Predictive failure system, apparatus and method for hydrostatic transmissions
Assignee2541980 Alberta LTD.
InventorMike Ball
Life of this patent
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Abstract
A system, apparatus and method providing a predictive maintenance system for a vehicle comprising a hydrostatic transmission. Sensors are installed on a vehicle to monitor various operating characteristics of a hydrostatic transmission. The sensors generate raw sensor data that is received by an onboard edge processing unit that applies the signals to a neural network model to derive predictions of potential future mechanical failures of the hydrostatic transmission. The inferences and raw sensor data may be sent to a remote data center via a personal communication device associated with the vehicle, to further train the neural network model.
Claims20
A predictive maintenance system for detecting future mechanical failures of a hydrostatic transmission, comprising:
- a plurality of sensors installed onto one or more areas of the hydrostatic transmission, configured to generate raw sensor data representative of a plurality of sensed mechanical conditions of the hydrostatic transmission, respectively;
- and
- an edge processing unit coupled to the plurality of sensors and comprising a communication interface for transmitting information to a person communication device, configured to:
- receive the raw sensor data from the plurality of sensors;
- process the raw sensor data using a neural network model specifically trained to predict future potential mechanical failures of the hydrostatic transmission;
- generate an inference based on the raw sensor data;
- and
- transmit an alert via the communication interface when the inference indicates that a future potential mechanical failure of the hydrostatic transmission may occur.
A method for predicting future mechanical failures of a hydrostatic transmission of a vehicle, comprising:
- training a neural network model to detect anomalies in one or more physical operating characteristics of the hydrostatic transmission;
- loading the trained neural network model onto an edge processing unit co-located with the vehicle;
- receiving, by the edge processing unit, raw sensor data from a plurality of sensors mounted to the hydrostatic drive;
- determining an inference by the neural network model based on evaluating the raw sensor data, wherein the inference indicates a potential future mechanical failure of the hydrostatic transmission;
- and
- sending, by the edge computing device, an alert of the inference to a personal communication device associated with the vehicle.
Dependencies are inferred from the claim text.