Autonomous Farming Machine Failure Diagnosis and Remedial Control
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Solution Overview
Problem
Conventional farming machines, especially autonomous ones, frequently encounter operational failures due to harsh conditions, leading to performance issues and significant delays in farming operations, as they require human intervention for repairs and can cause damage to fields or crops.
Innovation Solution
The farming machine is equipped with sensors and a control system that detects operational failures, configures itself to a remedial operational state to diagnose and address issues, potentially returning to a designated location if problems persist, using predefined solution operations to resolve the failure and resume normal operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If farming machines are automated to perform tasks autonomously, then productivity is improved, but reliability deteriorates due to frequent failures in harsh conditions
Solution Approach 1:
The farming machine is equipped with autonomous diagnostic and remedial capabilities that enable it to detect, diagnose, and attempt to repair its own failures without human intervention. The system monitors its operational state, identifies failures through sensor data analysis, selects appropriate remedial actions from predefined options, and executes repairs or workarounds automatically, allowing the machine to serve itself during failure events.
Solution Approach 2:
The system pre-configures multiple remedial operational states and predefined solution operations before failures occur. These include diagnostic procedures, repair sequences, and workaround protocols that are prepared in advance and stored in memory. When a failure is detected, the system can immediately execute the pre-planned remedial actions without requiring real-time human decision-making, thus maintaining productivity while addressing reliability issues.
2Reliability
If the farming machine ceases operation to address failures, then reliability is improved by preventing further damage, but loss of time increases due to repair delays
Solution Approach 1:
The autonomous diagnostic and remedial system enables the machine to immediately respond to failures without waiting for human operators. The system automatically detects failures, diagnoses their nature and severity, and executes pre-programmed repair sequences or workaround protocols, significantly reducing the time the machine remains non-operational while preventing further damage through immediate protective actions.
Solution Approach 2:
Predefined solution operations and remedial protocols are prepared in advance for various failure modes. These include immediate protective actions to prevent further damage, diagnostic procedures to quickly identify the problem, and repair sequences that can be executed automatically. This pre-planning eliminates the time required for human analysis and decision-making during failure events.
3Reliability
If human operators control farming machines, then reliability is maintained through human judgment, but productivity decreases due to manual operation limitations
Solution Approach 1:
The system transfers the diagnostic and remedial functions from human operators to the machine itself. Sensors continuously monitor operational parameters, and an onboard computer analyzes the data to detect failures, diagnose their causes, and execute appropriate remedial actions. This automation eliminates the need for constant human monitoring and intervention, allowing the machine to maintain reliable operation while significantly improving productivity through continuous autonomous operation.
Data Source
AI summary
As a farming machine travels through a field of plants, the farming machine operates in a normal operational state to perform one or more farming operations. The farming machine detects an operational failure of a component of the farming machine using measurements obtained from one or more sensors coupled to and monitoring the farming machine. The operational failure of the component impacts performance of a first farming operation of the farming operations. The farming machine configures the farming machine to operate in a remedial operational state. In the remedial operational state, the farming machine diagnoses the operational failure of the component using the obtained measurements. In the remedial operational state, the farming machine selects a solution operation to address the operational failure of the component based on the diagnosis. The farming machine performs the determined solution operation.