Trailer Tire And Bearing Monitoring Using Multi-Sensor Failure Prediction
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Solution Overview
Problem
Current tire and wheel bearing monitoring systems in transportation vehicles, particularly trailers, rely on manual inspections and lack real-time monitoring, leading to potential errors and failure detection only after catastrophic events, as they do not effectively address degradation or impending failure issues.
Innovation Solution
A sensor system is implemented on trailers that includes temperature sensors, accelerometers, and acoustic sensors to monitor tire and bearing conditions, processing data to predict impending failures and alert operators, utilizing a gateway and cloud-based data processing to provide real-time insights and scheduled maintenance recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection is used for tire and wheel bearing monitoring, then the system complexity is low, but the reliability and detection precision are insufficient
Solution Approach 1:
The patent combines multiple sensor types (acoustic sensors, temperature sensors, vibration sensors) into an integrated monitoring system that simultaneously tracks multiple parameters. This merging of sensing capabilities enables comprehensive monitoring of tire and bearing conditions, improving reliability while managing system complexity through unified data processing.
Solution Approach 2:
The monitoring system is designed to perform multiple functions: detecting acoustic anomalies, measuring temperature changes, analyzing vibration patterns, and predicting failures across different components (tires and bearings). This multi-functionality approach allows a single system to address various monitoring needs, enhancing reliability without proportionally increasing complexity.
2Measurement precision
If real-time sensor monitoring is implemented, then the detection precision and reliability improve, but the device complexity and cost increase
Solution Approach 1:
The patent extracts and isolates specific failure indicators from complex sensor data streams by focusing on particular acoustic frequency ranges, temperature thresholds, and vibration patterns characteristic of tire and bearing failures. This extraction approach enables precise failure detection while simplifying the processing requirements compared to analyzing all raw sensor data.
Solution Approach 2:
The system employs intermediate processing layers that translate raw sensor data into meaningful diagnostic information. Acoustic signals are converted to spectral analysis results, temperature readings are compared against operational baselines, and vibration data is transformed into condition assessments. These intermediary processing steps enhance measurement precision while managing system complexity through structured data transformation.
3Reliability
If continuous monitoring is performed, then the reliability and early warning capability improve, but the energy consumption and data processing requirements increase
Solution Approach 1:
The monitoring system implements periodic sampling of sensor data at optimized intervals rather than truly continuous monitoring. Acoustic, temperature, and vibration parameters are measured at regular intervals sufficient to detect degradation trends while allowing the system to enter lower-power states between measurements, reducing overall energy consumption while maintaining reliable continuous monitoring capability.
Solution Approach 2:
The system maintains continuous monitoring capability through persistent sensor operation and real-time data processing, ensuring uninterrupted detection of failure conditions. This continuous useful action is achieved by keeping sensor systems active and data processing pipelines running, providing uninterrupted reliability while managing energy use through efficient sensor operation modes.
4Measurement precision
If multiple sensor types are integrated, then the measurement precision and diagnostic capability improve, but the device complexity and data processing burden increase
Solution Approach 1:
The patent segments the monitoring system into distinct functional modules: acoustic sensing and analysis, temperature monitoring and analysis, vibration sensing and analysis, and integrated diagnostic synthesis. Each sensor type and processing function is separated into its own module, improving measurement precision through specialized processing while managing complexity through modular architecture that allows independent development and maintenance of each segment.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enhances the reliability of tire and bearing monitoring by providing early warnings of potential failures, reducing maintenance downtime and wear, and enabling proactive maintenance through continuous data collection and analysis.
Implementation Method 1
temperature sensors, accelerometers, and acoustic sensors to monitor tire and bearing conditions
Implementation Method 2
accelerometers, and acoustic sensors to monitor tire and bearing conditions
Implementation Method 3
accelerometers, and acoustic sensors to monitor tire and bearing conditions
Data Source
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AI summary
A method for monitoring performance of at least one component on a moving platform, the method including receiving sensor data for the at least one component, along with supplemental data, at a processing node; and processing the sensor data, the processing using the supplemental data to filter the sensor data.