Work Machine Monitoring Using 3D Terrain Profiles and Simulation
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Solution Overview
Problem
Existing work machine monitoring systems are costly and complex, with high computational requirements, and do not effectively utilize predictive modeling or measured data for performance evaluation.
Innovation Solution
A method and system that uses a surveying device to measure the three-dimensional surface profile of a worksite, processing this data to simulate the operation of work machines and monitor operating conditions such as stress and strain, allowing for predictive maintenance, route optimization, and duty segment assignment based on real-time data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are used to monitor operating conditions, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent creates a virtual copy of the physical machine through digital twins and simulation models. Instead of using multiple physical sensors to measure operating conditions, the system uses a digital model that replicates machine behavior and predicts operating conditions based on limited input data, thereby reducing sensor requirements while maintaining monitoring accuracy
Solution Approach 2:
The patent replaces physical sensing systems with computational modeling and simulation algorithms. Rather than mechanically measuring stress, strain, and operating conditions through multiple sensors, the system uses software-based machine models that calculate these parameters from basic operational data, eliminating the need for complex sensor arrays
2Reliability
If multiple sensors are deployed for comprehensive monitoring, then reliability is improved, but production cost increases
Solution Approach 1:
The patent uses digital twins to create virtual representations of machine components and systems. These digital copies allow for virtual testing, prediction, and monitoring without requiring expensive physical sensor installations, thereby maintaining reliability while reducing production costs
Solution Approach 2:
The machine model automatically monitors and predicts its own operating conditions and potential failures without requiring external sensing infrastructure. The system uses its own operational data to feed the simulation model, which then self-diagnoses and predicts maintenance needs, eliminating the need for costly external monitoring hardware
3Productivity
If real-time operating condition monitoring is implemented, then productivity is improved through predictive maintenance, but computational requirements increase
Solution Approach 1:
The patent performs computational analysis in advance by running simulation models that predict future operating conditions and potential failures. By pre-calculating maintenance needs and machine performance predictions before actual failures occur, the system enables proactive maintenance scheduling that improves productivity without requiring continuous high-power computational processing during operation
Solution Approach 2:
The system performs computational simulations at selective intervals rather than continuously, using the machine model to predict operating conditions based on representative samples of operational data. This partial action approach provides sufficient predictive maintenance capability while significantly reducing overall computational energy requirements compared to continuous real-time simulation
Data Source
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AI summary
A surveying device (15) is operated to measure a surface profile of a terrain (13) of a worksite (14) and generate surface profile data indicative of the surface profile. A work machine (11) is operated to move along a route (12) over the terrain (13) in accordance with an operating parameter and generates machine operational data indicative of the operating parameter. A navigation system determines the route (12) and generates route data. A processing unit processes the route data, machine operational data and surface profile data to generate monitored operating condition data indicative of a monitored operating condition of the machine (11).