains

AbstractHigh‐speed trains (HSTs) often face challenges associated with car‐body hunting, resulting from factors such as complex operating environments and wheel‐rail contact degradation. These issues have a significant impact on the ride quality and operational safety. Passive suspension systems are inadequate to provide satisfactory dynamic performance for HSTs in such circumstances. However, active suspension systems can provide an effective solution. To address the car‐body hunting stability of HSTs, this study proposes a novel control approach called displacement inequality constraint following control (ICFC‐BIS) for the active suspension of HSTs. The ICFC‐BIS leverages the beneficial nonlinearity of bio‐inspired structures (BIS) to indirectly achieve excellent dynamic characteristics of the BIS through actuators installed in the suspension of HSTs, eliminating the need for actual BIS installation. Numerical simulation results demonstrate that the proposed ICFC‐BIS can effectively suppress car‐body hunting motion, thereby enhancing the ride comfort of HSTs. Consequently, the operational safety and ride comfort indices of HSTs equipped with active suspension systems are significantly improved.

Railway Wheelset Active Control and Stability via Higher Order Neural Units

This article investigates an unconventional approach to solving the control of lateral displacement for railway bogie wheelsets using recurrent higher order neural units (HONUs). Although studies addressing control of independently rotating wheelsets have shown promising results, they are rarely applied by railway manufacturers. Research and developments in modern bogie design are trending toward active yaw control design as an extension to conventional wheelsets mechanics, particularly for higher speeds. We investigate a model-reference architecture for active control via setpoint tracking of lateral displacement. Then, a new HONU sliding mode architecture is derived to solve convergence for zero lateral displacements in higher running speeds which is a more profoundly complex issue in maintaining minimal hunting motion. Starting from the property of nonlinear polynomial architecture of HONUs with in-parameter linearity, we derive a time-variant state-space representation via nonlinear identical decomposition. Then, an input-to-state stability (ISS) approach is applied to prove the local asymptotic convergence of the applied algorithm in each state point and the bounded-input-bounded-state stability of the entire nonlinear adaptive control loop. Using ISS theory, we also prove the global asymptotic stability of the HONU sliding mode controller for the actively controlled wheelset system. The techniques are validated by simulations and a real roller rig system.

Bifurcation analysis of the bogie system with time delay and the influence of parameters on the system

In this paper, a bogie system with time delay is established. The centre manifold theorem and norm form theory are used to reduce the infinite dimensional delay system to the finite dimensional ordinary differential system, and the bifurcation behaviour of the bogie system is analysed. The MatCont toolkit was used to verify the subcritical bifurcation in the system. In addition, the influence of parameters on the bifurcation diagram of the system and the influence of parameters on the critical speed of the bogie system during the hunting motion are also analysed.

Computer vision for hunting stability inspection of high-speed trains

The existing online inspection methods for hunting motion of high-speed trains are mainly based on processing the acceleration of bogie frames, which cannot directly and reliably reflect the safety conditions. This paper proposes a novel computer vision (CV) method, named the virtual point tracking (VPT) method, to detect the hunting motion by processing the dynamic wheel-rail contact video. First, some virtual points are defined on each frame of the captured video, then the coordinates of these virtual points are automatically located by a deep learning model, and finally, the relative displacement between these coordinates is calculated. Two experiments demonstrate that the VPT method can accurately determine the hunting frequency and detect changes in the pixel coordinates corresponding to key positions of the wheel and the rail. Besides, a VPT method with Canny edge detection is introduced for comparison, and the results demonstrate that the VPT method is superior.

Prediction of hunting instability index of high-speed railway vehicles based on a coupled 2DCNN-GRU model

A coupled Two-Dimension Convolutional Neural Network-Gated Recurrent Unit (2DCNN-GRU) model is proposed to evaluate and predict the hunting instability of high-speed railway vehicles in this paper. First, vibration accelerations of four measuring points on the surface of the bogie frame of a high-speed railway vehicle in good working condition and with hunting instability are obtained through a line test and model simulation. The vibration acceleration data under different conditions is cut into many pieces at equal intervals. Low-frequency band-pass filtering is applied to each piece to obtain filtered vibration data, which is then analyzed separately to get a sample set of spectrum images, including short-time Fourier spectrum, Hilbert time-frequency-amplitude spectrum, and marginal spectrum. Then, a 2DCNN model is proposed to extract features by deeply studying the spectrum images of each piece of the filtered vibration data. The root-mean-square (RMS) of the vibration responses of four measuring points on the surface of the bogie frame and the mean value of the filtered vibration response envelope are calculated and recorded for each piece. The Hunting Instability Index (HII) is proposed by considering the weighted mean of RMS and the envelope mean of the filtered vibration responses to quantitatively get the extent of hunting instability. Finally, the GRU method is applied to predicting the dynamic change of HII indicators, and the effectiveness and accuracy of the method are verified by typical examples. One contribution of this work is proposing a method to evaluate the hunting motion by image identification of the short-time Fourier spectrum, Hilbert time-frequency-amplitude spectrum, and marginal spectrum of vibration signals, and another is the definition of HII based on 2DCNN and statistics.

Small-amplitude bogie hunting identification method for high-speed trains based on machine learning

Hunting stability is a critical aspect of the dynamic performance of high-speed trains. However, the current evaluation criteria only address heavy hunting motion, and they require supplementation and improvement to meet the increasing requirements of dynamic performance. Therefore, a study was conducted to develop an identification method for small-amplitude bogie hunting (SABH) motion. A total of 39,816 samples were obtained from field-measured bogie lateral acceleration and manually labelled as normal and SABH. The distribution comparison, Pierce coefficient, and importance ranking showed that harmonic character-related features (the autocorrelation coefficient, approximate entropy and etc.) should be considered more for SABH identification than amplitude-related features (maximum and RMS). The most critical features for SABH identification were the autocorrelation coefficient and spectral frequency spread. The classifier performance comparison showed that the decision tree was the best-performing classifier, followed by the support vector machine, while the linear discriminant, K-nearest neighbour, and naive Bayes classifiers were less effective. Sensitivity analysis indicated that the proposed method worked well with a sampling frequency of 50–200 Hz and a window length of 5–10 s. This research provides theoretical support for hunting instability monitoring and real-time active control studies for high-speed trains.

Utilization of Function Generation Synthesis on Biomimetics: A Case Study on Moray Eel Double Jaw Design.

Throughout history, humans have observed living or non-living things in nature and then imitated them in relation to these observations. This is due to the fact that the energy found in nature is generally consumed at an optimal level in order for it to endure. Biomimetic inspiration in many designs and applications is widely displayed, including within the field of engineering. In this paper, we were inspired by the double set of jaws found in the moray eel, which gives this fish a huge advantage while hunting, with a mobile pharyngeal jaw that works together with its oral jaw in order to overcome ineffective suction capabilities. A procedure that mimics the hunting motion of the moray eel was utilized by considering the overall movement as a single degree of freedom with multiple outputs on account of the repeating motion that is required during hunting. This procedure includes structural and dimensioning synthesis, wherein the latter was utilized with analytic kinematic synthesis for each linkage transfer. The flexibilities in parameters were taken into account with a novel multiple iterative kinematic synthesis algorithm that resulted in various mechanisms with the same purpose. Among the excessive number of resultant mechanisms, the optimization was carried out by considering the highest torque transmission ratio at critical timings that were specified as bio-constraints. In the end, the kinematic movement validation was utilized.

Numerical investigation on aerodynamic forces and flow patterns of high-speed trains from open air into long tunnel

Method of sliding mesh and segregated compressible large eddy simulation was used to simulate the flow field of a 1/25 scale eight-coach China Railway train running from open air into long tunnel, validated by the same scale Intercity Express 2 (ICE2) train. Side force fluctuation increases greatly when train enters tunnel. Short-time Fourier transform on side force coefficients of Coach 5 and 8 presents the peak frequency at about 95Hz. The hunting motion of laterally swinging airflow in lower space near the train is analyzed. Correlation analyses of pressure time histories reflect its traveling mode. Propagating velocity is 57–62% in open air, and 75–80% in tunnel of the operating speed. Wavelength is both in the range of 0.3–0.6m. Spectral Proper Orthogonal Decomposition (SPOD) and POD extract the transverse pattern of hunting motion. Total POD energy increases when hunting motion appears. Consistent to side force spectrums, SPOD energy spectrums present peak frequencies at 95Hz, where energy is larger in tunnel than open air. Mode 1 of POD and SPOD under peak frequencies presents similar spatial distribution: anti-symmetrical streamwise velocity fluctuation, vortex pairs outside bogie cavities and large-scale circulation. The relation between coherent structures and side forces is well established by SPOD.