Systems Automation

Seismic's exosuits integrated load cells to measure the force exerted by the wearer. A load cell outputs ADC (analog-to-digital) values that need to be calibrated to represent a tangible force value. Cumbersome tasks were performed to calibrate the load cells.  To automate some of these tasks, I developed a force calibration algorithm in Python with Matplotlib that was integrated into a command-line interface (CLI) for the engineering team to automate their motor sequence workflow. The algorithm calibrates force sensors by automating the motors' movement along a spring and calculating the force exerted in-lbs in correlation to the spring constant.

HOW IT WORKS

Figure: Example of data used to calibrate the loadcells. (A) data of the displacement the motor moved, the weight calculated from the motor system's displacement, and the ADC value of the load cell. (B) plot showing a linear regression of the weight calculated from the motor system's displacement vs. the ADC values of the load cell to create an equation showing the relationship between the two. 

Testing

While at Seismic, I was involved in the focus groups and production build of 30 exosuits. I assisted in fixing and testing electronics from the assembly line. The debugging and repair of electromechanical systems​ included:

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• Testing electromechanical systems such as dc motors, solenoids, and twisted-pair strings to ensure the system's working order.

• Making sure CAN communications were properly terminated.

• Analyzing PCB boards to solve different fault errors on chips by checking continuity, power rails, schematics, and datasheets.

• Wearing the system to make sure different functions were working properly,

• Flashing new firmware on boards​.

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