2results about How to "Improve disposal" patented technology

The application discloses a smart bus operation and maintenance task scheduling method based on an edge intelligent prediction model, belongs to the field of vehicle operation and maintenance scheduling, and comprises the following steps: performing segment division on a continuous sampling sequence according to a preset time window, extracting derived characteristic parameters used for operation and maintenance risk discrimination and prediction inference in each segment, and encapsulating the derived characteristic parameters and data quality information corresponding to the derived characteristic parameters to generate a characteristic certificate; performing comparable correction on the derived characteristic parameters based on the data quality information in the characteristic certificate; obtaining a certificate-driven operation and maintenance risk judgment result based on a derived characteristic drift index; generating a model input sequence and inputting the model input sequence into an edge intelligent prediction model to obtain a model-driven operation and maintenance risk judgment result; and the problems that different reporting strategy gears are prone to introducing derived characteristic deviation in the prior art, and then causing risk discrimination fluctuation and operation and maintenance scheduling jitter are solved.

This invention relates to the field of robot operation control technology and discloses a multi-task triggering linkage control method for unattended composite robots. This method addresses the problems of traditional methods, such as difficulty in uniformly identifying and controlling multi-source heterogeneous triggering events, which easily leads to missed triggering of critical alarms, broken execution chains after task preemption, high emergency response delays, and untraceable operation processes. The method first receives signals from the chemical site's timed schedule, sensors, vision, host computer, and emergency button signals, and completes time alignment and semantic unification. It then combines the chassis, robotic arm, end effector, and environmental status to perform priority determination, task preemption, breakpoint saving, safe switching, linkage link generation, collaborative execution, task recovery, and full-process recording, thereby improving the timeliness of critical event handling, operational continuity, and process traceability.