System for Accurate Measurement of Vehicle Speeds for Low Speed Industrial Applications

• US 20140313503A1
• Filed: 03/11/2014
• Published: 10/23/2014
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Kanawaha Scales & Systems Incorporated
• Original Assignee: Kanawaha Scales & Systems Incorporated
• Inventors: Bennett, Duane Lee, Barker, Robert Emil Jr., Foley, James Troy
• Granted Patent: US 9,573,607 B2
• Time in Patent Office: Days
• US Class Current: 356/28
• CPC Class Codes: B61L 27/40 Handling position reports or trackside vehicle data
• CPC Class Codes: G01P 5/18 by measuring the time taken to traverse a fixed distance
• CPC Class Codes: G01S 17/42 Simultaneous measurement of distance and other co-ordinates indirect measurement G01S17/46
• CPC Class Codes: G01S 17/58 Velocity or trajectory determination systems; Sense-of-movement determination systems
• CPC Class Codes: G01S 17/88 Lidar systems specially adapted for specific applications
• CPC Class Codes: G01S 7/4808 Evaluating distance, position or velocity data
• CPC Class Codes: G01S 7/497 Means for monitoring or calibrating

Abstract

A continuous scanning side laser detector system and method for real time, instantaneous accurate speed and direction measurement of a slow moving bulk material transport vehicle through a bulk material processing station.

Claims

1. A system for instantaneous, real-time speed measurement of a select low speed transport vehicle moving in a linear direction of travel and proximate to a bulk material processing station, comprising:

a stationary scanning laser and detecting sensor positioned to one side of and generally perpendicular to the direction of travel, said scanning laser and detecting sensor capable of generating a plurality of raw point scan measurement signals over a select arc;

a computing device for receiving the raw point scan measurement signals and applying at least one algorithm to said plurality of raw point scan measurements to modulate said scan measurements signals and provide a first data set representing a flattened two-dimensional linear representation of travel distance of the low speed transport vehicle, saving said first data set in a memory queue, comparing said first data set with a plurality of previously saved datasets in said memory queue using a root mean square deviation algorithm, determining if said first data set exceeds a preselected deviation threshold, accepting said first dataset when said predetermined deviation threshold is not exceeded, calculating the distance traveled by said vehicle from said first data set and computing the speed of the vehicle to produce a unique speed profile representative of the transport vehicle.

2. The system according to claim 1 where the stationary scanning laser and detecting sensor continuously detects the target vehicle travel through a select arc.

3. The system according to claim 1 where the stationary scanning laser has a radial scan arc of 90°

and said detecting sensor provides continuous detection.

4. The system according to claim 3 where the scanning cycle rate is 50 Hz.

5. The system according to claim 2 where the computing device filters noise generated by vehicle vibration from the flattened two-dimensional linear representation prior to storing in the memory queue.

6. The system according to claim 2 where the computing device calculates a rolling average of said transport vehicle based on a plurality of sequential speed profile computations.

7. The system according to claim 1 further comprising a tri-axis adjuster for alignment and leveling of the detector with the scanning laser system.

8. The system according to claim 7 where said scanning laser and detecting sensor are situated in a protective enclosure and disposed at a height selected to avoid ground level obstruction interference.

9. The system of claim 5 where for speed differences resulting from differential spacing occasioned by stretching between a plurality of railcars in a train is computed.

10. A system for instantaneously and in real time determining the velocity of a rail car traveling linearly and proximate to a bulk material processing station, comprising:

a radial scanning laser detector positioned perpendicularly to the line of travel of and for continuously scanning the rail car through a select arc corresponding to the sensor window of the laser detector; and

a computing means for receiving detected laser signals from the detector in the window, storing the signals, trigonometrically flattening the signals to produce signal dataset corresponding to a linear representation of distance, filtering noise from the signal dataset, comparing the signal dataset with previously obtained signal datasets, selecting matched datasets with minimum sum errors, determining the direction of movement and calculating the real-time velocity of the target railcar by dividing the calculated distance traveled by the elapsed time between the matched datasets.

11. The system of claim 10 further comprising an alignment controller for the radial scanning laser detector connected to the computing device to maintain alignment.

12. The system of claim 10 where the radial laser detector scanner is housed in a protective enclosure and is height adjustable.

13. The system of claim 10 where the computing means is connected to a communications up-link for electronically relaying the obtained speed information.

14. The system of claim 10 where the radial laser detector is sealed in a heated, environmentally sealed housing electrically connected to a power source, and mounted on a tri-axis adjustable mounting providing precise alignment and leveling relative to the target railcar.

15. A method for precisely determining the speed instantaneously and in real time of a bulk carrier transport vehicle proximate to a bulk material processing station during linear travel, comprising the steps of:

a) positioning a radial scanning laser and detector perpendicular to the direction of linear travel of the vehicle;

b) scanning the vehicle while in a detection window with the laser through a select arc;

c) detecting returned signals from the laser and timestamps thereof to obtain a plurality of data points;

d) feeding the plurality of data points to a computing device;

e) applying a trigonometric algorithm to flatten the plurality of data points into a first dataset corresponding to a two-dimensional representation of speed;

f) saving the first dataset into a memory queue in said computing device;

g) comparing the first dataset with a previously obtained dataset and applying a root mean square deviation algorithm to determine if said first dataset falls within a maximum deviation threshold to qualify for further processing;

h) calculating the X axis translation of a qualifying dataset corresponding to the travel distance of the vehicle;

i) computing the time difference between a qualifying dataset and previously qualified datasets; and

j) computing the vehicle speed by dividing the X-axis translation by the elapsed time of between the qualified datasets.

16. The method of claim 15 further where an algorithm based on root mean square deviation is used for dataset comparison.

17. The method of claim 15 further comprising the step of damping noise in the first flattened dataset.

18. The method of claim 17 further comprising the step of calculating rolling averages of the vehicle speed.

19. The method of claim 18 further comprising the step of providing the calculated rolling average to a controller for the bulk material processing system.

20. The method of claim 18 further comprising the step of providing the calculated rolling averages of the vehicle speed to a remote monitor system.