Method and apparatus for detecting railtrack failures by comparing data from a plurality of railcars

• US 5,987,979 A
• Filed: 11/30/1998
• Issued: 11/23/1999
• Est. Priority Date: 04/01/1996
• Status: Expired due to Fees

• Current Assignee: Cairo Systems, Inc.
• Original Assignee: Cairo Systems, Inc.
• Inventors: Bryan, Michael A.
• Primary Examiner(s): FELBER, JOSEPH LEON
• Application Number:
  US09/201,326
• Time in Patent Office: 358 Days
• Field of Search: 73/146, 33/1 Q, 33/651
• US Class Current: 73/146
• CPC Class Codes: B61K 9/08 Measuring installations for surveying permanent way applications of measuring apparatus or devices for track building purposes E01B35/00; measuring techniques G01
• CPC Class Codes: B61L 2205/04 Satellite based navigation systems, e.g. global positioning system [GPS]
• CPC Class Codes: B61L 23/044 Broken rails
• CPC Class Codes: B61L 23/048 Road bed changes, e.g. road bed erosion
• CPC Class Codes: B61L 25/021 Measuring and recording of train speed
• CPC Class Codes: B61L 25/023 Determination of driving direction of vehicle or train
• CPC Class Codes: B61L 25/025 Absolute localisation, e.g. providing geodetic coordinates
• CPC Class Codes: E01B 35/06 for measuring irregularities in longitudinal direction
• CPC Class Codes: G01S 19/14 specially adapted for specific applications

Abstract

A technique for monitoring anomalies in a railway system 400 to predict a future track behavior. The technique uses a motion sensor 207, 209 operably coupled to a chassis of a rail car 101 to detect a possibility of an event which may correspond to an anomaly in the railway system. A global positioning sensor (GPS) 213 operably coupled to the chassis detects a geographical location of the rail car 101 at a time corresponding to the event, which correlates the anomaly to the geographical location and the time. The technique also uses a processor 301 operably coupled to the motion sensor 207, 209 to direct a signal corresponding to the event and a recorder 215 operably coupled to the processor 301 to log the signal which may correspond to the anomaly and the geographical location of the rail car corresponding to the event. A central station 104 tracks and analyzes the anomaly over time to predict a possible defect in the railway system using a record of the events over time.

Claims

1. A method of detecting conditions of a railway system to predict a possible track failure, said method comprising:

detecting a first intensity value of an anomaly in a railway system using a first motion sensor operably coupled to a first moving rail car in a railway system;

detecting a second intensity value of said anomaly in said railway system using a second motion sensor operably coupled to a second moving rail car in said railway system; and

comparing said first intensity value to said second intensity value to identify a possible increase in a magnitude of said anomaly to predict a behavior of said anomaly.

2. The method of claim 1 further comprising identifying a track location of said anomaly using a positioning system operably coupled to said first moving rail car.

3. The method of claim 1 further comprising identifying a track location of said anomaly using a global positioning sensor operably coupled to said second moving rail car.

4. The method of claim 1 further comprising detecting a third intensity value of said anomaly using a third motion sensor operably coupled to a third rail car.

5. The method of claim 1 wherein said first moving rail car detects the first intensity value at a time substantially different from when said second moving rail car detects the second intensity value.

6. The method of claim 1 wherein said detecting of said first intensity value occurs at a different time from said detecting of said second intensity value.

7. The method of claim 1 wherein said anomaly is a rail track defect, said rail track defect is selected from a group consisting of a faulty rail tie, a faulty track, soil displacement, gravel displacement, and erosion of timber.

8. The method of claim 7 wherein the behavior is a possibility of a rail car derailment.

9. The method of claim 1 further comprising storing said first intensity value and said second intensity value in a memory.

10. The method of claim 1 wherein said first intensity value is detected at a first time and said second intensity value is detected at a second time, said first time occurring before said second time.

11. A method of detecting conditions of a railway system to predict a possible track failure, said method comprising:

detecting a plurality of intensity values of an anomaly in a railway system at a geographical location over time using a motion sensor operably coupled to a moving rail car in said railway system; and

analyzing said intensity values of said anomaly to identify a possible increase in a magnitude of said anomaly over time to predict a behavior of said anomaly.

12. The method of claim 11 further comprising ascertaining said geographical location of said anomaly using a global positioning sensor operably coupled to said moving rail car in said railway system.

13. The method of claim 11 wherein said anomaly is a rail track defect, said rail track defect is selected from a group consisting of a faulty rail tie, a faulty track, soil displacement, gravel displacement, and erosion of timber.

14. The method of claim 13 wherein the behavior comprises a rail car derailment.

15. The method of claim 11 further comprising storing said intensity values in a memory.

16. A system for detecting track failures in a railway system, said system comprising:

a plurality of rail car units to be operable in a railway system;

a tracking device on each of said rail car units for detecting an anomaly in said railway system, said tracking device including;

a sensor comprising a motion sensor to be coupled to a chassis of a rail car;

a global positioning sensor (GPS) to be coupled to said chassis; and

a processing means coupled to said GPS and coupled to said motion sensor for detecting a magnitude value of the anomaly at a geographical location over time and for comparing said magnitude value to previously detected values to identify a possible increase in the magnitude of said anomaly to predict a behavior of said anomaly; and

a tracking station for receiving data related to said anomaly from tracking device.