AI Soil Compactor Sensing for Accurate Compaction Evaluation
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Solution Overview
Problem
Existing technologies face challenges in determining soil stiffness changes and compaction status accurately, particularly in construction sites, due to limited data points and the need to assess soil type, compactibility, and degree of compaction efficiently.
Innovation Solution
A soil compactor equipped with accelerometers, strain sensors, and a microcontroller using artificial intelligence to evaluate soil type, compactibility, and compaction degree, utilizing machine learning algorithms and regression equations for real-time analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional measurement methods are used to determine soil compaction status, then the measurement process is simple, but the accuracy of determining soil stiffness changes and compaction degree is insufficient
Solution Approach 1:
The patent replaces traditional mechanical measurement methods with an accelerometer-based system that uses vibration signals to determine soil compaction status. The accelerometer measures vibration characteristics during compaction, and these signals are processed to extract information about soil stiffness and compaction degree, eliminating the need for complex mechanical measurement apparatus.
Solution Approach 2:
The patent introduces vibration signals as an intermediary to indirectly measure soil compaction properties. Instead of directly measuring soil stiffness, the system measures the vibration response of the compaction device and uses signal processing to infer compaction status, providing a non-intrusive measurement approach.
2Measurement precision
If artificial intelligence algorithms are trained with millions of data points, then the evaluation accuracy is high, but the data collection requirement is excessive for practical soil compaction applications
Solution Approach 1:
The patent performs preliminary processing of vibration signals by extracting relevant features (frequency, amplitude, time-domain characteristics) before feeding them to the AI algorithm. This preprocessing step concentrates the essential information into a compact feature set, allowing accurate soil evaluation with fewer raw data points.
Solution Approach 2:
The patent extracts key features from the vibration signals, such as frequency spectrum characteristics, amplitude modulation patterns, and time-domain statistics. By taking out only the most relevant features rather than using all raw data, the system achieves high evaluation accuracy with reduced data requirements.
3Measurement precision
If multiple sensors are used to measure soil properties, then the measurement accuracy is improved, but the device complexity and cost increase
Solution Approach 1:
The patent makes the accelerometer serve multiple functions: it measures vibration during compaction, characterizes the soil being compacted, and monitors compaction progress. This single sensor replaces what would traditionally require multiple specialized sensors, reducing system complexity while maintaining measurement accuracy.
Solution Approach 2:
The patent uses the dynamic vibration response of the compaction device to extract multiple soil properties. By analyzing different aspects of the vibration signal (frequency, amplitude, temporal patterns), the system derives information about soil stiffness, density, and compaction status from a single dynamic measurement source.
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
Accurately determines soil type, compactibility, and compaction degree with improved accuracy and reduced data requirements, enabling efficient soil compaction processes.
Implementation Method 1
The measurement sensors include at least three accelerometers (ACC_1, ACC_2, ACC_3)
Data Source
Figure 1a
Figure 1b
Figure 2a
AI summary
A soil compactor for measuring and evaluating soil, a computer-implemented method for performing measurement and evaluation of soil, a computer program and a computer-readable medium are provided. The soil compactor comprises a computer, such as a microcontroller, the computer comprising at least one processor and memory, a soil contact plate. The soil compactor further comprises a motor attached to the soil contact plate for bringing the soil contact plate into contact with the soil in order to compact the soil and a plurality of measurement sensors (ACC1-ACC6) coupled to the computer, the measurement sensors including at least three accelerometers. The memory comprises an artificial intelligence module configured to receive measurement information from the measurement sensors and to perform an evaluation of the soil, wherein the evaluation includes determining one or more of the following based on the measurement information: a soil type of the soil, wherein the soil type is one of the following: non-cohesive, cohesive, mixed-granularity, whether the soil is compactible, and a degree of compaction of the soil.