Vehicle Axle Sensor System for Failure Mode Discrimination
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Solution Overview
Problem
Off-highway vehicles face challenges in efficiently monitoring and predicting the health status of their axles, leading to suboptimal maintenance and increased costs due to time-based maintenance schedules that do not account for varying usage conditions.
Innovation Solution
A sensor system comprising axle sensors, a data processing unit, and memory that detects anomalies in axle data by comparing real-time data to reference models, allowing for the identification of specific failure modes and issuing alerts through various output devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If time-based maintenance schedules are used, then maintenance simplicity is improved, but maintenance efficiency and reliability deteriorate due to varying usage conditions
Solution Approach 1:
The patent replaces the mechanical time-based maintenance scheduling system with a sensor-based condition monitoring system. Sensors continuously collect real-time data on axle parameters (vibration, temperature, pressure), and this data is processed to determine actual axle health status, enabling maintenance decisions based on actual condition rather than predetermined time intervals.
Solution Approach 2:
The system implements continuous feedback through sensors that monitor axle parameters in real-time. The collected data is fed back to the control unit, which compares current readings against reference values and historical data, allowing dynamic adjustment of maintenance timing based on actual axle condition rather than fixed schedules.
2Measurement precision
If multiple sensors are deployed for comprehensive monitoring, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The control unit serves multiple functions: it processes data from various sensor types (vibration, temperature, pressure sensors), stores reference values, performs anomaly detection, and generates maintenance alerts. This multi-functional approach consolidates complexity into a single processing unit rather than requiring separate systems for each function.
Solution Approach 2:
The patent combines multiple sensing functions (vibration monitoring, temperature sensing, pressure detection) into an integrated sensor network that feeds into a single control unit. This merging approach allows comprehensive monitoring while managing complexity through centralized processing rather than distributed independent systems.
3Measurement precision
If real-time data analysis is performed, then failure prediction accuracy is improved, but processing time and energy consumption increase
Solution Approach 1:
The control unit performs partial data analysis by comparing sensor readings against pre-stored reference values and thresholds. Rather than continuously analyzing all raw data in real-time, the system selectively processes data when anomalies are detected or at scheduled intervals, reducing overall processing energy while maintaining effective failure detection.
Solution Approach 2:
Reference values, thresholds, and analysis criteria are pre-computed and stored in the control unit during system setup or initialization. This preliminary preparation allows the system to perform quick comparisons against predetermined standards during operation, minimizing real-time processing requirements and energy consumption during actual monitoring.
Data Source
AI summary
A method of monitoring a vehicle axle, and of discriminating between a plurality of axle failure modes, is described. The method may include acquiring first axle data and second axle data, detecting at least one first anomaly if the acquired first axle data deviate from first reference data provided by a model of the axle, detecting at least one second anomaly if the acquired second axle data deviate from second reference data, detecting at least one out of a plurality of axle failure modes based on which anomaly or which anomalies have been detected, and issuing a failure notice indicative of the at least one detected axle failure mode.


