On fault isolation for rail vehicle suspension systems

Reliability of the railway vehicle suspension system is of critical importance to the safety of the vehicle. It is very desirable to monitor the health condition and the performance degradation of the suspension system online, which offers the important information of the suspension system and is critically important for the condition-based maintenance rather than scheduled maintenance in the future. Advanced fault diagnosis method is one of the most effective means for the health monitoring of the suspension system. In this paper, taking the lateral suspension system as an examcple, the fault isolation issue for different component faults occurring in the suspension system is concerned. The sensor configuration for obtaining the vehicle state information and the mathematical model for the lateral suspension system are presented. Four fault features in the time domain and three fault features in the frequency domain are used for each sensor signal. Three different methods, Dempster–Shafer (D–S) evidence theory, Fisher discrimination analysis (FDA) and support vector machine (SVM) techniques are applied to the fault isolation problem. Simulation study is carried out by means of the professional multi-body simulation tool, SIMPACK. The simulation results show that these methods can isolate the considered component faults effectively with a high accuracy. The D–S evidence-based fault isolation approach outperforms the other two methods.     

Application of observer-based fault detection in vehicle roll control

This paper describes how observer-based techniques for intelligent fault detection were applied to monitoring an active suspension control system in an experimental articulated heavy vehicle. The aim was to define a practical method for detecting faults, taking into account the nonlinearities of the vehicle. The experimental vehicle was divided conceptually into subsystems, namely the passive dynamics of the trailer, the dynamics of the hydraulic actuators, and the expected response of the closed-loop system. A linear dynamic model was designed for each subsystem. A fault detection observer was then designed for each dynamic model. The observer feedback gains were chosen to optimise estimation by the observer residual of specified errors on the output measurements. The observer residuals were then normalised and combined logically to provide a fault diagnosis. The performance of the fault detection scheme is demonstrated in the case of sensor faults and changes in the operation of the active control system.     

Fault detection of vehicle suspension system using wavelet analysis

This paper presents a method based on continuous wavelet transform to detect the faults of vehicle suspension systems. The Morlet wavelet functions are employed to approach the natural frequencies of the system and the frequency components of the signal with relative maximum energy. To evaluate our method, we use a full vehicle dynamic model which has been simulated in ADAMS/CAR and validated by laboratory test results. The suspension faults have been considered due to the damage of shock absorbers (dampers) and upper damper bushings (UDBs) and assumed as the decrease in damping force and loose joints, respectively. In this paper, the incapability of the spectral analysis by using fast Fourier transform in analysis of the signals is revealed through applying the inputs that include transient characteristics and then wavelet transform employed to achieve more proper results. A swept frequency is applied as an input to the wheels that simulates the road irregularities. After detection of faulty sections of the system using signal energy distribution, the defects of damper and UDBs are distinguished from each other through observing the changes of natural frequencies and corresponding energy amplitudes.     

Condition monitoring of rail vehicle suspensions based on changes in system dynamic interactions

A novel scheme for the fault detection and condition monitoring of vehicle suspensions is presented in this study. The new technique exploits the dynamic interactions between different vehicle modes caused by component failures in the system, leading to a simple but effective solution. Compared with many model-based fault detection techniques, the proposed technique does not require complex mathematical models of the system and it overcomes potential difficulties associated with nonlinearities and parameter variations in the system. The use of inexpensive inertial sensors and ease of tuning make the practical implementation of the proposed scheme straightforward. A conventional railway vehicle is used in the study to illustrate the basic ideas as well as the effectiveness of the novel fault detection method, although the general principle is applicable to other systems.     

Fault detection and isolation for a nonlinear railway vehicle suspension with a Hybrid Extended Kalman filter

Fault detection is considered to be one way to improve system reliability and dependability for railway vehicles. The secondary lateral and anti-yaw dampers are the most critical parts in railway suspension systems. So far, the dampers have been modelled as linear components in the fault detection and isolation observer design. In this work, a Hybrid Extended Kalman filter is used to capture the nonlinear characteristics of the dampers. In order to detect and isolate faults, a nonlinear residual generator is developed, which can distinguish clearly between different types of faults. A lateral half train model serves as an example for the proposed technique. The results show that failures in the nonlinear suspension system can be detected and isolated accurately.     

An efficient recursive least square-based condition monitoring approach for a rail vehicle suspension system

A model-based condition monitoring strategy for the railway vehicle suspension is proposed in this paper. This approach is based on recursive least square (RLS) algorithm focusing on the deterministic ‘input–output’ model. RLS has Kalman filtering feature and is able to identify the unknown parameters from a noisy dynamic system by memorising the correlation properties of variables. The identification of suspension parameter is achieved by machine learning of the relationship between excitation and response in a vehicle dynamic system. A fault detection method for the vertical primary suspension is illustrated as an instance of this condition monitoring scheme. Simulation results from the rail vehicle dynamics software ‘ADTreS’ are utilised as ‘virtual measurements’ considering a trailer car of Italian ETR500 high-speed train. The field test data from an E464 locomotive are also employed to validate the feasibility of this strategy for the real application. Results of the parameter identification performed indicate that estimated suspension parameters are consistent or approximate with the reference values. These results provide the supporting evidence that this fault diagnosis technique is capable of paving the way for the future vehicle condition monitoring system.     

Switched control of vehicle suspension based on motion-mode detection

This paper presents a study on switched control of vehicle suspension based on motion-mode detection. This control strategy can be potentially implemented via the interconnected suspension such as hydraulically interconnected suspension by actively switching its interconnection configuration in terms of the dominant vehicle body motion-mode. The design of the switched control law is developed focusing on three vehicle body motion-modes: bounce, pitch, and roll. At first, an H_∞ optimal controller will be designed for each motion-mode with the use of a common quadratic Lyapunov function, which guarantees the stability of the switched system under arbitrary switching functions. Then, a motion-mode detection method based on the calculation of the motion-mode energy is introduced. And then, the possible implementation of the control system in practice is discussed. Finally, numerical simulations are used to validate the proposed study.     

A real-time posture monitoring method for rail vehicle bodies based on machine vision

Monitoring vehicle operation conditions has become significantly important in modern high-speed railway systems. However, the operational impact of monitoring the roll angle of vehicle bodies has principally been limited to tilting trains, while few studies have focused on monitoring the running posture of vehicle bodies during operation. We propose a real-time posture monitoring method to fulfil real-time monitoring requirements, by taking rail surfaces and centrelines as detection references. In realising the proposed method, we built a mathematical computational model based on space coordinate transformations to calculate attitude angles of vehicles in operation and vertical and lateral vibration displacements of single measuring points. Moreover, comparison and verification of reliability between system and field results were conducted. Results show that monitoring of the roll angles of car bodies obtained through the system exhibit variation trends similar to those converted from the dynamic deflection of bogie secondary air springs. The monitoring results of two identical conditions were basically the same, highlighting repeatability and good monitoring accuracy. Therefore, our monitoring results were reliable in reflecting posture changes in running railway vehicles.     

Improving crosswind stability of fast rail vehicles using active secondary suspension

Rail vehicles are today increasingly equipped with active suspension systems for ride comfort purposes. In this paper, it is studied whether these often powerful systems also can be used to improve crosswind stability. A fast rail vehicle equipped with active secondary suspension for ride comfort purposes is exposed to crosswind loads during curve negotiation. For high crosswind loads, the active secondary suspension is used to reduce the impact of crosswind on the vehicle. The control input is taken from the primary vertical suspension deflection. Three different control cases are studied and compared with the only comfort-oriented active secondary suspension and a passive secondary suspension. The application of active secondary suspension resulted in significantly improved crosswind stability.     

A numerical study of the derailment caused by collision of a rail vehicle using a virtual testing model

This study investigated the wheel-lift and roll-over derailment mechanisms caused by train collisions using a precise virtual testing model (VTM) of a Korean high-speed train. The VTM was a complex, nonlinear finite element model composed of the shell, beam, solid, spring, and surface contact elements for the car body, bogies, suspensions, and wheel–rail interfaces. The VTM was validated by checking the errors in the total energy and the dynamic responses of the spring elements. To achieve a quick, dynamic relaxation of the dead weight of the VTM before the collision analysis, the artificial damping method and the artificial force method were introduced and numerically evaluated. The surface-to-surface contact model from commercial software, Ls-Dyna, was applied to the VTM in order to simulate the derailment mechanisms caused by collision accidents. The numerical analyses of the VTM colliding with a large deformable obstacle or a rigid wall revealed for the first time that a mixed slip/roll-over-type derailment mechanism generally occurs. Furthermore, the simulation results were consistent with the results from a simplified theoretical derailment model of a wheel set.     

Fault detection and isolation for a full-scale railway vehicle suspension with multiple Kalman filters

Reliability and dependability in complex mechanical systems can be improved by fault detection and isolation (FDI) methods. These techniques are key elements for maintenance on demand, which could decrease service cost and time significantly. This paper addresses FDI for a railway vehicle: the mechanical model is described as a multibody system, which is excited randomly due to track irregularities. Various parameters, like masses, spring- and damper-characteristics, influence the dynamics of the vehicle. Often, the exact values of the parameters are unknown and might even change over time. Some of these changes are considered critical with respect to the operation of the system and they require immediate maintenance. The aim of this work is to detect faults in the suspension system of the vehicle. A Kalman filter is used in order to estimate the states. To detect and isolate faults the detection error is minimised with multiple Kalman filters. A full-scale train model with nonlinear wheel/rail contact serves as an example for the described techniques. Numerical results for different test cases are presented. The analysis shows that for the given system it is possible not only to detect a failure of the suspension system from the system's dynamic response, but also to distinguish clearly between different possible causes for the changes in the dynamical behaviour.     

基于RS的某电源车故障的综合评价

简单介绍了粗糙集理论,在分析、确定某型武器系统电源车故障评判指标体系的基础上,运用粗糙集客观赋权法确定了权重,克服了主观赋权法的不足,建立了电源车故障的RS综合评价模型,得出故障度次序和评价等级。该方法具有一定的实用性,为部队和地方其它设备故障评估提供了一种参考。     

Ride quality evaluation of a vehicle with a planar suspension system

The longitudinal connection between a chassis and a wheel in a conventional vehicle suspension system is commonly very stiff than the vertical connection. Such a mechanism can efficiently isolate vibrations and absorb shocks in the vertical direction but cannot sufficiently attenuate the impact in the longitudinal direction. In order to overcome such a limitation, a planar suspension system (PSS) with spring–damper struts in both the longitudinal and vertical directions is proposed so that the vibration along any direction in the wheel rotation plane can be isolated. In this paper, the dynamic responses of a vehicle with PSS due to a single bump and random road unevenness are investigated. The ride quality of the vehicle with PSS is evaluated in accordance with ISO 2631. A comparison with that of a similar conventional vehicle is conducted to demonstrate the promising potentials of the PSS in improving the vehicle ride quality.     

Impact of inerter nonlinearities on vehicle suspension control

This paper discusses the nonlinear properties of inerters and their impact on vehicle suspension control. The inerter was recently introduced as an ideal mechanical two-terminal element, which is a substitute for the mass element, where the applied force is proportional to the relative acceleration across the terminals. Until now, ideal inerters have been applied to vehicle, motorcycle and train suspension systems, in which significant performance improvement was achieved. However, due to the mechanical construction, some nonlinear properties of the existing mechanical models of inerters are noted. This paper investigates the inerter nonlinearities, including friction, backlash and the elastic effect, and their influence on vehicle suspension performance. A testing platform is also built to verify the nonlinear properties of the inerter model.     

Linear matrix inequality based control of vehicle active suspension system

Linear matrix inequality (LMI) methods, novel techniques in solving optimisation problems, were introduced as a unified approach for vehicle's active suspension system controller design. LMI methods were used to provide improved and computationally efficient controller design techniques. The active suspension problem was formulated as a standard convex optimisation problem involving LMI constraints that can be solved efficiently using recently developed interior point optimisation methods. An LMI based controller for a vehicle system was developed. The controller design process involved setting up an optimisation problem with matrix inequality constraints. These LMI constraints were derived for a vehicle suspension system. The resulting LMI controller was then tested on a quarter-car model using computer simulations. The LMI controller results were compared with an optimal PID controller design solution. The LMI controller was further tested by incorporating a nonlinear term in the vehicle's suspension model; the LMI's controller degraded response was enhanced by using gain-scheduling techniques. The LMI controller with gain-scheduling gave good results in spite of the unmodelled dynamics in the suspension system, which was triggered by large deflections due to off-road driving.     

A new parameter identification methodology for a modal analysis test of a rail vehicle

The validation of vehicle mathematical models is a key part of the virtual acceptance process since it is essential to ensure a precise representation of the reality. The model validation procedure should include validation of stationary but also dynamic tests. However, parameter identification from on-track tests is a challenging task due to the non-controlled excitation and the great variability of the test results. Thus, an alternative solution by means of a vehicle modal analysis is proposed, developing a parameter identification methodology for dynamic vehicle model parameters. This methodology calculates estimated values of the vehicle model parameters that have an influence on the excited vehicle vibration modes. Moreover, a new criterion for taking into account the effect of the measurement uncertainties on the selection process of the vehicle parameters is developed. Finally, experimental results show that not only estimations of the suspension stiffness parameters can be obtained, but damping values and structural frequencies from the vehicle bodies can also be estimated.     

Dynamic model for ride comfort evaluations of the rubber-tired light rail vehicle

The dynamic model was developed to evaluate vibration accelerations and ride comforts during the running of the Korean-standardised rubber-tired light rail vehicle. Ride comfort indexes were analysed and tested in accordance with UIC 513R by using the dynamic model and the actual vehicle in the test track. Based on the comparisons between analysis results and test results, the validity of the developed dynamic model was evaluated. It was verified whether or not the developed Korean-standardised rubber-tired light rail vehicle met the specified target specification on ride comfort. In addition, the influence of the wearing of guide wheels on ride comfort was estimated.     

An investigation into the effect of suspension configurations on the performance of tracked vehicles traversing bump terrains

This is a theoretical investigation into the effect of various suspension configurations on a tracked vehicle performance over bump terrains. The model developed is validated using published experimental data of the modal characteristics of the vehicle. The desired performance is based on ride comfort via the mixed objective function (MOF), which combines the crest factor of bounce acceleration, bounce displacement, angular acceleration, and pitch angle. The optimisation process involves evaluating the MOF for different numbers and locations of dampers and under different rigid bump road conditions and speeds. The system responses of the selected suspension configurations in the time and frequency domains are compared against the undamped suspension. The results show that the suspension configurations have a significant effect on the vehicle mobility over bump road profiles. For a five-road–wheel half model of a tracked vehicle, the maximum number of dampers to use for ride comfort over these road bumps is three with the dampers located at wheel positions 1, 2 and 5. This confirms the current practice for many tracked vehicles with 10 road wheels. However, it is further shown that the suspension fitted with two dampers at the extreme road wheels offer the best performance over various rigid bump terrains.     

An approach for the validation of railway vehicle models based on on-track measurements

This paper proposes an approach for the validation of railway vehicle models based on on-track measurements. The validation of simulation models has gained importance with the introduction of new applications of multi-body simulation in railway vehicle dynamics as the assessment of track geometry defects, the investigation of derailments and the analysis of gauging. These applications are not only interested in qualitative predictions of the vehicle behaviour but also in precise quantitative results of the safety and comfort relevant vehicle responses. The validation process aims at guaranteeing that the simulation model represents the dynamic behaviour of the real vehicle with a sufficient good precision. A misfit function is defined which quantifies the distance between the simulated and the measured vehicle response allowing to evaluate different models at different running conditions. The obtained modelling errors are compared to the measurement uncertainty estimated for one vehicle using repeatability analysis.     

Parameters optimisation of a vehicle suspension system using a particle swarm optimisation algorithm

The purpose of this paper is to determine the lumped suspension parameters that minimise a multi-objective function in a vehicle model under different standard PSD road profiles. This optimisation tries to meet the rms vertical acceleration weighted limits for human sensitivity curves from ISO 2631 [ISO-2631: guide for evaluation of human exposure to whole-body vibration. Europe; 1997] at the driver's seat, the road holding capability and the suspension working space. The vehicle is modelled in the frequency domain using eight degrees of freedom under a random road profile. The particle swarm optimisation and sequential quadratic programming algorithms are used to obtain the suspension optimal parameters in different road profile and vehicle velocity conditions. A sensitivity analysis is performed using the obtained results and, in Class G road profile, the seat damping has the major influence on the minimisation of the multi-objective function. The influence of vehicle parameters in vibration attenuation is analysed and it is concluded that the front suspension stiffness should be less stiff than the rear ones when the driver's seat relative position is located forward the centre of gravity of the car body. Graphs and tables for the behaviour of suspension parameters related to road classes, used algorithms and velocities are presented to illustrate the results. In Class A road profile it was possible to find optimal parameters within the boundaries of the design variables that resulted in acceptable values for the comfort, road holding and suspension working space.