Photoelectric Optic Wireless Timing Gates
In sprinting accurate timing systems are an important factor for evaluating your performance. In top speed training this requires accuracy up to 0.001s at the most closest of finishes. In training athletes use such systems to accurately measure their sprinting performance and speed to improve their training quality.
Alternative systems are available for purchase, but they are often between 400 to a 1000 euros. This was not in my track and fields team's budget. Therefore, I set out to create my own alternative timing system. The system consists of 2 modules, a starting module and a finish module. More of these modules can be added in between to potentially calculate more split times, but this documentation focuses only on the start and finish module.
The base of the system is using a Photoelectric through-beam production line sensor from SICK. I acquired this sensor second hand for cheap. This option allowed for accurate tracking upto a frequency of a 1000hz. This also meant that I did not have to create my own photo electrc through-beam sensor, which could prove to be inaccurate. Any through-beam laser sensor can work for this project.
The list of hardware requirements for this projects are as follows:
- 2x Arduino Nano
- 2x SICK Photoeletric through-beam sensor or own DIY alternative
- 2x 1602 LCD screens
- 12 volt battery pack or alternatively 6x 18650 batteries
- 2x nrf24lo1 and power board modules
- 2x 9 volt batteries
- 2x 10 uF capacitors
- 4x Any Camera tripod
- Some sort of housing/case
I started with a very crude prototype to test the concept of the system, and to verify the connectivity between the two modules. This resulted in a version on a quick scrap piece of wood, where I quickly soldered all the parts together. This version was also tested on the track to test the range of the system. Theoretically the system is rated up to 1000 meters of range, but this proved to be inconsistent based on multiple forums. The tests on track showcased latency below 5 micro seconds.
After proving the concept and testing the hardware I started modeling a final version of the system and started coding improvements to the code. This resulted in the following casing for the system:
Then it was time for the assembly of the system. The assembly and wiring is handsoldered and is pretty fragile, but it is functional for the prototype.
Once completely finished and debugging the codes with a few hickups along the way, the final system works correctly. This system was validated by a slowmotion camera setup from multiple phones to validate the system at 960 fps. The system came within 0.003 seconds of accuracy on average after 10 tests. This DIY system forms a proper alternative and mainly cheaper alternative than some of the competitors. I created this system for the total material cost of 90 euros.
Second version of the project (WIP)
After the first version of the project I started working on a second version of the project. This version is still in development, but it will feature a more robust design. During usage one of my youth athletes dropped the casing on accident, resulting in multiple solder breakages. This indicated that the improvised soldered wires are not going to be enough to make this a unsupervised version. Therefore, the goal is to create a version with a smaller housing/case and an internal custom circuit board with an integrated arduino processor. The circuit board will be created using Altium Designer. An updated version of the schematic can be seen below:
The circuit board is powered only by the 12v battery. A buck stepdown converter will be used to power both the arduino and the sensor from the same source. An adapter board is required to mitigate noise from the very picky NRF24l01 module. This adapter board is now integrated into the pcb requiring less solder work and creating more stability. To prevent solder work lock in female headers are used to provide stable and easy power transmission. The following PCB was created:
Once the PCB is finished and tested, the next step is to create a new case for the system. The case will be designed in Fusion 360 and printed using a 3D printer. The current prototype for the case is the following:
