Self-assembling wireless network, vehicle communications system, railroad wheel and bearing monitoring system and methods therefor

• US 7,705,743 B2
• Filed: 01/19/2007
• Issued: 04/27/2010
• Est. Priority Date: 03/01/2006
• Status: Active Grant

• Current Assignee: Convey LLC
• Original Assignee: L-3 Communications Corporation (L3Harris Technologies, Inc.)
• Inventors: Nyquist, Charles W., Breitfeller, Jason O., Rose, Roger E. Jr., Jacobs, David Andrew, Barone, Gerard A.
• Primary Examiner(s): TWEEL JR, JOHN ALEXANDER
• Application Number:
  US11/655,672
• Publication Number:
  US 20070208841A1
• Time in Patent Office: 1,194 Days
• Field of Search: 340/682, 340/686.1, 340/933, 246/167.R, 246/169.S, 246/169.A
• US Class Current: 340/682
• CPC Class Codes: B61L 15/0027 Radio-based, e.g. using GSM-R
• CPC Class Codes: B61L 15/0036 Conductor-based, e.g. using CAN-Bus, train-line or optical fibres
• CPC Class Codes: B61L 15/0081 On-board diagnosis or maintenance
• CPC Class Codes: F16C 19/52 with devices affected by abnormal or undesired conditions
• CPC Class Codes: G01D 21/00 Measuring or testing not otherwise provided for
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04W 76/30 Connection release
• CPC Class Codes: H04W 84/005 Moving wireless networks
• CPC Class Codes: H04W 84/06 Airborne or Satellite Networks space-based or airborne stations H04B7/185
• CPC Class Codes: H04W 84/18 Self-organising networks, e.g. ad-hoc networks or sensor networks
• CPC Class Codes: Y04S 40/18 Network protocols supporting networked applications, e.g. including control of end-device applications over a network

Abstract

A low power self-organizing network is made up of a plurality of wireless communication nodes communicating wirelessly with each other. The nodes each have a sensor providing a respective sensor data value indicative of a physical parameter in the environment of that node. The wireless network discontinues communication with any nodes in which the sensor data value is outside a range of network sensor data values. The network is preferably a group of vehicles moving together, especially a train in which each node is associated with a respective wheel of a railroad car. The nodes are low-power devices that communicate using wireless communications according to a Zigbee protocol. The nodes each have an additional sensor sensing a physical parameter the respective wheel thereof and determines from said electrical signal a degree of degradation of a bearing of the wheel, and transmits data of the degree of degradation to the main node. The main node communicates with another computer system using a higher power communication system and transmits thereto data indicative of degradation of said bearings.

Claims

1. A networking system comprising:

a plurality of wireless communication nodes communicating wirelessly with each other so as to form a low power wireless network;

the nodes each having a sensor providing a respective sensor data value indicative of a physical parameter in the environment of the node;

said wireless network discontinuing communication with any nodes therein in which the sensor data value is outside a range of network sensor data values.

2. The networking system of claim 1, wherein one of said nodes determines whether the sensor data value from the sensor thereof is within said range of sensor data values, and responsive to a determination that the sensor data value thereof is outside said range, discontinues wireless communication with any of the other nodes of the network.

3. The networking system of claim 1, wherein when a first of the nodes of the system determines that a second of the nodes of the system has a sensor data value that is outside the range of sensor data values, said first node causes the second node to be dropped or to drop itself from the network.

4. The networking system of claim 1, wherein one of said nodes joins the network as a result of receiving a communication signal from another node of said network, and transmits the sensor data thereof or receives data over the low power network defining the range of sensor data values, said node dropping from the network or being dropped from the network responsive to a determination made at one of said nodes that the sensor data of said one of said nodes is outside said range.

5. The networking system of claim 4, wherein, prior to receiving the communication signal, said one of the nodes is in a low-power sleep state that terminates and after which the node sends or receives said data.

6. The networking system of claim 1, wherein prior to joining the network, one of said nodes is in a low-power sleep state, said node waking from said sleep state responsive to a local electronic event so as to enter a higher power usage awake state, said node in said awake state transmitting data to, or receiving data from, another of the nodes of the network.

7. The networking system of claim 6, wherein after said one of said nodes enters the awake state and joins the network, a determination is made that the sensor data value thereof is within the range, and responsive to said determination, the node remains in the network and wirelessly communicates additional data with at least one other node thereof.

8. The networking system of claim 6, wherein said local electronic event is an interrupt to a microprocessor in the node.

9. The networking system of claim 6, wherein the node has a generator that generates electrical power responsive to movement of the node, and said local electronic event is an increase in a level of electrical power generated by the generator.

10. The networking system of claim 9, wherein the node is supported on a wheel of a vehicle, and the generator is configured so as to generate electrical power when the wheel rotates.

11. The networking system of claim 10, wherein the node has a supercapacitor that is charged by the generator when the wheel rotates and supplies power to the node at a later time when the power from the generator is not sufficient.

12. The networking system of claim 1, wherein the nodes are each associated with a respective vehicle.

13. The networking system of claim 1, wherein the nodes each have a Zigbee transceiver and communicate therebetween using wireless communications according to a Zigbee protocol.

14. The networking system of claim 1, wherein each node communicates wirelessly over the network using less than 50 mW of power for the communication.

15. The networking system of claim 1, wherein the sensor of each node is a rotation sensor operatively associated with a respective wheel and the sensor data value is a rate of rotation of said wheel.

16. The networking system of claim 1, wherein each node is associated with a respective wheel of railroad cars in a train moving together.

17. The networking system of claim 16, wherein the network includes a locomotive having a main node, said nodes all communicating with the main node either directly or by communicating through other nodes of the network as intermediary communication links.

18. The networking system of claim 16, wherein the nodes each have an additional sensor operatively associated with the respective wheel thereof and sensing a physical parameter thereof and providing an electrical signal corresponding to a value of said physical parameter, said node determining from said electrical signal a degree of degradation of a bearing of the wheel or a presence of a flat on said wheel, and transmitting a data signal indicating the presence of said flat or said degree of degradation to the main node, said main node communicating with another computer system using a higher power communication system and transmitting thereto data indicative of degradation of said bearings.

19. The networking system of claim 1, wherein each of said nodes is associated with a respective vehicle, the sensors each being a GPS device and the sensor data value identifying a respective location of each of the nodes, and said range of sensor data values defining a geographical area, one of said nodes dropping from the network when the location is outside said geographical area.

20. A method of forming a wireless network, said method comprising:

transmitting a wireless communication signal from a first node responsive to an interrupt therein;

receiving said wireless communication signal at a second node;

determining whether a sensor data value obtained from a sensor of the second node equals a discrimination value or falls within a discrimination range of values; and

making a determination at one of said nodes whether the sensor data value satisfies a network discrimination criterion; and

responsive to a determination that the sensor data value does not satisfy the network discrimination criteria, causing the second node to discontinue communications with the first node.

21. The method of claim 20, wherein the first node has a generator that produces electrical power as a result of turning of a wheel associated with the first node, said interrupt being caused by an increase in electrical power as a result of the wheel starting to turn.

22. The method of claim 21 wherein the second node is in a low-power sleep mode prior to receiving said wireless signal, and said wireless communication signal is a ping responsive to which the second node wakes and receives a wireless signal defining the discrimination value or range of values, or sends a wireless signal transmitting the sensor data value.

23. The method of claim 22, wherein, responsive to a determination that a third of said nodes has a sensor data value from a sensor thereof that satisfies the discrimination criteria, said first and third nodes function as a network.

24. The method of claim 23, wherein a network coordinator node joins the network, and said third node communicates with said network coordinator node by transmitting data to the first node, said first node transmitting said data as an intermediary to the network coordinator node.

25. The method of claim 24, wherein the network coordinator determines and transmits data defining the discrimination criteria for the network to the nodes of the network so as to be applied to nodes communicating with any of said nodes.

26. The method of claim 25, wherein the first, second and third nodes are each associated with a respective wheel of railroad cars, and the network coordinator node is carried on a locomotive;

said sensors of the first, second and third nodes being rotation sensors deriving said data values from a rate of rotation of the associated wheel, and the discrimination criteria being derived from a speed at which the locomotive is traveling, such that only nodes on railcars in a train being moved by the locomotive are in the network.

27. The method of claim 26, wherein the nodes each have an accelerometer detecting radial or vertical acceleration of an axle of the associated wheel and producing an electrical output signal dependent thereon, said method further comprising

analyzing the accelerometer output signal using a microprocessor in the node and determining therefrom a bearing condition data value corresponding to a degree of wear of bearings of said wheel, and

transmitting said bearing condition data value from the node over the network to the locomotive network coordinator node;

storing the bearing condition data values received from all of the nodes in a computer accessible data storage device at the locomotive network coordinator node.

28. The method of claim 27, and

transmitting data corresponding to the bearing condition data values for at least some of the nodes over a high-power wireless communication to a computer system accessible to an operator remote from the locomotive.

29. The method of claim 26, wherein the nodes each have a sensor generating an output signal indicative of a physical parameter that is affected by a flat on the associated wheel, said method further comprising

analyzing the sensor output signal using a microprocessor in the node and determining therefrom whether a flat is present on said wheel, said analyzing including determining whether elevated levels of the output signal are present periodically at a frequency corresponding to a frequency of rotation of the wheel;

and

transmitting data indicative of said presence of said flat from the node over the network to the locomotive network coordinator node;

taking action responsive to said data at the locomotive network coordinator node.

30. The method of claim 27, wherein the accelerometer output signal is analyzed by screening the output signal for elevated levels therein of defect frequencies for components of the bearings.

31. The method of claim 30, wherein said analysis includes performing a discrete Fourier analysis of said output for said defect frequencies.

32. The method of claim 31, wherein said analysis includes performing a discrete Fourier analysis of said output to derive levels of harmonic frequencies for said defect frequencies thereof, and a range of frequencies around said defect frequencies separated by frequency increments of 0.5 to 1 Hz.

33. The method of claim 20, wherein said communication signal includes data defining the network discrimination criteria, and the determination is made at the second node, which enters a low-power sleep mode responsive to the determination that the sensor data value does not satisfy the discrimination criteria.

34. The method of claim 20, wherein the discrimination criteria is a data value or a range of data values to which the sensor data value is compared.

35. The method of claim 31, wherein the node has a second accelerometer sensor sensing lateral or axial acceleration of the axle, said method further comprising

analyzing output from said second accelerometer for the presence of hunting of the wheel;

and

responsive to detection of hunting, transmitting data to the locomotive node configured to alert the locomotive node of the presence of hunting.

36. A node comprising:

a mounting structure configured to be secured in engagement with a railcar wheel axle assembly so that the node turns when a wheel of the railcar wheel axle assembly turns;

a housing supported on the mounting structure, said housing supporting a generator configured to produce electrical power when the wheel turns as the railcar moves;

circuitry supported in said housing and receiving said electrical power, said circuitry including a microprocessor and a low-power wireless communication transceiver;

a sensor assembly operatively associated with the axle assembly, said sensor assembly having accelerometers detecting axial and radial accelerations of the wheel axle assembly;

the circuitry receiving electrical signals from the accelerometers, said microprocessor having memory storing software configured to cause said microprocessor to analyze said electrical signals and derive therefrom bearing condition data corresponding to a degradation condition of bearings of the associated wheel axle assembly;

a rotation sensor operatively associated with the circuitry and supplying thereto a rotation frequency signal corresponding to the rate of rotation of the wheel;

the circuitry being configured to assemble the node into a network communicating wirelessly via said low-power transceiver wherein the network is made up of nodes traveling in a train together with a locomotive node to which the nodes transmit the bearing condition data, said nodes being retained in the network only if the rotation rate of the associated wheel is consistent with the railcars moving together in said train.

37. The node of claim 36, and

said sensor assembly having a temperature sensor sensing temperature of the axle assembly, the circuitry receiving electrical signals from the temperature sensor and using said signals to determine the condition of the bearings, said circuitry triggering an alarm reaction causing an alert to be given to an operator when the electrical signals indicate that the temperature of the axle has risen sharply or has exceeded a predetermined threshold temperature indicative of imminent bearing failure.

38. The node of claim 36, and

said sensor assembly having a temperature sensor sensing temperature of the axle assembly, and a microphone sensing sound in the axle assembly, the circuitry receiving electrical signals from the temperature sensor and the microphone and using said signals to determine the condition of the bearings.

39. The node of claim 36, wherein the node is configured to go into a low-power-usage sleep state using less than 5 mW of electrical power when the generator produces a low level of electrical power indicative of the wheel ceasing to rotate, and to wake up to a higher power operational state responsive to an increase of electrical power from the generator corresponding to the wheel beginning to turn or to a wireless communication ping from another node received via the transceiver.

40. A method for monitoring a wheel assembly of a railway car, said method comprising:

providing a monitoring unit on an axle structure connected with a wheel of said assembly so that an accelerometer of said monitoring unit detects radial accelerations of said axle and transmits a data signal corresponding thereto;

obtaining accelerometer data from said data signal over a period of time while the railway car is in movement; and

analyzing said accelerometer data so as to derive data indicative of whether the wheel has a flat, or bearing condition data corresponding to a degree of degradation of a bearing of the wheel;

said analyzing comprising screening the accelerometer data for characteristics of presence of said flat or of bearing component failure;

wherein said analyzing includes determining an intensity for a set of predetermined defect frequencies for the bearing of the wheel;

wherein the determining of the intensity includes performing a Fourier analysis on the accelerometer data;

wherein the Fourier analysis on the accelerometer data is a discrete Fourier analysis directed to said set of defect frequencies; and

wherein the set of defect frequencies includes a frequency of rotation of the wheel, a cup defect frequency, a cone defect frequency and a roller defect frequency, and a frequency corresponding to the cup defect frequency minus the frequency of rotation of the wheel, a frequency corresponding to the cup defect frequency plus the frequency of rotation of the wheel, a frequency corresponding to the cone defect frequency minus the frequency of rotation of the wheel, a frequency corresponding to the cone defect frequency plus the frequency of rotation of the wheel, a frequency corresponding to the roller defect frequency minus the frequency of rotation of the wheel, and a frequency corresponding to the roller defect frequency plus the frequency of rotation of the wheel.

41. The method of claim 40 wherein the period of time in which the data is taken comprises data is at least ten revolutions of the wheel, and a predetermined number of samples are taken for the time period regardless of the rate of rotation of the wheel.

42. The method of claim 40 wherein the data signal from the accelerometer is passed through a signal conditioner that comprises a high pass filter, a rectifier, and a low pass or band pass filter filters out frequencies above about 300 Hz.

43. The method of claim 40, wherein the discrete Fourier analysis is also directed to a group of frequencies above and below said defect frequencies.

44. The method of claim 40, wherein the screening of said accelerometer data includes determining whether a peak is present for one of the defect frequencies and a second of the defect frequencies separated therefrom by the rotation frequency of the wheel.

45. The method of claim 40, wherein the group of frequencies are separated from each other by a frequency interval of 0.5 to 2 Hz.

46. The method of claim 40, wherein said analysis is performed by a microprocessor supported at the monitoring unit and the method further comprises:

transmitting said bearing conditioning data from said monitoring unit to a central computer system receiving bearing condition data from other monitoring units on other wheels of other railcars in a train of which the railcar is part.

47. The method of claim 46, wherein the bearing conditioning data is transmitted from the monitoring unit wirelessly using a low-power local communications protocol, and wherein the monitoring units of the train and the central computer system together form a network transmitting data from each monitoring unit to the central computer system using some of the monitoring units as intermediary communication nodes for monitoring units that are too distant from the central computer system to communicate directly therewith.

48. The method of claim 47, wherein the monitoring unit has a generator producing electrical power responsive to rotation of the wheel, said monitoring unit going into a low-power sleep state when the wheel stops turning, and returning to a higher-power awake state when the wheel turns again.

49. A method for monitoring a wheel assembly of a railway car, said wheel assembly having a wheel on an axle and a bearing on said axle, said method comprising:

providing a monitoring unit on the wheel assembly so that a microphone of said monitoring unit detects ultrasonic sound of said axle and transmits a data signal corresponding thereto;

obtaining acoustic data from said data signal over a period of time while the railway car is in movement; and

analyzing said acoustic data so as to derive condition data comprising flat data indicative of whether the wheel has a flat or bearing condition data corresponding to a degree of degradation of the bearing of the wheel;

said analyzing comprising screening the acoustic data for characteristics of the flat or bearing component failure; and

wherein the microphone analog signal conditioning comprises passing the output to a high-pass or band-pass filter allowing passage of frequencies of about 19.5 KHz and above, then through an amplifier with a gain of about 11, through a ½

wave rectifier and load having a time constant of approximately 0.68 ms, and then through a low-pass or band-pass filter transmitting frequencies of approximately 300 Hz or lower.

50. The method of claim 49 wherein said analyzing includes determining an intensity for a set of predetermined defect frequencies for the bearing of the wheel.

51. The method of claim 50 wherein the determining of the intensity includes performing a Fourier analysis on the acoustic data.

52. The method of claim 51 wherein the Fourier analysis on the acoustic data is a discrete Fourier analysis directed to said set of defect frequencies.

53. A method for monitoring a wheel assembly of a railway car, said wheel assembly having a wheel on an axle and a bearing on said axle, said method comprising:

providing a monitoring unit on the wheel assembly so that a microphone of said monitoring unit detects ultrasonic sound of said axle and transmits a data signal corresponding thereto;

obtaining acoustic data from said data signal over a period of time while the railway car is in movement; and

analyzing said acoustic data so as to derive condition data comprising flat data indicative of whether the wheel has a flat or bearing condition data corresponding to a degree of degradation of the bearing of the wheel;

said analyzing comprising screening the acoustic data for characteristics of the flat or bearing component failure;

wherein said analyzing includes determining an intensity for a set of predetermined defect frequencies for the bearing of the wheel;

wherein the determining of the intensity includes performing a Fourier analysis on the acoustic data;

wherein the Fourier analysis on the acoustic data is a discrete Fourier analysis directed to said set of defect frequencies; and

wherein the set of defect frequencies includes a cup defect frequency, a cone defect frequency and a roller defect frequency, and a second and third harmonic frequency of each of said frequencies.

54. The method of claim 53, wherein the discrete Fourier analysis is also directed to a group of frequencies above and below said defect frequencies and said second and third harmonics of said frequencies, said group of frequencies encompassing frequencies separated from the respective defect frequency by the frequency of rotation of the wheel.

55. The method of claim 53, wherein the screening of said acoustic data includes determining whether a peak is present for a frequency separated from one of said defect frequencies by the rotation frequency of the wheel.

56. The method of claim 53, wherein said analysis is performed by a microprocessor supported at the monitoring unit and the method further comprises:

transmitting said bearing conditioning data from said monitoring unit to a central computer system receiving bearing condition data from other monitoring units on other wheels of other railcars in a train of which the railcar is part.

57. The method of claim 56, wherein the bearing conditioning data is transmitted from the monitoring unit wirelessly using a low-power local communications protocol, and wherein the monitoring units of the train and the central computer system together form a network transmitting data from each monitoring unit to the central computer system using some of the monitoring units as intermediary communication nodes for monitoring units that are too distant from the central computer system to communicate directly therewith.

58. The method of claim 57, wherein the monitoring unit has a generator producing electrical power responsive to rotation of the wheel, said monitoring unit going into a low-power sleep state when the wheel stops turning, and returning to a higher-power awake state when the wheel turns again.

59. A method for monitoring a wheel assembly of a railway car, said wheel assembly having a wheel on an axle and a bearing on said axle, said method comprising:

providing a monitoring unit on the wheel assembly so that a microphone of said monitoring unit detects ultrasonic sound of said axle and transmits a data signal corresponding thereto;

obtaining acoustic data from said data signal over a period of time while the railway car is in movement; and

analyzing said acoustic data so as to derive condition data comprising flat data indicative of whether the wheel has a flat or bearing condition data corresponding to a degree of degradation of the bearing of the wheel;

said analyzing comprising screening the acoustic data for characteristics of the flat or bearing component failure; and

wherein the acoustic data from the microphone is analyzed so as to determine whether the output of the microphone indicates the presence of ultrasonic sound having a frequency of at least 20 kHz at an intensity above a preselected threshold and for more than a preselected period of time, and

responsive to detection of said presence of said ultrasonic sound above said threshold and for more than the period of time, triggering an alert indicative of a bearing failure.

60. A node comprising:

a mounting structure configured to be secured in engagement with a railcar wheel axle assembly so that the node turns when a wheel of the railcar wheel axle assembly turns;

a housing supported on the mounting structure;

circuitry supported in said housing, said circuitry including a microprocessor and a low-power wireless communication transceiver;

a sensor assembly operatively associated with the axle assembly, said sensor assembly having accelerometers detecting accelerations of the wheel axle assembly;

the circuitry receiving electrical signals from the accelerometers, said microprocessor having memory storing software configured to cause said microprocessor to analyze said electrical signals and derive therefrom bearing condition data corresponding to a degradation condition of bearings of the associated wheel axle assembly;

the circuitry being configured to assemble the node into a network communicating wirelessly via said low-power transceiver wherein the network is made up of nodes traveling in a train of railcars together with a locomotive node to which the nodes transmit the bearing condition data, said nodes being retained in the network only where each node determines that the respective railcar thereof is moving with the railcars together in said train.

61. The node of claim 60, and

said sensor assembly having a temperature sensor sensing temperature of the axle assembly, the circuitry receiving electrical signals from the temperature sensor and using said signals to determine the condition of the bearings, said circuitry triggering an alarm reaction causing an alert to be given to an operator when the electrical signals indicate that the temperature of the axle has risen sharply or has exceeded a predetermined threshold temperature indicative of imminent bearing failure.

62. The node of claim 60, wherein the accelerometers of said sensor assembly detect axial and radial accelerations of the wheel axle assembly.

63. The node of claim 60, wherein said sensor assembly has a microphone sensing sound in the axle assembly, the circuitry receiving electrical signals from the microphone and using said signals to determine the condition of the bearings.

64. The node of claim 60, wherein said node determines that the respective railcar thereof is moving with the railcars together in said train based on an indication of velocity of the respective railcar.

65. The node of claim 60, wherein the mounting structure is configured to be secured in engagement with an axial end of an axle assembly of the railcar wheel axle assembly.

66. The node of claim 60, wherein the mounting structure is configured to engage securingly to an axle cap on the end of the axial end of the axle assembly.