Electric Tool Shutdown Control Using Composite Load Averaging

The patent segments the average calculation process into multiple stages: first calculating a first average value from initial current data, then calculating a second average value from subsequent data, and finally computing a composite average from these intermediate results. This segmentation allows the system to adapt to different working conditions at different stages, improving shutdown control accuracy without requiring an overly complex single-step algorithm.

The patent implements dynamic adaptation by using different average calculation strategies based on working conditions. The system transitions from a first average algorithm to a second average algorithm, and finally to a composite average algorithm, allowing the control method to dynamically adjust its complexity and precision based on the actual operating state, thereby reducing misjudgment rates while maintaining reasonable computational complexity.

The patent performs preliminary calculations by first computing the first average value from initial current data before the fastening operation begins. This preliminary action prepares the system with baseline information, allowing the composite average algorithm to work more efficiently during the actual operation by comparing real-time data against pre-established references, thereby reducing overall calculation time while maintaining high reliability.

The patent calculates not only the necessary composite average value but also intermediate first and second average values that can be used for different purposes. This partial/excessive calculation approach provides redundant information that improves reliability through multiple comparison points, while the systematic organization of these calculations prevents excessive time consumption by reusing intermediate results.

The patent changes the parameters of the average calculation algorithm based on working conditions. By switching between different average calculation methods (first average, second average, composite average) and adjusting the weighting and combination of these algorithms, the system adapts to varying load conditions, material types, and fastening requirements without requiring fundamentally different control systems for each scenario.

The composite average algorithm serves multiple functions: it provides baseline comparison data, enables real-time deviation detection, and offers a unified framework that handles various working conditions. This multi-functional approach allows a single control system to adapt to different scenarios (drilling, fastening, different materials) without requiring separate specialized algorithms for each case, thereby improving versatility while controlling overall system complexity.