Road Quality Assessment via Suspension Strut Sensors
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Solution Overview
Problem
Current systems for managing vehicle fleets in open pit mines lack advanced analytics to improve fleet operations beyond maintenance and warranty monitoring, failing to effectively assess and address road quality issues in real-time.
Innovation Solution
Implementing a method that tracks vehicle position and suspension strut parameters to determine road quality, using sensors and telecommunications networks to transmit data for real-time analysis and maintenance recommendations, allowing for automated scheduling of road maintenance operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vehicle diagnostics are used for maintenance monitoring, then vehicle reliability is improved, but road quality assessment capability is insufficient
Solution Approach 1:
The vehicle diagnostic system is extended to perform multiple functions: traditional maintenance monitoring plus road quality assessment. The same suspension strut sensors and vehicle networks are utilized to assess both vehicle health and road conditions, eliminating the need for separate dedicated road assessment equipment while enhancing system versatility.
Solution Approach 2:
The vehicle's existing suspension system and sensors are leveraged to assess road quality during normal vehicle operation. The system uses the vehicle's own movement and suspension characteristics to infer road conditions, eliminating the need for external road testing equipment or separate assessment vehicles.
2Reliability
If comprehensive vehicle data is collected, then maintenance monitoring is improved, but data processing complexity increases
Solution Approach 1:
From the comprehensive vehicle data collected by CAN systems, the analysis extracts and focuses on specific parameters relevant to road quality assessment - primarily suspension strut parameters - while maintaining the broader maintenance monitoring context. This selective extraction reduces processing complexity by concentrating on key indicators rather than processing all vehicle data uniformly.
Solution Approach 2:
The data processing approach applies different analysis methods to different data types: suspension strut parameters are analyzed specifically for road quality assessment, while other vehicle parameters are processed for maintenance monitoring. This localized processing strategy reduces overall complexity by treating data streams according to their specific purposes rather than applying a single complex processing framework to all data.
3Productivity
If road quality assessment is implemented, then fleet operations are improved, but measurement and detection difficulty increases
Solution Approach 1:
The suspension strut parameters serve as an intermediary indicator to indirectly measure road quality. Instead of directly measuring road surface characteristics with complex equipment, the system uses the vehicle suspension's response to road conditions as a proxy indicator, significantly simplifying the detection and measurement process while maintaining assessment accuracy.
Data Source
AI summary
A system for determining road quality includes a vehicle equipped with sensors to detect a position of the vehicle on the road and a suspension strut parameter indicative of road quality. The suspension strut parameter may be suspension strut pressure or suspension strut cylinder stroke. A threshold range is established outside of which an absolute value of the suspension strut parameter is associated with poor road quality. A computerized system generates a heat map to display relative quality of road segments.