Hose Assembly Life Prediction Using Bend and Torque Sensors
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Solution Overview
Problem
Current prediction techniques for the remaining life of hose assemblies in hydraulic circuits are inaccurate, leading to unexpected failures that can damage the circuit and other components of work machines.
Innovation Solution
A system comprising a hose assembly with multiple sensor devices that generate data on bend radius, torque, elongation, and torsion, which is used by a controller to determine the remaining life of the hose assembly, allowing for proactive maintenance actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current prediction techniques are used to estimate remaining life of hose assemblies, then the system is simple and low-cost, but the prediction accuracy is poor leading to unexpected failures
Solution Approach 1:
The hose assembly is segmented into multiple monitoring zones with different sensor types placed at strategic locations. Each sensor monitors specific parameters (bend radius, torque, elongation, torsion, temperature, pressure) to provide comprehensive data for accurate remaining life prediction without requiring a single complex sensor system.
Solution Approach 2:
The system transitions from using单一 prediction methods to monitoring multiple physical parameters simultaneously. By measuring bend radius, torque, elongation, torsion, temperature, and pressure, the system captures the complex stress-state of the hose assembly under various operating conditions, enabling accurate prediction of remaining life through multi-parameter analysis.
2Reliability
If multiple sensor devices are installed to monitor hose assembly conditions, then prediction accuracy improves, but the cost and complexity of the system increase
Solution Approach 1:
The sensor system is designed with multi-functionality where sensors monitor multiple aspects of hose assembly health. The same sensor infrastructure supports various measurement functions (mechanical stress, thermal conditions, fluid pressure) to provide comprehensive reliability assessment without requiring separate dedicated systems for each parameter.
Solution Approach 2:
The system implements continuous feedback by constantly monitoring hose assembly conditions through multiple sensors and comparing actual measurements against predicted values. This feedback mechanism enables real-time adjustment of predictions and early detection of deviations from normal operation, significantly improving prediction reliability while maintaining manageable system complexity through automated monitoring.
3Measurement precision
If hose assembly is monitored continuously under different operating conditions, then remaining life prediction becomes accurate, but data processing complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-establishing the relationship between operating conditions and hose assembly degradation patterns. By collecting and analyzing data under various operating conditions in advance, the system builds predictive models that can accurately estimate remaining life without requiring complex real-time processing during actual operation.
Data Source
AI summary
A system may include a hose assembly and a controller. The hose assembly may comprise a plurality of sensor devices configured to generate sensor data regarding the hose assembly. The sensor data may include at least one of first sensor data regarding a bend radius of a first portion of the hose assembly, or second sensor data regarding an amount of torque at a second portion of the hose assembly. The controller may be configured to receive the sensor data from the plurality of sensor devices; determine a remaining life of the hose assembly based on the sensor data; and perform an action based on the remaining life of the hose assembly.