Positional load door monitoring system
Systems, methods, and non-transitory machine-readable media for tracking the state of a rail car are disclosed. In one or more example embodiments, a device may use sensors such as a spring height sensor or a time of flight sensor to determine a status of a load car, which may be associated with a location. The system may determine a delivery event at the location. This data may be correlated with spring usage data.
1 . A computing device associated with a rail car, the computing device comprising:
a time of flight sensor;
a time of flight signal emitter;
a processor; and
a memory storing instructions that, when read by the processor, cause the computing device to:
send, using the time of flight signal emitter, a pulsed time of flight signal;
determine, using the time of flight sensor and based on a reflection of the pulsed time of flight signal being in phase with the pulsed time of flight signal, that the reflection is a genuine signal;
determine, using the time of flight sensor and based on the reflection, a time of flight reading of a spring associated with the rail car;
compare the time of flight reading with a calculated spring value;
determine, based on the comparing, a spring height;
determine, based on spring usage data, an expected height value for the spring, wherein the expected height value corrects for fatigue of the spring; and
determine, based on the spring height and the expected height value, a load for the rail car.
2 . The computing device of claim 1 , wherein the instructions, when read by the processor, further cause the computing device to determine a location a location of the rail car based on a global positioning system coordinate associated with the time of flight reading.
3 . The computing device of claim 1 , wherein the instructions, when read by the processor, further cause the computing device to:
determine an ambient light reading associated with the rail car; and
determine a door opening based on the ambient light reading.
4 . The computing device of claim 3 , wherein the instructions, when read by the processor, further cause the computing device to determine, based on the load and the door opening, a delivery event associated with the rail car.
5 . The computing device of claim 1 , wherein the spring usage data comprises at least one of:
previous car load data,
lifetime spring compression data,
car travel distance data, or
spring deformity data.
6 . The computing device of claim 1 , wherein the instructions, when read by the processor, further cause the computing device to determine the spring height by comparing, based on the time of flight reading, a tare state of the spring with a load level of the spring.
7 . The computing device of claim 1 , wherein the instructions, when read by the processor, further cause the computing device to:
determine an additional time of flight reading associated with a door for the rail car; and
determine the door opening based on the additional time of flight reading.
8 . A computer-implemented method for detecting a rail car event, comprising:
sending, using a time of flight signal emitter, a pulsed time of flight signal;
determining, using a time of flight sensor and based on a reflection of the pulsed time of flight signal being in phase with the pulsed time of flight signal, that the reflection is a genuine signal;
determining, using the time of flight sensor and based on the reflection, a time of flight reading of a spring associated with the rail car;
comparing the time of flight reading with a calculated spring value;
determining, based on the comparing, a spring height;
determining, based on spring usage data, an expected height value for the spring, wherein the expected height value corrects for fatigue of the spring; and
determining, based on the spring height and the expected spring height value, a load for the rail car.
9 . The computer-implemented method of claim 8 , further comprising determining a location a location of the rail car based on a global positioning system coordinate associated with the time of flight reading.
10 . The computer-implemented method of claim 8 , further comprising:
determining an ambient light reading associated with the rail car; and
determining a door opening based on the ambient light reading.
11 . The computer-implemented method of claim 10 , further comprising determining, based on the load and the door opening, a delivery event associated with the rail car.
12 . The computer-implemented method of claim 8 , wherein the spring usage data comprises at least one of:
previous car load data,
lifetime spring compression data,
car travel distance data, or
spring deformity data.
13 . The computer-implemented method of claim 8 , wherein the determining the spring height comprises comparing, based on the time of flight reading, a tare state of the spring with a load level of the spring.
14 . The computer-implemented method of claim 8 , further comprising:
determining an additional time of flight reading associated with a door for the rail car; and
determining the door opening based on the additional time of flight reading.
15 . A non-transitory machine-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform steps comprising:
determining, based on a reflection of a pulsed time of flight signal being in phase with the pulsed time of flight signal, that the reflection is a genuine time of flight signal;
determining, using a sensor comprising a time of flight sensor and based on the reflection, a time of flight reading of a spring associated with a rail car;
determining, based on the sensor, an ambient light reading associated with the rail car;
determining a door opening based on the ambient light reading;
comparing the time of flight reading with a calculated spring value;
determining, based on the comparing, a spring height;
determining, based on spring usage data, an expected height value for the spring, wherein the expected height value corrects for fatigue of the spring; and
determining, based on the spring height and the expected spring height, a load for the rail car.
16 . The non-transitory machine-readable medium of claim 15 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to further perform steps comprising:
determining a location a location of the rail car based on a global positioning system coordinate associated with the time of flight reading.
17 . The non-transitory machine-readable medium of claim 15 , wherein the time of flight reading and the ambient light reading are determined using the same hardware.
18 . The non-transitory machine-readable medium of claim 15 , wherein the spring usage data comprises at least one of:
previous car load data,
lifetime spring compression data,
car travel distance data, or
spring deformity data.
19 . The non-transitory machine-readable medium of claim 15 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to further perform determining the spring height by comparing, based on the time of flight reading, a tare state of the spring with a load level of the spring.
20 . The non-transitory machine-readable medium of claim 15 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to further perform steps comprising:
determining an additional ambient light reading associated with a door for the rail car; and
determining the door opening based on the additional ambient light reading.