Spray Nozzle Outlier Detection for Targeted Application Reliability
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Solution Overview
Problem
Existing fault detection systems in agricultural spray systems struggle to reliably identify faults causing underspray or overspray during targeted spray operations, leading to inconsistent spray performance.
Innovation Solution
A system that detects statistical anomalies in nozzle instructions and generates composite scores to identify deviations, allowing for automatic adjustment or fallback modes, and utilizes machine-learned models to predict and compensate for spray performance degradation based on data from multiple vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fault detection systems are implemented to detect faults in spray components, then system reliability is improved, but the ability to reliably detect all faults causing underspray or overspray is insufficient
Solution Approach 1:
The system implements feedback by continuously monitoring spray performance data from multiple nozzles and comparing actual spray outcomes against expected performance. The control system receives feedback from spray performance sensors and automatically adjusts nozzle operations or triggers alerts when deviations are detected, creating a closed-loop system that improves both reliability and detection accuracy.
Solution Approach 2:
The patent replaces traditional mechanical fault detection methods with data-driven analytical approaches. Instead of relying on physical inspection or simple mechanical sensors, the system uses computational algorithms to analyze spray performance data, identify patterns indicating faults, and predict potential issues before they cause significant spray deviations.
2Productivity
If targeted spray operations are used to reduce crop stress and costs, then pesticide application efficiency is improved, but spray performance consistency deteriorates due to undetected faults
Solution Approach 1:
The system maintains spray performance consistency through continuous feedback monitoring of each nozzle's spray patterns and droplet distribution. When deviations are detected, the control system automatically adjusts operational parameters or alerts operators to maintain consistent spray quality throughout the field, preventing both underspray and overspray conditions.
Solution Approach 2:
The system performs preliminary fault detection and prediction before spray performance significantly deteriorates. By analyzing trends in spray performance data and identifying early signs of nozzle degradation or malfunction, the system takes preventive action to maintain consistent spray application quality throughout the operational season.
3Manufacturing precision
If individual nozzle control is implemented for precise droplet sizing, then target spray precision is improved, but system complexity increases making fault detection more difficult
Solution Approach 1:
The system manages complexity by segmenting the monitoring and control functions for each individual nozzle. Each nozzle has its own performance monitoring channel that independently tracks spray characteristics, allowing precise control and fault detection at the nozzle level without requiring complex centralized processing for the entire spray system.
Solution Approach 2:
The system implements self-service through automated monitoring and diagnostic capabilities that allow the spray system to detect and report its own faults without external intervention. Each nozzle and sensor unit independently monitors its performance and communicates status information to the control system, reducing the burden on operators and simplifying fault detection in complex systems.
Data Source
AI summary
For each of a plurality of spray nozzles of an autonomous agricultural vehicle, a set of instructions provided by the autonomous agricultural vehicle to the spray nozzle is accessed. Each instruction in the set is generated by analyzing a respective image of a portion of a geographic area captured by the autonomous agricultural vehicle. A spray performance of at least one spray nozzle from among the plurality of spray nozzles is identified as an outlier by analyzing the sets of instructions respectively provided to the plurality of spray nozzles. An action with respect to the at least one spray nozzle identified as the outlier is performed. The action may be to place the vehicle in fallback state in which a targeted spray may be switched to broadcast spray.