Implement Vibration Sensing for Real-Time Ground Material Identification
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Solution Overview
Problem
Construction machines face challenges in accurately identifying the material or soil type during operation, which affects efficiency and precision in tasks such as digging or mapping, especially in environments with obstructions or varying soil densities.
Innovation Solution
Utilizing a vibration sensor to capture signals from the implement of a construction machine, analyzing these signals with machine-learning models to predict material type, and adjusting ground surface maps in real-time based on the analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vibration signals are captured and analyzed using machine-learning models to identify material type, then measurement precision of material type is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical material identification systems with a vibration-based sensing system coupled with machine-learning models. Vibration sensors (accelerometers, gyroscopes) capture signals during implement operation, and machine-learning algorithms process these signals to identify material type, moisture level, and compactness. This substitution reduces mechanical complexity while improving measurement precision through advanced signal processing.
Solution Approach 2:
The patent introduces vibration signals as an intermediary medium to indirectly identify material properties. Instead of directly analyzing material characteristics, the system captures vibration signals generated during implement-material interaction, then uses machine-learning models to translate these signals into material type identification. This intermediary approach enables non-contact, real-time measurement with high precision.
2Productivity
If real-time vibration signal analysis is performed during implement operation, then productivity is improved, but use of energy increases
Solution Approach 1:
The patent implements continuous vibration signal capture and analysis during implement operation, enabling real-time material identification without interrupting work. The vibration sensors continuously monitor implement vibrations, and machine-learning models process these signals on-the-fly to provide immediate material type feedback. This continuous operation maximizes productivity by eliminating idle identification time while the system leverages existing operational energy.
Solution Approach 2:
The system utilizes vibrations naturally generated during implement operation rather than requiring separate excitation sources. The implement-material interaction itself produces the vibration signals needed for identification, making the system self-powered in terms of signal generation. This approach avoids additional energy consumption for signal generation while maintaining high productivity through continuous analysis.
3Measurement precision
If vibration sensors are mounted on the implement for direct signal capture, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The patent designs the vibration sensing system to be integrated with existing implement structures, allowing the same sensor mounting infrastructure to serve multiple functions. Vibration sensors mounted on the implement not only capture material identification signals but also monitor implement health and operational conditions. This multi-functionality reduces installation complexity while maintaining high measurement precision through optimal sensor placement.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate and efficient adjustment of construction machine operations based on soil type, improving speed and path control, and providing detailed ground surface maps with material type information.
Implementation Method 1
capturing a vibration signal that is indicative of a movement of the implement
Data Source
AI summary
Described herein are systems, methods, and other techniques for determining a material type while an implement of a construction machine is interacting with a ground surface. A vibration signal that is indicative of a movement of the implement is captured. One or more features are extracted from the vibration signal. The one or more features are provided to a machine-learning model to generate a model output. The material type of the ground surface is predicted based on the model output.