Determining drive system anomalies based on power and/or current changes in an irrigation system
AssigneeHeartland AG Tech, Inc.
InventorsRussell Sanders, Jeremie Pavelski
Life of this patent
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Abstract
A predictive maintenance system for an irrigation system includes one or more sensors configured to generate a signal indicative of abnormal operation within the irrigation system, the sensors electrically coupled to a drive system, a processor, and a memory. The memory includes instructions stored thereon, which when executed by the processor cause the predictive maintenance system to receive the generated signal, determine abnormal operation of the drive system based on the generated signal, and predict, by a machine learning model, a maintenance requirement of the drive system based on the determined abnormal operation.
Claims20
A predictive maintenance system for an irrigation system including a drive system, the predictive maintenance system comprising:
- at least one sensor configured to measure an amount of a reactive power and generate a signal indicative of abnormal operation within the irrigation system, the sensor electrically coupled to the drive system;
- a processor;
- and
- a memory, including instructions stored thereon, which when executed by the processor cause the predictive maintenance system to:
- receive the generated signal;
- determine a tire condition of a tire of the drive system based on the generated signal;
- and
- predict, by a machine learning model, a maintenance requirement of the drive system based on the determined tire condition, wherein the maintenance requirement is predicted by:
- generating, based on the received sensor signal, a data structure that is formatted to be processed through one or more layers of a machine learning model, wherein the data structure includes one or more fields structuring data;
- processing data that includes the data structure, through each of the one or more layers of the machine learning model that have been trained to predict a likelihood that a particular piece of the drive system may require maintenance;
- and
- generating, by an output layer of the machine learning model, an output data structure, wherein the output data structure includes one or more fields structuring data indicating a likelihood that a particular piece of equipment may require maintenance.
A computer-implemented method for predictive maintenance for an irrigation system, the computer-implemented method comprising:
- receiving a signal, sensed by a sensor coupled to a drive system of the irrigation system, the signal indicative of a condition of abnormal operation of the drive system, the irrigation system configured to irrigate a predetermined area, wherein the sensor is configured to measure an amount of a reactive power;
- determining a tire condition of a tire of the drive system;
- and
- predicting, by a machine learning model, a maintenance requirement of the drive system based on the determined tire condition,
- wherein the maintenance requirement is predicted by:
- generating, based on the received sensor signal, a data structure that is formatted to be processed through one or more layers of a machine learning model, wherein the data structure includes one or more fields structuring data;
- processing data that includes the data structure, through each of the one or more layers of the machine learning model that have been trained to predict a likelihood that a particular piece of the drive system may require maintenance;
- and
- generating, by an output layer of the machine learning model, an output data structure, wherein the output data structure includes one or more fields structuring data indicating a likelihood that a particular piece of equipment may require maintenance.
A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause the processor to perform a method for predictive maintenance for an irrigation system, the method comprising:
- receiving a signal, sensed by a sensor coupled to a drive system of the irrigation system, the signal indicative of a condition of abnormal operation of the drive system, the irrigation system configured to irrigate a predetermined area, wherein the sensor is configured to measure an amount of a reactive power;
- determining a tire condition of a tire of the drive system based on the received signal;
- predicting, by a machine learning model, a maintenance requirement of the drive system based on the determined the tire condition;
- and
- displaying on a display the predicted maintenance requirement of the drive system,
- wherein the maintenance requirement is predicted by:
- generating, based on the received sensor signal, a data structure that is formatted to be processed through one or more layers of a machine learning model, wherein the data structure includes one or more fields structuring data;
- processing data that includes the data structure, through each of the one or more layers of the machine learning model that have been trained to predict a likelihood that a particular piece of the drive system may require maintenance;
- and
- generating, by an output layer of the machine learning model, an output data structure, wherein the output data structure includes one or more fields structuring data indicating a likelihood that a particular piece of equipment may require maintenance.
Dependencies are inferred from the claim text.