Tire Heating Press Leak Detection Using Machine Learning Models
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Solution Overview
Problem
Current tire heating press devices require significant design and equipment expansion, as well as additional gas, to detect leaks in the heating bladder, increasing costs and operational effort.
Innovation Solution
A method utilizing a machine learning model to monitor sensor values and control variables within the tire heating press device, allowing for early detection of defects or anomalies in the heating bladder using existing sensors and control variables, thereby reducing the need for additional equipment and resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If additional nitrogen gas and detection systems are added to detect heating bladder leaks, then leak detection capability is improved, but device complexity and costs increase
Solution Approach 1:
The patent makes existing sensors serve multiple functions: they continue to monitor vulcanization parameters (temperature, pressure) while simultaneously detecting heating bladder leaks through pattern recognition. This eliminates the need for separate leak detection equipment by enabling existing sensors to perform dual roles.
Solution Approach 2:
The system uses its own existing sensor infrastructure and operational data to detect leaks, rather than requiring external specialized equipment. The machine learning model analyzes data already being collected during normal operation, allowing the system to self-monitor for anomalies without additional hardware investment.
2Reliability
If additional nitrogen gas is used for leak detection, then leak detection capability is improved, but operational costs increase
Solution Approach 1:
The existing process gas (air or nitrogen) used during vulcanization is repurposed for leak detection by monitoring its pressure and flow characteristics through existing sensors. No additional gas is required since the same gas serves both the vulcanization process and the leak detection function.
Solution Approach 2:
The system detects leaks using data from its own operational processes without requiring external substances or resources. The machine learning model identifies leak conditions by analyzing normal operational variations in pressure, temperature, and gas flow that already occur during vulcanization.
3Measurement precision
If specialized leak detection equipment is added, then leak detection precision is improved, but ease of operation deteriorates
Solution Approach 1:
The existing control system continues to manage vulcanization parameters while automatically performing leak detection through machine learning analysis. Operators interact with the same familiar control interface, which now provides additional leak detection information without requiring new operational procedures or specialized equipment operation.
Solution Approach 2:
The machine learning model continuously monitors sensor data and provides real-time feedback about potential leaks to the control system and operators. This automated feedback mechanism maintains high detection precision while keeping operation simple, as the system self-monitors and alerts operators only when anomalies are detected.
Data Source
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AI summary
The present invention relates to a method and an evaluation device for monitoring a vulcanization process of a vehicle tire (116, 126) in a tire heating press (100), wherein at least one sensor value and/or at least one control variable of the tire heating press (100) is detected, wherein - the at least one sensor value and/or the at least one control variable is supplied to an evaluation device, - the evaluation device (138, 500) comprises a machine learning model (502) created by means of a machine learning method, - and the evaluation device (138, 500) and/or the machine learning model (502) issues a warning message if an evaluation of the at least one sensor value and/or the at least one control variable by the evaluation device (138, 500) reveals that a defect or anomaly of the tire heating press (100) or at least a part of the tire heating press (100) is present.- or that a defect or anomaly of the tire heating press (100) or at least of a part of the tire heating press (100) is imminent.