Two-Wheeler Wear Parameter Generation via Sensor Segmentation
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Solution Overview
Problem
Existing methods for monitoring wear in two-wheeler components do not effectively update based on dynamic operating and status data, leading to inadequate detection of wear and potential safety risks.
Innovation Solution
A method and device that generate a wear parameter by detecting weight and use parameters, using sensors to collect dynamic data, and comparing them to threshold values to determine the need for maintenance or component replacement, with the option to automatically schedule service visits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional wear monitoring methods are used, then the system structure remains simple, but the wear detection accuracy and timeliness deteriorate
Solution Approach 1:
The wear monitoring system is segmented into multiple independent sensor modules (acceleration sensor, temperature sensor, pressure sensor, etc.) that independently monitor different physical parameters. Each sensor captures specific aspect of wear conditions, and the evaluation unit integrates these segmented data streams to achieve comprehensive and accurate wear detection without requiring a single complex sensor system.
Solution Approach 2:
An evaluation unit is introduced as an intermediary component that receives raw data from multiple sensors, processes the information using wear models, and generates meaningful wear parameters. This intermediary layer transforms complex multi-sensor data into actionable wear assessments, improving detection accuracy while maintaining manageable system complexity through modular architecture.
2Measurement precision
If dynamic operating data is continuously monitored, then the wear parameter accuracy improves, but the energy consumption increases
Solution Approach 1:
The system implements periodic monitoring of operating parameters (acceleration, temperature, pressure) at defined intervals during vehicle operation. Rather than continuous monitoring, sensors capture data at periodic cycles, which reduces energy consumption while still providing sufficient data density for accurate wear parameter calculation through the evaluation unit's processing capabilities.
Solution Approach 2:
The system dynamically adjusts monitoring parameters based on operating conditions. The evaluation unit modifies the frequency and intensity of data collection according to the vehicle's operational state (e.g., higher monitoring frequency during high-stress operations, lower frequency during normal operation), optimizing the balance between wear detection accuracy and energy consumption.
3Reliability
If multiple sensors are deployed to collect comprehensive data, then the wear monitoring reliability improves, but the device complexity increases
Solution Approach 1:
The evaluation unit serves multiple functions: it receives data from various sensor types, processes different parameter combinations, applies various wear models, and generates comprehensive wear assessments. This multi-functional component consolidates the complexity of managing multiple sensors into a single versatile processing unit, maintaining reliability while controlling overall system complexity.
Solution Approach 2:
Multiple sensor data streams (acceleration, temperature, pressure, etc.) are merged and integrated within the evaluation unit to generate unified wear parameters. By combining these diverse data sources through a centralized processing approach, the system achieves enhanced monitoring reliability through data correlation and validation, while avoiding the complexity of multiple independent processing systems.
4Loss of time
If wear parameters are calculated in real-time, then the maintenance timing accuracy improves, but the computational load increases
Solution Approach 1:
The system pre-establishes wear models and calculation algorithms in the evaluation unit before actual wear assessment is needed. These pre-programmed models contain the necessary formulas, thresholds, and processing logic for calculating wear parameters from sensor data. During operation, the evaluation unit simply applies these pre-prepared models to incoming data, achieving real-time wear parameter calculation with minimal computational overhead.
Solution Approach 2:
The evaluation unit calculates wear parameters at selective intervals rather than continuously, and only processes the minimum necessary data subset required for accurate assessment. By performing partial calculations at strategic moments (e.g., after specific operational cycles or when threshold conditions are met), the system maintains maintenance timing accuracy while reducing overall computational load and power consumption.
Data Source
AI summary
A method, a device, and a two-wheeler including a device of this type, in which at least one wear parameter that represents the wear of at least one wear part or a component of the two-wheeler is generated, determined, or ascertained. It may be provided that a shared wear parameter for multiple wear parts or in each case separate wear parameters for individual wear parts is/are generated, determined, or formed. Typical components on a two-wheeler, in particular on a bicycle, that may be subject to wear include the brake pads, the brake disks, a sprocket, a chainring, a chain, or a tire. In addition, brake fluid in a hydraulic brake may also be subject to wear, it being possible for the brake fluid to absorb either air, water, or dirt, thus impairing the responsiveness of the pressure transfer.