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48results about How to "Reduce start and stop" patented technology

Servo Continuous Interpolation and Curve Parametric Control Method Based on Mitsubishi PLC System

ActiveCN121722056Bquick debuggingdebug accuratelyControl engineeringGeometric modeling
This invention discloses a servo continuous interpolation and curve parameterization control method based on a Mitsubishi PLC system, relating to the field of CNC motion control technology. The method includes process parameter conversion and interpolation execution: The system receives user-inputted process parameters at a human-machine interface, including at least the target bending angle; the PLC main controller automatically calculates the coordinate parameters required for the motion control module to execute the interpolation motion based on a preset geometric model and the process parameters. This application lowers the operational threshold by encapsulating complex mathematical coordinate calculations within the program, allowing operators to interact only with intuitive process parameters, enabling even non-professionals to quickly and accurately debug equipment. This application also improves equipment efficiency and flexibility: intelligent continuous interpolation judgment reduces unnecessary starts and stops, increases equipment operating cycle time, and one-click switching between linear / circular modes enhances the equipment's ability to handle different processes.
Owner:ANHUI KINGPOWER EQUIP & MOLD MFR

Cylindrical battery material transfer switching device

A cylindrical battery material switching speed change device, comprising a mechanism base and a vertical first side plate connected to the mechanism base. The left side of the first side plate is provided with first to fourth gears engaged and connected through first to fourth rotating shafts. The first to fourth rotating shafts are fixedly connected through connecting rods and double swing arms. The third gear is connected to a fifth gear provided on the mechanism base through a pull rod, and the fifth gear is drivingly connected to the first gear. The relative displacement of the second and third gears can be achieved by rotating the fifth gear to pull the pull rod. The right side of the first side plate is provided with four buffer forks with limiters and multiple recesses for adsorbing and grabbing batteries through first to fourth rotating shafts. The relative speed change between the buffer wheels can be completed by the displacement of the gears, achieving the effect of uniform speed feeding and variable speed discharging. It facilitates the discharge of the battery discharge process to prohibit the detection of moisture, reduces the influence between the appearance detection speed and the front end feeding speed, and improves the battery detection production efficiency.
Owner:ZHEJIANG HANGKE TECH

Traffic signal control method based on machine vision perception and time-space sequence prediction

The invention discloses a traffic signal control method based on machine visual perception and space-time sequence prediction, and relates to the technical field of intelligent traffic signal control. The traffic signal control method based on machine vision perception and time-space sequence prediction comprises the following steps: S1, machine vision perception: acquiring real-time image data of a traffic intersection through image acquisition equipment, preprocessing the image data, and extracting traffic flow key parameters; and S2, space-time sequence prediction: constructing a PCA-LSTM traffic flow prediction model based on principal component analysis PCA and a long short-term memory neural network LSTM, inputting the preprocessed traffic flow historical data, and outputting a short-term traffic flow prediction result. The traffic signal control method based on machine visual perception and time-space sequence prediction is comprehensive in data coverage and low in acquisition cost; and the prediction performance is better: through abnormal data processing and dynamic principal component selection of the PCA-LSTM model, the prediction precision is improved by 2%-5% compared with the traditional LSTM, and the calculation efficiency is improved by 15.01%.
Owner:SHAANXI UNIV OF SCI & TECH