Method and system for determining a vertical profile of a rail surface

Abstract

The present invention defines a method of determining a vertical profile signal of a rail surface that includes, obtaining a vertical acceleration signal acc.sub.1, by measuring vertical acceleration of a bogie of a rail vehicle that runs on the rail surface; processing the vertical acceleration signal to obtain a vertical velocity signal; determining the vertical profile signal of the rail surface, by using the vertical acceleration signal and the vertical velocity signal as inputs to a simulation model of the bogie, the model having an unsprung mass connected to a sprung mass, the vertical acceleration signal acc.sub.1 represents the vertical acceleration of the unsprung mass; and measuring a linear velocity signal of the rail vehicle, the linear velocity signal is used in the step of determining to convert the vertical profile signal from the time domain to the distance domain.

Claims

1. A method of determining a vertical profile signal of a rail surface, comprising: obtaining a vertical acceleration signal acc.sub.1, by measuring vertical acceleration of a bogie of a rail vehicle that runs on the rail surface; processing the vertical acceleration signal acc.sub.1 to obtain a vertical velocity signal vel.sub.1; determining the vertical profile signal of the rail surface, by using the vertical acceleration signal acc.sub.1 and the vertical velocity signal vel.sub.1 as inputs to a simulation model of the bogie, the model comprising an unsprung mass m.sub.1 connected to a sprung mass m.sub.2, wherein the vertical acceleration signal acc.sub.1 represents the vertical acceleration of the unsprung mass m.sub.1; and measuring a linear velocity signal n of the rail vehicle, wherein the linear velocity signal is used in the step of determining to convert the vertical profile signal z from the time domain to the distance domain.

2. The method of claim 1, further comprising a step of converting the vertical profile signal to the wavelength domain.

3. The method of claim 1, wherein the step of processing further comprises: filtering the vertical acceleration signal acc.sub.1; converting the filtered signal to the frequency domain; single integration of the converted signal in the frequency domain; and obtaining the vertical velocity signal vel.sub.1 by converting the integrated signal to the time domain.

4. The method of claim 1, wherein the simulation model of the bogie is a quarter-bogie model.

5. A condition monitoring system for detecting corrugations in a rail surface, the system comprising: an accelerometer for measuring vertical acceleration, the accelerometer being mounted to a bogie of a rail vehicle that runs on the rail; a speed sensor for measuring a linear speed of the rail vehicle; a processor configured to receive a vertical acceleration signal acc.sub.1 from the accelerometer and to receive a linear speed signal n from the speed sensor; wherein, the processor is programmed to implement the determination of a vertical profile signal of the rail surface, by using a vertical acceleration signal acc.sub.1 and a vertical velocity signal vel.sub.1 as inputs to a simulation model of the bogie, the model comprising an unsprung mass m.sub.1 connected to a sprung mass m.sub.2, wherein the vertical acceleration signal acc.sub.1 represents the vertical acceleration of the unsprung mass m.sub.1.

6. The condition monitoring system of claim 5, further comprising means for position location, so that the vertical profile signal z may be calculated in the distance domain with reference to a fixed reference of known position.

7. The condition monitoring system of claim 5, wherein the processor is configured to perform a band-pass analysis of the vertical profile signal, to characterize the signal in terms of different wavelength bands corresponding to different classes of corrugation.

8. The condition monitoring system of claim 7, wherein the processor is configured to convert the vertical profile signal z into the wavelength domain and is programmed to transmit an alert if an amplitude of the signal in wavelength domain exceeds a predetermined maximum value that has been set for a specific wavelength band.

Description

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING

[0035] FIG. 1 is a schematic representation of a train including a condition monitoring system for bearing units that is suitable for use in the method according to the invention;

[0036] FIG. 2 is a flowchart of an example of method according to the invention;

[0037] FIG. 3 depicts a quarter-bogie model that is used in the method according to the invention.

[0038] FIG. 4 shows an example of a vertical profile signal in the distance domain, obtained using the method of the invention.

[0039] FIG. 5 shows an example of a vertical profile signal in the wavelength domain, obtained using the method of the invention.

DETAILED DESCRIPTION OF THE INVENTION

[0040] FIG. 1 is a schematic representation of a train including a condition monitoring system for bearing units of the train. The system provides multiple condition monitoring units 10—one for each wheel of the train—for measuring at least one operating parameter of one bearing unit of a train axle box. In the depicted example, the condition monitoring units 10 are formed as wireless sensor nodes attached to or embedded into the end plate of a double row roller bearing assembly of the hub (not shown). In other examples, the system for measuring and collecting data may be a wired system.

[0041] The measured operating parameters include vibrations, and each unit 10 is equipped with an accelerometer 12 that measures acceleration in the vertical direction. Typically, bearing temperature is also measured. In addition, at least one condition monitoring unit is equipped with a rotational speed sensor 13.

[0042] A control unit 18 for receiving and processing signals obtained from the condition monitoring units 10 is provided in a locomotive of the train. The communication between the control unit 18 and the condition monitoring units 10 is at least partially wireless using antennae 17a. If necessary, each of the wagons is provided or some of the wagons are provided with a remote network manager 15 serving as a wireless network manager, a power supply manager for the units 10 and as a wireless network extender. The wireless network can be a single-band 2.4 GHz network or a dual band 2.4 GHz and 5 GhHz network. The skilled person may use other communication frequencies or protocols including different protocols for the backbone and for the communication between extenders and the units 10 depending on the circumstances.

[0043] The control unit 18 is further equipped with a GPS antenna 17c and with an antenna 17b for a mobile communication interface using e.g. a GSM, GPRS, UMTS, LTE or HSDPA standard.

[0044] In the embodiment of FIG. 1, the control unit 18 provides a GPS receiver 19 receiving positioning signals from a system of satellites 30 as means for detecting a geographic position.

[0045] The train runs on a railway track (not shown). The individual rails may contain surface defects, such as corrugations, that affect the vertical acceleration measured by the sensors 12. The main purpose of the condition monitoring units 10 is to gather data on the health of the bearings. The control unit 18 may be programmed to analyse the measured data in real time, or may be configured to transmit the data to e.g. a server for storage in a database. The recorded and transmitted data is preferably tagged with positional information obtained from the GPS receiver 19.

[0046] The data may then be retrieved from the database and analysed remotely by a computer 50 that is programmed, for example, to identify defective operation of the wheel bearings. In the method of the invention, the gathered data is additionally used for condition monitoring of the rails. Specifically, a vertical profile of the rail surfaces is determined, in order to identify track sections where corrugations have a magnitude that is potentially harmful to the service life of rail vehicles.

[0047] The method of the invention is depicted by the flow chart in FIG. 2.

[0048] In a first step 100, a vertical acceleration signal acc1 is obtained from at least one accelerometer 12.

[0049] In a second step 200, the vertical acceleration signal is processed to obtain a vertical velocity signal v1.

[0050] The processing suitably provides filtering of the signal using e.g. a Butterworth filter in the passband of interest. Typically, a high-pass filter with a cut-off frequency of 10 Hz is used. The filtered signal is converted to the frequency domain and is then integrated to obtain a velocity signal in the frequency domain. An inverse FFT is then applied to obtain the vertical velocity signal v1 in the time domain. Omega Arithmetic is one example of a processing method that may be used to obtain the velocity signal veil from the acceleration signal acc1.

[0051] In a third step 300, the vertical velocity signal veil and the vertical acceleration signal acc1 are used as inputs to a simulation model of the bogie on which the accelerometer 12 is mounted, to obtain a track signal z of vertical undulations.

[0052] This will be explained with reference to FIG. 3, which shows a two-mass model of a bogie. The depicted model is generally known as a quarter-bogie model and is widely used in railway vibrations engineering. The model considers the train as two masses connected by a spring k2 and a damper c2, representing the primary suspension. The upper mass m2 represents a quarter of the mass of a bogie frame and train housing. The lower mass m1 simulates half of an axle mass and is an unsprung mass. In response to undulations in the rail surface 80, i.e. the vertical rail profile, the upper and lower masses m2 and m1 undergo vertical displacements y2 and y1 respectively. The displacements are influenced by the wheel-to-rail contact stiffness, which is represented by a spring k1. The function to be obtained is z, the vertical rail profile.

[0053] The equations of motion for the quarter-bogie model in the time domain are as follows:

m2ÿ2+c2({dot over (y)}2−{dot over (y)}1)+k2(y2−y1)=0  [1]

m1ÿ1−c2ÿ2+c1{dot over (y)}1−k2y2+(k1+k2)y1−k1z=0  [2]

[0054] The accelerometer 12 measures the vertical acceleration of the unsprung mass m1, meaning that the vertical acceleration signal acc1 is equivalent to ÿ1. The vertical velocity signal veil that is obtained from acc1 is therefore equal to {dot over (y)}1. Further known parameters are the masses m1 and m2 (kg), the spring coefficient k2 (N/m) and damping coefficient c2 of the primary suspension and the spring coefficient k1 (N/m) of the wheel contact stiffness.

[0055] First, equation [1] is solved using the vertical velocity signal veil.

[0056] Suitably, state variables x1, x2 and x3 are defined, whereby:

[0057] x1=y1 (vertical displacement of m1), implying that {dot over (x)}1=vel1.

[0058] x2=y2 (vertical displacement of m2).

[0059] x3={dot over (x)}2, which implies that {dot over (x)}3={dot over (y)}2 (vertical velocity of m2).

[0060] Equation [1] may therefore be expressed in state-variable form as:

m2{dot over (x)}3+c2(x3−vel1)+k2(x2−x1)=0

[0061] such that

[00001]$\stackrel{.}{x}.Math.3=\frac{k_2}{m_2}.Math.x_1-\frac{k_2}{m_2}.Math.x_2-\frac{c_2}{m_2}.Math.x_3+\frac{c_2}{m_2}.Math.{\mathrm{vel}}_1$

[0062] Using known stiffness and damping matrices, equation [1] can be solved as follows:

[00002]$\left[\begin{array}{c}{\stackrel{.}{x}}_1\\ {\stackrel{.}{x}}_2\\ {\stackrel{.}{x}}_3\end{array}\right]=\left[\begin{array}{ccc}0& 0& 0\\ 0& 0& 1\\ \frac{k_2}{m_2}& -\frac{k_2}{m_2}& -\frac{c_2}{m_2}\end{array}\right].Math.\left\{\begin{array}{c}{x}_1\\ x_2\\ x_3\end{array}\right\}+\left\{\begin{array}{c}\begin{array}{c}1\\ 0\end{array}\\ \frac{c_2}{m_2}\end{array}\right\}.Math.{\mathrm{vel}}_1.Math.\left[\begin{array}{c}{y}_1\\ y_2\\ {\stackrel{.}{y}}_2\end{array}\right]=\left[\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right].Math.\left\{\begin{array}{c}{x}_1\\ x_2\\ x_3\end{array}\right\}+\left\{\begin{array}{c}0\\ 0\\ 0\end{array}\right\}.Math.{\mathrm{vel}}_1$

[0063] to obtain the vertical displacement y1 of the unsprung mass m1, the vertical displacement y2 of the sprung mass m2 and the vertical velocity y2 of the sprung mass m2.

[0064] Equation [2] can now be solved for the function z:

[00003]$z=\frac{m_1}{k_1}.Math.{\mathrm{acc}}_1+\frac{c_2}{k_1}.Math.{\mathrm{vel}}_1+\frac{\left(k_1+k_2\right)}{k_1}.Math.\stackrel{.}{y}.Math.2-\frac{k_2}{k_1}.Math.y_2$

[0065] Thus, the vertical acceleration signal acc1 is used directly to solve the equations of motion associated with the model. Furthermore, this signal is subjected to only one integration process, to obtain the vertical velocity signal veil, which is also used as an input to solving the equations. The calculated vertical profile signal z therefore contains minimal noise and has a high degree of accuracy.

[0066] Returning to FIG. 2, the method of the invention suitably provides converting the calculated signal from the time domain to the distance domain. The method provides a further step 400 of obtaining a speed signal n of the train. In one example, at least one wheel of the train is equipped with a rotational speed sensor 13 (refer FIG. 1), whereby the measured speed in rpm is converted to a linear speed of the train using the known wheel diameter.

[0067] Using the measured speed, distance from a fixed reference point can be calculated. In order to locate the vertical track profile in the “real world”, the position of the fixed reference point may be obtained, for example, from the GPS receiver 19 or from a waypoint that triggers the gathering of vertical acceleration data along a particular route section. Alternatively, the location of objects at known positions along or adjacent to the track, such as points or crossings, may be detected. Dead reckoning methods may also be used, including inertial guidance systems, and measuring distance from known positions

[0068] An example of the vertical profile signal z in the distance domain is shown in FIG. 4.

[0069] Surface defects are usually classified according to their wavelength. In a metro line, for example, very short-pitch corrugations have a wavelength λ of 3-8 cm; short-pitch corrugations have a wavelength λ of 8-30 cm; medium-pitch corrugations have a wavelength λ of 30-100 cm.

[0070] The wavelength of track corrugations and their amplitude can be obtained from the vertical profile signal z. Suitably, the signal is converted to the wavelength domain, to enable defects to be classified according to their wavelength. An example of the track signal z plotted in the wavelength domain is shown in the periodogram of FIG. 5.

[0071] Once obtained, the vertical profile signal is used to identify track sections that may require maintenance. For example, alarms can be set according to the amplitude of defects within a specific wavelength band.

[0072] Thus, an in-service vehicle that is instrumented for monitoring bearing health can additionally be used for monitoring the condition of the track on which the rail vehicle runs. As will be understood, the method and system of the invention may be solely dedicated to the identification of surface defects in the track.