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.
Claims18
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 personal 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, wherein the neural network model is trained prior to deployment in the field using actual raw sensor data from a plurality of vehicles in use, at least some of the plurality of vehicles comprising different hydrostatic transmission types, respectively, and refined using raw sensor data received from vehicles having a particular make and model of the vehicle;
- 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, wherein the neural network model is trained prior to deployment in the field using actual raw sensor data from a plurality of vehicles in use, at least some of the plurality of vehicles comprising different hydrostatic transmission types, respectively, and refined using a specific raw sensor data received from vehicles having a particular make and model of the vehicle;
- 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.