Tether-free Driveline Control for Water Propulsion Devices

Abstract: For many machines, safety requires the constant presence of an operator, with the risk of damage or danger if the operator is unintentionally absent. Dead man’s switches (DMS) are commonly used to halt operations if this absence is detected, often relying on physical elements like leashes or buttons. However, these solutions can hinder operator convenience and equipment aesthetics. For devices with electrical brushless DC motors, motor data can be generated and analyzed. This opens the door for machine learning models to discern patterns signifying operator presence. The potential benefits are most evident in personal devices, where user activity directly influences motor data. This study delves into the feasibility of a software-based, tether-free, DMS for a jet surfboard. Initially, user opinions on the existing leash-and-magnet DMS were gathered, assessing its impact on user experience through surveys and interviews. Results showed that a tether-free DMS solution would improve user experience mainly in regards to convenience and comfort. The existing DMS is regarded as simple, safe and reliable - characteristics that would need to be reflected by a tether-free DMS. Subsequently, machine learning models were constructed to analyze ride log data in order to detect surfer presence. Two approaches were explored, detecting when someone is falling off the board, and detecting when the board is running with no one on it. It was found that strong negative and positive trends in the motor data (corresponding to deceleration and acceleration) were the characteristics that the models mostly identified with fall-off and off-board data, which resulted in some misclassifications. Results show that there are some possible differentiating features between different activities on board in some cases, but the models ultimately fall short of the performance requirements for a DMS.