Road Construction Machine Learning Mode for Wheel and Roller Adjustment
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Solution Overview
Problem
Existing self-propelled road construction machines require operators to precisely adjust the position of wheels or crawler tracks, the height of the milling/mixing roller, and the machine frame relative to the ground surface, posing a challenge for quick familiarization and safe operation.
Innovation Solution
A self-propelled road construction machine equipped with a controller that generates control command signals for drives and actuators based on operating states, a human-machine interface for visualization of instruction data sets, and a learning mode that guides operators through specific machine functions like height and inclination adjustments, using a state monitoring device to detect operating states and provide feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If operators manually adjust the position of wheels, height of milling roller, and alignment of machine frame without guidance systems, then the machine can operate with simpler control systems, but operators require extensive training time and face higher safety risks
Solution Approach 1:
The patent implements a state monitoring device that continuously detects the actual operating state of the machine and compares it with the desired state. This feedback loop enables the control system to automatically generate corrective control commands, thereby improving operational safety and precision without requiring extensive operator training or intervention.
Solution Approach 2:
The control system is designed to autonomously monitor its own state and self-correct deviations from the desired operating parameters. The system independently generates control commands based on detected operating states, eliminating the need for constant manual adjustment and reducing safety risks associated with manual operations.
2Ease of operation
If operators practice machine functions under realistic conditions without risk, then learning efficiency improves, but physical practice carries inherent safety risks
Solution Approach 1:
The patent creates a virtual copy of the machine's operating environment through the human-machine interface, which displays visual representations of the machine and its components. Operators can practice controlling the virtual machine without physical risks, while the system learns from these practice sessions to improve real-world operation guidance.
Solution Approach 2:
The human-machine interface acts as an intermediary between the operator and the actual machine. It provides a safe intermediate environment for practice and learning, allowing operators to become familiar with machine functions before operating the physical equipment, thereby reducing safety risks during actual operation.
3Manufacturing precision
If the system provides detailed real-time guidance through human-machine interface, then operator precision improves, but information processing load increases
Solution Approach 1:
The patent divides the information presentation into segmented, modular components displayed on the human-machine interface. Instead of overwhelming the operator with all possible information simultaneously, the system presents relevant guidance information in discrete segments based on the current operating context and operator needs, reducing cognitive load while maintaining precision.
Solution Approach 2:
The system provides partial information guidance rather than complete exhaustive instructions. It offers just enough real-time feedback and guidance necessary for precise operation without overwhelming the operator with excessive information, allowing the operator to use their own judgment and experience while receiving targeted assistance.
Data Source
AI summary
The invention relates to a road construction machine having a controller 27 which is configured such that control command signals are generated for drives and actuators 8, 9, 16, 20A, 20B assigned to the wheels 4, 5, 6, 7 and/or the milling/mixing roller 18. Additionally provided are: a human-machine interface 26 that interacts with the controller 27 and a memory device 30that interacts with the controller as well as a state monitoring device 32 that interacts with the controller, which monitoring device detects an operating state or operating mode of the drives and actuators. The road construction machine is characterized in that a plurality of instruction data sets is stored in the memory device, said data sets each containing data for an instruction to be visualized using the human-machine interface. The controller provides a learning mode comprising a plurality of lessons for adjusting the position of the wheels and/or the height of the milling/mixing roller and is configured such that, depending on an operating state or operating mode of the drives and actuators detected by the state monitoring device, a selection of a specific data set is made from the instruction data sets stored in the memory device, and the instruction corresponding to the selected instruction data set is visualized using the human-machine interface. In addition, depending on the command entered with the human-machine interface after the visualization of the instruction, the controller generates for the drives and actuators the control command signals corresponding to the command entered, so that the wheels and/or milling/mixing roller move.