4results about How to "Self-learning ability" patented technology

This application relates to the field of soil remediation technology, and discloses a method, system, and storage medium for real-time monitoring of soil remediation effects. The method includes: collecting multi-depth data samples of soil in the vertical direction to construct a stratified soil characteristic dataset; identifying locations of highly heterogeneous sections based on the dataset; injecting a tracer at these locations and imaging in real time to obtain a sequence of infiltration path images; using a random forest model to predict diffusion velocity and blockage point locations, dynamically adjusting injection parameters to eliminate blockage, and obtaining infiltration path data; tracking and quantifying the effects of the soil amendment on each soil layer through time-series analysis to obtain quantitative indicators of the effect; comparing these indicators with the initial dataset to optimize the stratification model and construct a stratified monitoring framework; integrating multi-depth data samples to validate the framework and generating an evaluation report on the soil remediation effect. This invention achieves accurate characterization of soil vertical stratification characteristics and scientific, quantitative evaluation of remediation effects, improving the efficiency of soil amendment use.

This invention discloses a radar-coordinated braking control method for electric-assist bicycles in complex road conditions, relating to the field of electric-assist bicycle control technology. The method includes acquiring radar-detected rear target signals, determining the presence of collision risk based on the changing trend of the rear target signals, and identifying the movement pattern of the rear targets; acquiring the rider's pedaling torque signal; when a collision risk is determined, predicting the moment when the rider's pedaling torque will begin to decrease based on the changing trend of the rear target signals; at the predicted moment, initiating mechanical braking pre-pressure and simultaneously reducing the motor's assist output. This invention utilizes residual assist to provide soft support for the rider's body posture, compensating for the instability caused by the forward shift of the center of gravity, and solving the timing conflict problem between braking intervention and rider posture changes in existing technologies. This improves braking efficiency in dangerous rear-end scenarios while enhancing the stability and smoothness of the riding process.

This invention provides a subsea pipeline oil leak early warning system and method based on multiphysics digital twins, relating to the field of marine oil and gas development technology. The early warning system includes: an anchored buoy platform, an underwater glider, multiphysics sensors, a base workstation, a digital twin cloud platform, and an intelligent early warning module. The anchored buoy platform provides fixed-point observation, while the underwater glider conducts mobile patrols, forming a collaborative observation network to collect environmental data from the pipeline's location. The digital twin cloud platform establishes a multiphysics digital twin model, analyzes it in real time, and automatically generates tiered early warnings; the intelligent early warning module executes the tiered warnings. This invention, through the collaborative design of multiphysics digital twins and intelligent early warning, fundamentally solves the problems of real-time performance and accuracy in subsea pipeline oil leak detection. It not only achieves multi-dimensional data fusion and high-fidelity simulation but also improves the system's robustness in harsh marine environments, significantly reducing the risk of environmental pollution.

This application provides a method and system for intelligently optimizing the cutting path and parameters of a laser cutting machine, belonging to the field of laser cutting machine control technology. The method includes: acquiring task parameters and querying a process parameter experience model library to generate initial processing parameters; simultaneously employing an improved genetic-ant colony hybrid algorithm to solve for the theoretically optimal cutting path sequence; collecting multi-source feature information and inputting it into a pre-trained state recognition model to identify the current cutting state in real time; dynamically adjusting the laser power and cutting speed based on the current cutting state; and performing local replanning of the theoretically optimal cutting path sequence based on multi-source feature information, including geometric deviation compensation and dynamic collision avoidance, to generate corrected motion control commands; and using an incremental learning algorithm to update and optimize the dual-channel convolutional neural network and the process parameter experience model library. This application shortens processing time, improves cutting quality stability, reduces energy consumption and defect rate, and enhances the level of intelligence.