Wisconsin Patent of the Month – May 2023
Irrigation systems are vital for maintaining healthy crops and maximizing agricultural productivity. Since they are integral, breakdowns in these systems can cause significant delays, increased costs, and disruptions to the farming process. To address this challenge, Heartland Ag Tech has developed a new predictive maintenance system for irrigation systems.
Heartland’s predictive maintenance system utilizes sensors and advanced algorithms to monitor the operation of the irrigation system in real-time. By observing the system’s performance and comparing it to predefined parameters, the system can detect abnormal operation and predict maintenance requirements before a breakdown occurs.
The heart of the system lies in the movable end gun, a crucial component of the irrigation system. Sensors are strategically placed on the end gun to capture data on its movement, positioning, and other operational parameters. These sensors include encoders, pressure sensors, flow meters, gyroscopes, and more.
The generated signals from the sensors are processed and analyzed using machine learning models, such as deep learning networks or classical machine learning algorithms. The models compare the observed data with expected patterns and determine whether the end gun is exhibiting abnormal behavior.
Once abnormal operation is detected, the predictive maintenance system can predict the specific maintenance requirements of the end gun. It can estimate parameters like drive arm impact frequency, acceleration magnitude, angular rates, heading change rates, time per pass, or time to flip a reversing lever. This information is crucial for maintenance planning and scheduling.
Heartland’s predictive maintenance system goes beyond just monitoring the end gun itself. It can also integrate external data sources like weather stations, soil moisture sensors, topographical maps, and temperature sensors. By incorporating these additional inputs, the system can provide even more accurate predictions and maintenance recommendations.
The results of the predictive maintenance analysis can be displayed on a user-friendly interface, allowing farmers and irrigation system operators to stay informed about the maintenance requirements of their equipment. This proactive approach to maintenance helps prevent unexpected breakdowns, reduces downtime, and optimizes the overall performance of the irrigation system.
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