7results about How to "Reduce storage space usage" patented technology

The application relates to the technical field of industrial visual inspection and edge computing, and provides a distributed storage and hardware cooperative deployment method and system of an industrial quality inspection multi-task visual model, which comprises the following steps: constructing a multi-task visual model; storing model weight files of a shared backbone network in a first storage partition in a read-only mode; storing task head weight files of a plurality of lightweight task heads in the form of independent files in a second storage partition in a distributed mode; determining a target task identifier corresponding to a current product to be inspected; loading the shared backbone network and a task head corresponding to the target task identifier by edge computing hardware; inputting a product image into the shared backbone network and extracting general visual features of the product image; inputting the general visual features into the task head corresponding to the target task identifier in parallel to obtain classification results of the task heads; and determining the quality state of the current product to be inspected according to the classification results. Thus, systematic cost reduction is achieved.

This utility model relates to the field of steel plate component technology, specifically a steel plate component stacking equipment, including a frame with multiple sets of clamping plates installed on it, and baffles and recessed support plates distributed between each set of clamping plates; a transfer component is also installed on the inner side of the frame. This steel plate component stacking equipment, through the coordinated action of the transfer component and the pushing component, achieves automatic transfer, positioning, and stacking of steel plate components, reducing manual intervention and significantly lowering the labor intensity of workers. The clamping plates and baffles define the stacking boundaries, the support plate of the pushing component cooperates with the recessed support plate to clamp the steel plates from both sides, and the pushing plate and auxiliary plate of the transfer component ensure longitudinal positioning, ensuring neat stacking and avoiding the risk of slippage due to tilting, while also reducing storage space occupation. The waist hole design of the side plates and clamping plates allows for adjustment of the position of the baffles and clamping plates, and the adjustment holes of the auxiliary plates allow for adjustment of their installation position, enabling the equipment to adapt to the stacking needs of steel plate components of different sizes.

This application relates to the field of robotics, and in particular to a training data acquisition device for robot gripper control. The training data acquisition device mainly comprises four core modules: the acquisition device body, an image acquisition module (51), a motion detection module (52), and a data processing module (53). In use, the operator holds the device, aligns the mechanical finger (2) with the object to be grasped, and presses the handle (3) on the acquisition device body to control the mechanical finger (2) to close and grasp the object. During this process, the image acquisition module (51) records visual information, and the motion detection module (52) records the degree of finger opening and closing. The data processing module (53) aggregates these two types of heterogeneous data. Thus, the hand-eye coordination process of a real robot can be simulated at extremely low hardware cost, and key matching data is provided for robot imitation learning.

This invention provides an image-assisted 3D object detection method, comprising the following steps: Step 1, extracting features from a point cloud containing the 3D object to be detected and its corresponding image; Step 2, fusing the features of the point cloud and the image based on a block self-attention mechanism to obtain fused multimodal features; Step 3, generating a foreground point mask based on the fused multimodal features and using it to extract multi-scale features with a focus on the foreground, obtaining feature maps of the point cloud at different resolutions; Step 4, generating an object detection proposal, i.e., interpolating the feature maps at different resolutions based on the three nearest neighbor interpolation method, fusing the interpolated features with the multimodal features using a multilayer perceptron, and feeding them into a two-stage detection module to generate an object detection proposal, thereby completing the image-assisted 3D object detection.

The invention provides an ice generation method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring surface feature information of a target three-dimensional model; determining an ice growth area on the surface of the target three-dimensional model based on the surface feature information; generating a plurality of scattering point positions in the ice growth area; performing particle simulation based on the plurality of scattering point positions to generate ice particle data; an ice model is generated based on the ice particle data. According to the method provided by the invention, the suitable ice growth area is automatically identified by using the surface feature information, the problem of stiff distribution caused by only depending on single normal information is avoided, intelligent judgment of the ice growth area is realized, the manual division workload is reduced, and the interaction experience is improved.

This application relates to the field of communication optimization technology, and discloses a PLC-based photovoltaic optimizer communication method and system. The method includes: initializing and frequency testing the MPPT optimizer to obtain an initial communication frequency set; monitoring and analyzing real-time communication quality indicators and environmental parameters to obtain real-time communication frequencies; classifying, packetizing, and prioritizing the data to be transmitted to obtain a priority data packet sequence; performing topology analysis and multi-path planning on the MPPT optimizer network to obtain a distributed data segment set; aggregating and performing integrity checks on the multi-path transmitted data to obtain target verification data; and compressing, encrypting, and hierarchically storing the target verification data to obtain target communication data. This application improves the efficiency of PLC-based photovoltaic optimizer communication.