The present invention relates to using a series of inductive proximity sensors to determine the trajectory of railroad car wheel sets over a section of straight railroad track. The trajectory is analyzed to determine if the wheel sets exhibit an unstable lateral motion or exhibit eccentric lateral tracking positions relative to the track.
Freight and passenger railroad car wheel sets can develop sustained lateral oscillations, commonly referred to as high-speed lateral instability or “hunting”, while operating on railroad track at elevated speeds. The consequences of wheel set lateral instability include:
1. Excessive suspension wear.
2. Damage to lading carried by railroad vehicles, particularly finished automobiles, electronic products or any items that are sensitive to sustained vibrations.
3. Increased derailment risk.
4. Increased fuel consumption of trains with hunting cars.
5. Reduced train operating speeds.
Lateral instability is a natural consequence of the typical railroad car wheel set design (
However, due to insufficient damping forces in this simple mechanical system the wheel set will tend to oscillate laterally around its equilibrium position, as shown in
Railroad cars have suspensions commonly referred to as “trucks” or “bogies”. Several different types of trucks are currently used in railroad cars, but most consist of two or more rigid axle wheel sets contained within a framework that rotates horizontally under the railroad car body to negotiate curves.
Attempts have been made to minimize wheel set lateral instability in railroad cars by several methods:
1. The use of cylindrical wheel shapes or wheels with very little tread taper.
2. Increasing the yaw resistance of railroad car suspensions to prevent lateral wheel set oscillations.
3. Adding yaw dampers to railroad car suspensions to damp out the lateral wheel set oscillations.
Unfortunately these methods also tend to degrade the ability of railroad car suspensions to negotiate curves, and they increase the cost and maintenance of railroad car suspensions. Thus, the vast majority of freight railroad cars in service in North America are not equipped with any special equipment to control wheel set lateral instability. As a consequence high-speed instability is remedied by simply replacing wheel sets and truck components when lateral instability is detected.
Truck tracking errors occur when one or more wheel sets in a truck run with a lateral offset toward one rail or the other. The causes of this behavior include:
1. The two wheels of a wheel set have worn to different diameters.
2. Different side/side wheel set center distances (d1, d2) due to defects in the truck frame (
3. Truck frames 7, locked in misalignment with the railroad car and track due to rotational binding or friction at their pivot point 22 (
Three truck-tracking situations are illustrated in
The current invention utilizes the same array of inductive proximity sensors as the lateral instability detector to detect wheel sets that are tracking toward one rail or the other. The invention also employs an algorithm that evaluates the wheel set trajectory to determine if a wheel set is tracking consistently toward one rail or the other.
Several methods have been previously developed to detect and quantify the lateral instability of railroad cars. Prior art involved placing acceleration or force sensors on individual railroad cars and monitoring these sensors in a series of track tests under controlled conditions. These “on-board” methods of detecting and quantifying lateral instability are not practical for the large number of railroad cars in operation on the freight railroads.
Another lateral instability detection device has been developed for commercial applications by Salient Systems, Inc. This device employs strain gauge force sensors applied to lengths of rail that sense the lateral forces applied by railroad car wheel sets. Proprietary computer algorithms are applied to the wheel set lateral force data to detect lateral force patterns associated with lateral instability.
The lateral force measurement method of detecting lateral instability suffers from the following problems:
1. Lateral force measuring sensors must be applied to the rails and calibrated periodically.
2. The lateral force sensors cannot be removed and reapplied to the rails for track maintenance.
3. Certain track maintenance activities destroy the lateral force sensors.
4. The lateral force sensors are susceptible to voltage surges that propagate along the rails.
5. Lighter railroad cars may generate lateral wheel forces that are below the sensitivity threshold of the sensors and will not be detected even though the railroad car wheel sets are laterally unstable.
The advantages of the lateral displacement measurement method of detecting lateral instability of the present invention compared to the lateral force method include:
1. The lateral displacement sensors of this invention are easily removed from the rails and do not require periodic calibration.
2. The inductive proximity sensors are well isolated from the rails and are less susceptible to damage from voltage surges in the rails.
3. The lateral displacement sensor detection capability is not affected by the magnitude of the lateral wheel force, and very light railroad cars (those more inclined to hunt) are detected as reliably as heavier railroad cars.
The shape of the sinusoidal trajectory of a laterally unstable wheel set is more uniform and easier to characterize compared to the wheel set lateral force time series.
Prior art for detecting truck tracking errors consists of a commercial product offered by Wayside Inspection Devices Inc. (http://www.wid.ca) called the T/BOGI™ system (U.S. Pat. No. 5,368,260). This device consists of a laser/camera range finder system that scans the side of passing railroad car wheel sets to measure their angular orientation and tracking disposition relative to the track.
The disadvantage of this prior art is the complexity and cost of the laser/camera range finder system and the need for periodic cleaning and maintenance. In addition, the T/BOGI™ system obtains one instantaneous measurement of the wheel set tracking position at a single point on the track.
The current invention evaluates the tracking position of the wheel set at several points along the track. Furthermore, the present invention detects light railroad cars, which are most prone to hunt. The present invention is easier to maintain and more resistive to damage caused by voltage surges in the rails.
An aspect of the present invention is to provide a railroad car lateral instability detection system using an array of inductive proximity sensors located at several points along a length of railroad track and oriented to measure the lateral position of wheel sets relative to the track.
Another aspect of the present invention is to provide a reliable computer algorithm that evaluates the set of wheel set lateral position sensor readings to detect an oscillating pattern indicating lateral instability.
Another aspect of the present invention is to provide a computer algorithm that fits a sinusoidal curve equation to the oscillating pattern of lateral wheel set positions.
Another aspect of the present invention is to provide a computer algorithm that evaluates the sinusoidal curve equation to develop a severity index that is related to the lateral acceleration of the unstable wheel set.
Another aspect of the current invention is to provide a remote alarm communication sub-system connected to the lateral instability detector.
Another aspect of the current invention is to provide a truck tracking error detector within the same system.
Another aspect of the current invention is to provide an algorithm that evaluates the wheel set trajectory to determine if a wheel set is tracking consistently toward one rail or the other, thereby indicating a truck tracking error.
Other aspects of this invention will appear from the following description and appended claims, reference being made to the accompanying drawings forming a part of this specification wherein like reference characters designate corresponding parts in the several views.
An array of inductive proximity sensors are attached to both rails along a length of railroad track and oriented to sense the lateral position of railroad car wheel sets relative to the track. The proximity sensor voltage signals are monitored by a computer running an automatic data collection and control (ADCC) system.
As a train passes over the section of track the lateral positions of the wheel sets in the railroad cars are recorded at each proximity sensor pair by the ADCC system.
After the train passes, the ADCC system applies an algorithm to the data that evaluates the lateral position data set of each wheel set to determine if an oscillating pattern exists. If so, then a second algorithm fits a sinusoidal curve equation to the oscillating pattern of lateral wheel set positions. A third algorithm evaluates the sinusoidal curve equation to develop a severity index that is related to the lateral acceleration of the unstable wheel set.
If an oscillating pattern is not found in the lateral position data of a wheel set, then the ADCC system applies an algorithm that evaluates the data for consistent tracking of the wheel set toward one rail or the other, thereby indicating a truck tracking error.
Concurrent with the data collection activity, the ADCC system scans the car identification radio tags of passing railroad cars as a reference for reporting any cars that exhibit lateral instability or truck tracking errors.
The ADCC program generates electronic reports of any railroad cars exhibiting lateral instability or truck tracking errors and transmits these reports over the railroad communication network to the appropriate destinations.
a, prior art, is a front plan view of a centered railroad car wheel set.
b, prior art, is the same view as
a, 3b, 3c, prior art, are top views of three truck tracking dispositions.
a is an end view of the inductive proximity sensor preferred mounting arrangement on standard North American 136-lb rail.
b is a top view of the proximity sensor preferred mounting arrangement shown in
a, 7b show a typical wheel flange profile on the rail at two lateral positions relative to the inductive proximity sensor detection envelope.
a, 8b, 8c are views of the wheel set on the rails at three lateral positions relative to the inductive proximity sensors.
a, 9b, 9c are three top views of a wheel set on the track with the inductive proximity sensor arrays.
a shows plots of the trajectories of the wheels in an unstable wheel set, the inductive proximity sensor detection envelopes, and the resulting sensor voltage signals.
b shows equations used to calculate lateral acceleration.
a, 11b are two top views of wheel sets exhibiting different tracking positions on the track, the inductive proximity sensors and the resulting sensor voltage signals.
Before explaining the disclosed embodiment of the present invention in detail, it is to be understood that the invention is not limited in its application to the details of the particular arrangement shown, since the invention is capable of other embodiments. Also, the terminology used herein is for the purpose of description and not of limitation.
Referring first to
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Referring next to
Referring next to
The ADCC system 10 concurrently monitors the railroad car identification system 1001 comprised of the radio identification tag reader 13 and wheel detector 12. The wheel detector 12 generates a voltage pulse as a railroad car wheel passes over the detector 12. These pulses are recorded by the ADCC system 10.
Electronic alerts or reports of railroad cars exhibiting lateral instability or truck tracking errors can be sent by the ADCC system via the phone, internet, radio or microwave link 11 to the appropriate destinations on the railroad communication network.
Referring next to
Nominal dimensions are d10=3.150 inch, d11=2.550 inch, d12=3.150 inch, d13=2.550 inch. Mounting holes H are used to mount the sensor 8 to a bracket. Active face 500 is placed near the flange tip point of a passing wheel. The cable connector 501 receives a cable (not shown).
Referring next to
Referring next to
In
b shows the wheel flange profile 4 shifted 0.25-inch toward the rail 2. The flange tip point FTP resides outside of the sensor 8 detection envelope E such that the internal relay is not triggered, and the sensor output voltage remains at 0 volts. The sensors are mounted such that a 00.25-inch lateral shift of the wheel set from the nominal center position toward the rail will result in the wheel flange moving outside of the sensor detection envelope, thereby changing the sensor output from 10 to 0 volts.
Referring next to
In
In
In
Referring next to
b shows a wheel set 40, 50, 60 exhibiting a slight lateral oscillation through the test zone. The pattern of sensor voltage signals 23,24 that correspond to this trajectory are shown. Sensors at positions 8 and 9 on the right rail 3 output 0-volt signals as the wheel passes over because the wheel set has moved toward flange contact with the right rail 3. Sensors at positions 1 and 16 on the left rail 2 output 0-volt signals as the wheel set passes over because the wheel has moved toward flange contact with the left rail 2.
c shows a wheel set 41, 51, 61 exhibiting more severe lateral oscillations through the test zone. The pattern of sensor voltage signals 25,26 corresponding to this trajectory are shown. Sensors at positions 7-10 on the right rail 3 output 0-volt signals as the wheel set passes over because the wheel set has moved toward flange contact with the left rail. Sensors at positions 1,2 and 15,16 on the left rail 2 output 0-volt signals as the wheel set passes over because-the-wheel set has moved toward flange contact with the left rail.
Comparing the patterns in
Referring next to
The algorithm first scans the left and right rail sensor voltage signals to find 0-volt readings that correspond to the wheels of an oscillating wheel set moving laterally toward the rail and outside of the sensor detection envelopes. In this example the wheel set shifted toward the left rail at sensor locations 2-6 and toward the right rail at sensors locations 11-14 as indicated by the 0-volt signals from these sensors.
Next, the algorithm determines the set of distance indices (LF,LL,RF,RL) corresponding to the positions of the first and last sensors signaling 0 volts according to EQS.1-4 in
The wavelength λ of the lateral wheel set sinusoidal oscillation is calculated from the average distance between the indices according to EQ. 5 in
Next, the right and left rail chord lengths CR and CL are calculated according to EQ. 6 and EQ. 7 in
The wavelength λ, right rail chord length CR and sensor lateral detection distance AR′ from the nominal wheel lateral tracking line are used in EQ. 8 of
Next, the oscillatory frequency ω of the wheel set is calculated according to EQ. 11 in
The maximum amplitude of the wheel set lateral acceleration amax is calculated from the average lateral oscillation amplitude A and the lateral oscillatory frequency ω according to EQ. 12 in
Referring next to
b shows the sensor array voltage signal patterns 29, 30 for a wheel set 40, 50, 60 tracking consistently toward the left rail 2. The right rail sensor voltage pattern 30 shows all sensors signaling 10 volts while the left rail sensor voltage pattern 29 shows all sensors signaling 0 volts. The patterns 29, 30 of
The tracking detector algorithm scans the sensor voltage signals for consistent readings of 10 volts from every sensor in the array on one rail and 0 volts from every sensor in the array on the other rail. If such patterns are found, then the wheel set is flagged as having a tracking error, and a report is issued identifying the wheel set by its position in the railroad car and the railroad car identification code.
Referring next to
1. Block 1000 monitors the inductive proximity sensors for high (10-volt) signals that indicate a train has arrived at the test zone.
2. When a sensor signal goes high block 1001 records the train time.
3. Block 1002 records the wheel detector (12 of system 1001) signals.
4. Block 1003 records the railroad car radio identification tag reader (13 of system 1001) data.
5. Block 1004 records the inductive proximity sensor array voltage signals.
6. Block 1005 monitors the elapsed time since the last sensor high signal to determine when the train has left the test zone. The program flows back to block 1002 if the train is still in the test zone.
7. If block 1005 determines that the train has left the test zone the program proceeds to block 1006 which records the end of file times and closes the files containing raw proximity sensor voltage signal data, wheel detector data and railroad car identification code data.
8. An algorithm operates in block 1007 that associates the wheel detector and railroad car identification code data with the proper proximity sensor array data for each wheel set and railroad car.
9. Block 1008 checks the proximity sensor array voltage patterns of the wheel set for lateral instability.
10. If block 1008 finds the current wheel set to be unstable then it proceeds to block 1010, which scans the proximity sensor array voltage patterns for the 0-volt index locations.
11. Block 1011 calculates the lateral oscillation wavelength for the left and right rails based on the locations of the 0-volt indices.
12. Block 1012 calculates the average lateral oscillation amplitudes for the left and right rail wheels.
13. Block 1013 calculates the oscillatory frequency of the wheel set from its linear velocity and oscillation wavelength and the maximum lateral acceleration of the wheel set.
14. Block 1014 writes the wheel set lateral instability records to a file on disk.
15. If the wheel set is found to be stable in block 1008 then the program proceeds to block 1009 which checks the proximity sensor array voltage signal patterns of the wheel set for tracking errors.
16. Block 1014 writes the wheel set tracking error records to a file on disk.
17. After the records for all of the wheel sets in the train are analyzed block 1015 generates an electronic report of the wheel sets and associated railroad cars that exhibit instability or tracking errors.
18. Block 1016 transmits the electronic report via the railroad communication network.
19. The program proceeds back to block 1000 to wait for proximity sensor signals indicating that a train is present at the test zone.
The preferred embodiment of the invention to detect lateral instability and tracking errors in North American freight railroad train service is shown in
1. Arrays of 16 inductive proximity sensor pairs 8,9 mounted on the left and right rails 2,3 of a railroad track 1 with a spacing of approximately 24 inches between sensor pairs.
2. Inductive proximity sensors 8,9 with a nominal detection range of 50 mm, an internal switching relay, a switching frequency of at least 250 Hz. and an operating voltage range of 10-30 VDC.
3. Inductive proximity mounting brackets (14-17 in
4. A railroad car identification system 1001 in
5. An automatic data collection and control computer 10 in
6. A straight section of railroad track with minimal surface and alignment deviations and average train speeds above 50 mph.
Alternative embodiments of the invention are appropriate for other railroad applications such as high-speed passenger trains. In this application the inductive sensor design and spacing would be modified to detect the longer wavelength lateral oscillations and higher operating speeds of passenger railroad cars. Another less expensive embodiment would only use a single left or right array to compare a pattern deviating from a chosen normal pattern of wheel segments either in or out of a set of proximity sensor envelopes.
Although the present invention has been described with reference to preferred embodiments, numerous modifications and variations can be made and still the result will come within the scope of the invention. No limitation with respect to the specific embodiments disclosed herein is intended or should be inferred. Each apparatus embodiment described herein has numerous equivalents.
This application is a non-provisional application claiming the benefits of provisional application No. 60/682,537 filed on May 19, 2005.
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