Sensor-Guided Power Tool Kickback Detection Across Operating States
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Solution Overview
Problem
Existing power tools lack effective mechanisms to differentiate between various user experiences and operating conditions, leading to inconsistent kickback event detection and potential safety hazards due to unnecessary interruptions during machining.
Innovation Solution
A power tool with a control device that selectively determines between two recognition functions for kickback event detection based on function determination information, allowing for optimized recognition according to the user's experience and current operating state, using sensor data on force, acceleration, velocity, deflection, deformation, and mechanical stress.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single recognition function with fixed sensitivity is used for kickback detection, then the device complexity is reduced, but the adaptability to different user experiences and operating conditions deteriorates
Solution Approach 1:
The control device dynamically selects between a first recognition function and a second recognition function based on detected operating conditions (e.g., machining state, workpiece type). This dynamic adaptation allows the system to adjust its kickback detection sensitivity in real-time without requiring a complex reconfigurable architecture, resolving the contradiction between simplicity and adaptability.
Solution Approach 2:
The system changes the parameters of the recognition function (such as threshold values, sensitivity levels, or detection criteria) based on the operating state. By having multiple predefined recognition functions with different parameter sets, the control device can adapt to various user experiences and machining conditions while maintaining a relatively simple overall structure.
2Reliability
If a sensitive recognition function is used to detect weak kickbacks, then the reliability of safety detection is improved, but the productivity deteriorates due to unnecessary interruptions
Solution Approach 1:
The system adjusts the sensitivity parameters of the recognition function based on the detected operating state. For example, during certain machining operations where minor vibrations are normal, a less sensitive function is selected to avoid false alarms. During other operations where kickback is more critical, a more sensitive function is applied. This parameter adaptation maintains high reliability while minimizing unnecessary interruptions to productivity.
Solution Approach 2:
The recognition function's sensitivity is dynamically adjusted according to the current machining context. The control device monitors operating conditions and switches between different recognition functions to match the appropriate sensitivity level, ensuring reliable kickback detection without causing unnecessary productivity losses from false positive interruptions.
3Productivity
If a less sensitive recognition function is used to avoid unnecessary interruptions, then the productivity is improved, but the reliability of safety detection deteriorates
Solution Approach 1:
The system employs multiple recognition functions with different sensitivity parameters and selectively applies them based on the operating state. When the machining context indicates low risk of false alarms, a less sensitive function maintains productivity. When the context suggests higher risk, a more sensitive function ensures reliability. This conditional parameter selection resolves the contradiction between productivity and reliability.
4Adaptability or versatility
If multiple recognition functions are available for different operating conditions, then the adaptability is improved, but the device complexity increases
Solution Approach 1:
The control device implements a dynamic selection mechanism that automatically chooses the appropriate recognition function based on detected operating conditions. This dynamic approach provides high adaptability across different machining scenarios while keeping the control structure manageable through automated decision-making rather than manual configuration or complex user interfaces.
Data Source
AI summary
A power tool with a rotatable tool designed as a saw blade or a milling cutter. The power tool includes a sensor device for detecting a mechanical quantity, the mechanical quantity including a force, an acceleration, a velocity, a deflection, a deformation and/or a mechanical stress. The mechanical quantity is dependent on a force emanating from the tool, and a control device communicatively coupled to the sensor device. The control device is adapted to recognize a kickback event based on the detected mechanical quantity, in which the control device is adapted to selectively determine a first recognition function or a second recognition function different from the first recognition function based on a function determination information, and to perform the recognition of the kickback event based on the detected mechanical quantity using the determined recognition function.