Statistical and trend analysis of railroad bearing temperatures

Data processing: measuring – calibrating – or testing – Measurement system – Temperature measuring system

Reexamination Certificate

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Details

C702S179000, C246S16900S, C374S141000, C374S153000

Reexamination Certificate

active

06813581

ABSTRACT:

BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to systems for analyzing bearing temperature measurements taken from moving trains by wayside measurement devices, and more particularly to a system of statistical and trend analysis of railroad bearing temperatures that improves detection of faulty bearings and reduces the incidence of false “hot box” alarms.
2. Description of the Prior Art
Bearing temperature measurements are routinely taken from trains as they pass wayside measurement devices, commonly known as “Hot Box Detectors.” These measurements are indicative of bearing health and the risk of pending failure. Past use of measurements of this nature were severely limited by random and non-random braking events, differing train speeds, weather conditions, calibration errors, environmental effects (from dust, pollen, etc.), and the lack or non-use of resources to communicate these measurements to a datastore for their use in a more comprehensive manner. These limitations caused the applicable alarm levels of prior art systems to be set at artificially high temperatures in an attempt to limit the alarm notifications to pending bearing failures only. The artificially high alarm temperatures overlooked many statistically valid indicators of bearing problems for the purpose of allowing the operations of the railroad to continue without undue or excessive interruption on a day-to-day basis. However, they also allowed foreseeable failures to occur with major associated costs and delays.
Current hot box detectors typically provide an absolute alarm that is transmitted by radio when the temperature of a bearing exceeds an ambient temperature by a fixed value. Other alarm systems are available which identify bearings having a lower temperature than those above the fixed value. These systems make a fixed-difference comparison of a car average, or car-side average, to each of the single bearings on the car or to one side of the train. In some cases, the standard deviation has also been used as a measure of comparative health of the bearings. However, the problem with reducing the absolute fixed value or by adding additional comparison alarms that are more sensitive to lower temperatures is that the number of alarms increase greatly, which negatively affects railroad operations. The number of trains stopped due to these alarms may be five times higher than the number of trains later verified to be suffering from pending bearing failures. This is due to the large number of false alarms generated by current systems. False alarms include those alarms that are caused by: heat that is transmitted from the wheel brakes to the bearings; sun reflections; obscured sensor lenses; and other anomalous conditions or electrical problems. In addition, 20% to 40% of those bearings verified by human inspection as being “overheated” are later disassembled and determined by experts to have been falsely removed with no indications of heat or mechanical problems.
The ability to communicate all of the measured temperatures to a central or manned location is a common option for current detectors. This has provided the opportunity for further processing of the data to better analyze problems that are detected.
The exact locations of alarmable defects is currently given by an axle location, which is then manually counted from the leading end of the train. Some detectors now have integrated AEI detectors that improve equipment identification and bearing location. However, these stand-alone integrated devices are costly and still cannot resolve the other shortcomings in current hot box detection.
Accordingly, what is needed is a system for the accurate detection of bearing failures that virtually eliminates unnecessary train stops.
SUMMARY OF THE INVENTION
The system of the present invention tracks individual train wheel bearing temperatures and selects those that are statistically determined to be abnormally high, while eliminating from consideration, or otherwise categorizing those high temperature readings which are the result of other anomalous conditions. The system determines the overall distribution of the bearing temperatures for both sides of each train at each wayside location. The bearing temperatures are then ranked for comparison with the overall train distribution. Outliers are detected and characterized based on temperature patterns and previous history. Information compiled by the system is then displayed in such a manner that appropriate action can be taken.
The present system also enhances the automated equipment identification system through the use of hot box detector axle spacing data and car bearing temperature patterns.
Accordingly, one of the principal objects of the present invention is to provide an improved system for analyzing temperature data from the wheel bearings of trains.
Another object of the present invention is to provide an improved system for analyzing temperature data from the wheel bearings of trains using existing temperature detection systems.
A further object of the present invention is to provide a system for enhancing the existing automated equipment identification system.
Still another object of the present invention is to provide an improved system for statistically detecting wheel bearings having abnormally high temperatures or abnormally large changes in temperature.
A further object of the present invention is to provide an improved system for the detection of abnormally hot bearings while identifying and categorizing high temperature readings that are a result of non-emergency conditions.
These and other objects will be apparent to those skilled in the art.


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