Wheel Head Monitoring Using Cross-Wheel Signal Comparison
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for detecting malfunctions in wheel heads of commercial vehicles require precise threshold values, making them susceptible to dynamic conditions and potentially missing early signs of wear-related issues.
Innovation Solution
A wheel head monitoring unit comprising first and second sensor units and an evaluation unit that compares measured values and their time derivatives or integrations, allowing for the detection of malfunctions without relying on pre-known threshold values, using identical sensors to record physical variables on each wheel head and predicting expected values through neural networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If precise threshold values are used for malfunction detection, then measurement precision is improved, but the system becomes susceptible to dynamic conditions and environmental influences
Solution Approach 1:
The system changes from using fixed threshold values to using dynamically adapted reference values that are updated based on actual operating conditions. The reference value is continuously adjusted to reflect current environmental factors, vehicle load, and operational state, thereby maintaining detection precision across varying conditions without being affected by environmental variability.
2Device complexity
If static threshold values are used, then device complexity is reduced, but reliability of malfunction detection deteriorates under varying operating conditions
Solution Approach 1:
The system performs self-calibration by automatically updating its own reference values based on actual operating data. The control unit continuously learns from operational patterns and adjusts the reference values without external intervention, enabling the system to maintain high reliability across diverse conditions while keeping the overall device complexity manageable through autonomous adaptation.
3Ease of operation
If pre-known threshold values are required, then ease of operation is improved, but adaptability to different operating conditions deteriorates
Solution Approach 1:
The system transitions from static threshold values to dynamic reference values that automatically adapt to changing operating conditions. The reference values are continuously updated based on real-time data from sensors and actual vehicle operation, enabling the system to maintain ease of operation while achieving high adaptability to various environmental and operational factors without requiring manual reconfiguration.
Data Source
Figure 1~2
Figure 3
AI summary
The invention relates to a wheel-head monitoring unit (1), comprising a first sensor unit (10), a second sensor unit (30) and an evaluation unit (50); wherein the first sensor unit (10) captures and/or is designed to capture at least one first measurement value (M1) of a first wheel head (2); wherein the second sensor unit (30) captures and/or is designed to capture a second measurement value (M2) of a second wheel head (4); wherein the evaluation unit (50) is designed to compare the first measurement value (M1) with the second measurement value (M2) and/or to compare the first measurement value (M1) with a predicted first measurement value and/or to compare their derivatives or integrals with respect to time; and wherein the evaluation unit (50) is designed in particular to output and/or store a signal if the difference (Diff) of the first measurement value (M1) from the second measurement value (M2) and/or of the first measurement value (M1) from the predicted first measurement value exceeds a threshold value.