Work Machine Parameter Identification Using Time Series Data
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Solution Overview
Problem
Simulations of construction performance using design values may not accurately represent actual work machine performance due to variations in site conditions and operator skills, leading to discrepancies in parameters such as traveling speed and time.
Innovation Solution
A parameter identifying device that includes a work state identifying unit and a parameter identifying unit, which utilize time series data of position, azimuth, and speed to determine work states and corresponding parameters for work machines like hydraulic excavators, bulldozers, and dump trucks, allowing for more accurate simulation of construction performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If simulation is performed using design values of work machine parameters, then the simulation setup is simple and quick, but the simulation results may be estranged from actual construction progress status
Solution Approach 1:
The system collects actual operation data from work machines during construction activities and feeds this information back to update simulation parameters. Position data, azimuth data, and speed data are continuously monitored and used to adjust simulation models, ensuring they reflect real-world performance rather than relying solely on design values.
Solution Approach 2:
The system dynamically changes simulation parameters based on actual measured data from work machines. Instead of using fixed design values, the system adjusts parameters such as traveling speed, work amount per unit time, and operational efficiency based on real-time or historical operation data, making the simulation more representative of actual construction performance.
2Device complexity
If parameters are set based on design values, then the simulation model is easy to establish, but it does not account for variations in site conditions and operator skills
Solution Approach 1:
The system enables work machines to self-report their operational parameters through onboard sensors and data collection systems. Position data, azimuth data, and speed data are automatically captured by the machines themselves during operation, eliminating the need for manual data entry or complex external monitoring systems.
Solution Approach 2:
The system is designed to collect and process data from multiple types of work machines (excavators, bulldozers, dump trucks, etc.) using a unified data collection framework. The same data processing methodology applies across different machine types and construction activities, making the system adaptable to various site conditions and machine configurations without requiring separate specialized systems.
3Measurement precision
If actual operation data is collected and used for parameter identification, then simulation accuracy improves, but data collection and processing requirements increase
Solution Approach 1:
The system replaces manual data collection methods with automated electronic sensing and data transmission. Onboard sensors, GPS receivers, and communication systems automatically capture position, azimuth, and speed data, eliminating the need for manual measurement and recording processes.
Solution Approach 2:
The system creates digital copies of actual work machine operations through data collection and processing. Instead of physically tracking each machine, the system generates digital representations of machine performance through collected data, which are then used to update simulation models. This digital copying approach simplifies data management while maintaining accuracy.
Data Source
AI summary
A work state identifying unit identifies work states of a work machine. A parameter identifying unit identifies a parameter related to a work amount per unit time of the work machine or a parameter related to a speed of the work machine for each of the identified work states on the basis of a time series of position data, azimuth data, or speed data of the work machine.