AI Compactor Control Using Cross-Machine Compaction Data
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Solution Overview
Problem
Existing compaction control systems for construction machines, such as road rollers, lack automated control of compression settings, despite advancements in semi-autonomous and autonomous operations, leading to suboptimal compaction quality and efficiency.
Innovation Solution
A control system for compactors that integrates sensors, a processor, and a radio interface to receive internal and external process values, determining internal machine parameters for optimized compression control by using artificial intelligence to analyze and adapt settings based on both internal and external data, including compaction performance, drum frequency, and environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If automated control of compaction settings is implemented, then compaction quality and efficiency are improved, but device complexity increases due to integration of sensors, processors, and communication interfaces
Solution Approach 1:
The compactor controller automatically determines internal machine parameters by processing internal process values and external machine parameters without requiring manual intervention. The system self-adjusts compaction settings based on sensor data and communication with other construction machines, enabling autonomous operation that improves compaction quality while the complexity is managed through automated decision-making algorithms
Solution Approach 2:
The control system continuously receives internal process values from sensors and external machine parameters from other construction machines via radio interface. This feedback loop allows the processor to dynamically adjust internal machine parameters to optimize compaction quality in real-time, resolving the contradiction by using information feedback to achieve precision without proportional increase in operational complexity
2Adaptability or versatility
If external machine parameters from other construction machines are integrated, then adaptability and compaction optimization are improved, but information processing requirements and system complexity increase
Solution Approach 1:
The controller is designed to handle multiple functions: processing internal sensor data, receiving external machine parameters from other construction machines via radio interface, and determining optimal internal machine parameters. This multi-functional design improves adaptability by integrating diverse data sources while managing information processing through a unified control architecture that prevents information loss
Solution Approach 2:
The radio interface acts as an intermediary that selectively receives and transmits relevant external machine parameters between construction machines. This intermediary function filters and processes information to reduce data processing load while maintaining adaptability by only exchanging necessary compaction-related parameters rather than all possible data
3Productivity
If real-time adjustment of machine parameters is implemented, then productivity and compaction efficiency are improved, but control system complexity and computational requirements increase
Solution Approach 1:
The control system dynamically adjusts internal machine parameters in real-time based on current internal process values and external machine parameters. This dynamic adaptation improves compaction efficiency by optimizing settings during operation rather than using fixed parameters, while the complexity is managed through real-time processing algorithms that respond to changing conditions without requiring overly complex pre-computation
Data Source
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AI summary
Compactor, in particular road roller or earthmoving roller or self-propelled, autonomous or semi-autonomous roller, for compacting a subsoil with a control system comprising the following features: a sensor/data input for receiving one or more internal process values; an interface configured to receive a basic machine parameter or external machine parameter, determined on the basis of at least one external process value determined on another construction machine; a processor configured to determine an internal machine parameter on the basis of at least one of the internal process values, taking into account the basic machine parameter or the external machine parameter; a control output configured to output a control signal on the basis of the at least one determined internal machine parameter in order to control the compactor.