Patents by Inventor Yongduan Song

Yongduan Song has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20220291276
    Abstract: A detection circuit for open, close and suspension states of a high and low level effective switch in a vehicle. The circuit includes an optocoupler circuit module, a low-level active path module, a high-level active path module, a filtering and debouncing module, a transient suppression module, and a wiring terminal. The optocoupler circuit module is connected to the low-level active path module, the high-level active path module and the low-level active path module are connected in parallel to the filtering and debouncing module, and the filtering and debouncing module is connected to the transient suppression module, and then connected to the external high-level active switch or low-level active switch through the wiring terminal. Whether it is a high-level active switch or a low-level active switch, the detection circuit can distinguish whether the switch is in the closed or suspended state, and the strong and weak voltages are isolated.
    Type: Application
    Filed: January 31, 2022
    Publication date: September 15, 2022
    Inventors: YONGDUAN SONG, Shuaicheng Hou, Jiawei Chen, Mi Fang
  • Publication number: 20220292311
    Abstract: The present disclosure provides a method for object detection and recognition based on a neural network. The method includes: adding a detection layer following three detection layers of an existing YOLOv5 network model, to construct a new YOLOv5 network model; then, training the new YOLOv5 network model by considering an overlapping area between a predicted box and a ground truth box, a center-to-center distance between the two boxes, and an aspect ratio of the two boxes; and finally, inputting a to-be-detected image into the trained new YOLOv5 network model, outputting a predicted box of an object and probability values corresponding to a class to which the object belongs, and setting a class corresponding to a maximum probability value as a predicted class of the object in the to-be-detected image. This method can quickly and effectively detect multiple classes of objects. Especially, a detection effect for small objects is more ideal.
    Type: Application
    Filed: July 7, 2021
    Publication date: September 15, 2022
    Inventors: Yongduan Song, Shilei Tan, Li Huang, Ziqiang Jiang, Jian Liu, Lihui Tan
  • Publication number: 20220255327
    Abstract: The present disclosure provides a decentralized active equalization method for a cascaded lithium-ion battery pack. The method includes: connecting each battery cell in the cascaded lithium-ion battery pack to a direct current (DC) bus through an equalizer respectively, where each equalizer includes an independent controller, a sampling circuit, a power supply circuit, a drive circuit, and a main circuit; connecting an input terminal of the main circuit to a corresponding battery cell, and connecting an output terminal of the main circuit to the DC bus. The present disclosure solves the technical problem that an existing cascaded lithium-ion battery pack equalization method cannot achieve equalization when a centralized controller failure or a communication failure occurs, improves the reliability of the equalization method, can make the equalizer work at high efficiency by configuring parameters of C, K, and R, and speeds up the equalization or improves the equalization accuracy.
    Type: Application
    Filed: January 31, 2022
    Publication date: August 11, 2022
    Inventors: Yongduan Song, Jiawei Chen, Li Chen, Qingchao Song
  • Publication number: 20220196459
    Abstract: The present disclosure provides a real-time vehicle overload detection method based on a convolutional neural network (CNN). The present disclosure detects a road driving vehicle in real time with a CNN method and a you only look once (YOLO)-V3 detection algorithm, detects the number of wheels to obtain the number of axles, detects a relative wheelbase, compares the number of axles and the relative wheelbase with a national vehicle load standard to obtain a maximum load of the vehicle, and compares the maximum load with an actual load measured by a piezoelectric sensor under the vehicle, thereby implementing real-time vehicle overload detection. The present disclosure has desirable real-time detection, can implement no-parking vehicle overload detection on the road, and avoids potential traffic congestions and road traffic accidents.
    Type: Application
    Filed: September 30, 2021
    Publication date: June 23, 2022
    Applicants: Dibi (Chongqing) Intelligent Technology Research Institute Co., Ltd., Star Institute of Intelligent Systems
    Inventors: Yongduan Song, Yujuan Wang, Gonglin Lu, Shilei Tan, Yating Yang, Chunxu Ren, Mingyang Liu
  • Publication number: 20220180090
    Abstract: The present disclosure provides a neural network-based visual detection and tracking method of an inspection robot, which includes the following steps of: 1) acquiring environmental images of a dynamic background a movement process of the robot; 2) preprocessing the acquired images; 3) detecting human targets and specific behaviors in the images in the robot body, and saving the sizes, position information and features of the human targets with the specific behaviors; 4) controlling the orientation of a robot gimbal by using a target tracking algorithm to make sure that a specific target is always located at the central positions of the images; and 5) controlling the robot to move along with a tracked object. The neural network-based visual detection and tracking method of an inspection robot in the present disclosure has a quite high adaptive ability, achieves better detection and tracking effects on targets in a dynamic background scene.
    Type: Application
    Filed: June 16, 2021
    Publication date: June 9, 2022
    Inventors: Yongduan Song, Li Huang, Shilei Tan, Junfeng Lai, Huan Liu, Ziqiang Jiang, Jie Zhang, Huan Chen, Jiangyu Wu, Hong Long, Fang Hu, Qin Hu
  • Patent number: 11354856
    Abstract: An unmanned aerial vehicle navigation map construction system based on three-dimensional image reconstruction technology comprises an unmanned aerial vehicle, a data acquiring component and a three-dimensional navigation map construction system, wherein the three-dimensional navigation map construction system comprises an image set input system, a feature point extraction system, a sparse three-dimensional point cloud reconstruction system, a dense three-dimensional point cloud reconstruction system, a point cloud model optimization system and a three-dimensional navigation map reconstruction system. A scene image set is input into the three-dimensional navigation map construction system, feature point detection is carried out on all images, a sparse point cloud model of the scene and a dense point cloud model of the scene are reconstructed, the model is optimized by removing a miscellaneous point and reconstructing the surface, and a three-dimensional navigation map of the scene is reconstructed.
    Type: Grant
    Filed: March 9, 2021
    Date of Patent: June 7, 2022
    Assignee: Star Institute of Intelligent Systems
    Inventors: Yongduan Song, Xiao Cao
  • Publication number: 20220171395
    Abstract: A method for obstacle detection and recognition for an intelligent snow sweeping robot is disclosed, comprising: 1) disposing ultrasonic sensors at a front end of the snow sweeping robot to detect distance information from an obstacle ahead; and disposing radar sensors at the front and rear of the snow sweeping robot to detect whether a creature suddenly approaches; 2) processing signals detected by each of the ultrasonic sensors and radar sensors, and calculating a forward distance of the snow sweeping robot; and 3) determining a snow cover extent of a working road, detecting a change of the distance from the obstacles, and recognizing the obstacles for conditions of an ultrasonic ranging variation ratio and a variation of the forward distance of the snow sweeping robot, a change of the signal detected by radar sensors, and a descriptive statistic of the snow cover extent within a specific time period.
    Type: Application
    Filed: July 22, 2021
    Publication date: June 2, 2022
    Applicant: Chongqing University
    Inventors: Yongduan Song, Ziqiang Jiang, Shilei Tan, Junfeng Lai, Huan Liu, Li Huang, Jie Zhang, Huan Chen, Hong Long, Fang Hu, Jiangyu Wu, Qin Hu, Wenqi Li
  • Publication number: 20220152817
    Abstract: The present disclosure discloses a neural network adaptive tracking control method for joint robots, which proposes two schemes: robust adaptive control and neural adaptive control, comprising the following steps: 1) establishing a joint robot system model; 2) establishing a state space expression and an error definition when taking into consideration both the drive failure and actuator saturation of the joint robot system; 3) designing a PID controller and updating algorithms of the joint robot system; and 4) using the designed PID controller and updating algorithms to realize the control of the trajectory motion of the joint robot. The present disclosure may solve the following technical problems at the same time: the drive saturation and coupling effect in the joint system, processing parameter uncertainty and non-parametric uncertainty, execution failure handling during the system operation, compensation for non-vanishing interference, and the like.
    Type: Application
    Filed: March 24, 2021
    Publication date: May 19, 2022
    Inventors: Yongduan SONG, Huan LIU, Junfeng LAI, Ziqiang JIANG, Jie ZHANG, Huan CHEN, Li HUANG, Congyi ZHANG, Yingrui CHEN, Yating YANG, Chunxu REN, Han BAO, Kuilong YANG, Ge SONG, Bowen ZHANG, Hong LONG
  • Publication number: 20220155136
    Abstract: The present disclosure discloses a method for quick weighing of loose and small packages of traditional Chinese medicine (TCM), comprising: 1) establishing an equivalent physical model of a weighing system for loose and small packages, and, through Laplace transformation and Z transformation, obtaining a formula of the mass M of medicine packages to be weighed; 2) calculating a1, a2, b1, and b2 on the basis of a vector prediction error; 3) according to a1, a2, b1, and b2 obtained and the formula of the mass of medicine packages to be weighed, obtaining the mass of the loose and small packages of TCM that are weighed. According to the method, the scalar prediction error is expanded into the vector prediction error based on the traditional method so as to construct a new identification model based on the vector prediction error, and as a result the utilization efficiency of prediction error turns higher.
    Type: Application
    Filed: March 16, 2021
    Publication date: May 19, 2022
    Applicant: Chongqing University
    Inventors: Yongduan Song, Zhixi Shen, Haifeng Liu, Jie Lei
  • Publication number: 20210358206
    Abstract: An unmanned aerial vehicle navigation map construction system based on three-dimensional image reconstruction technology comprises an unmanned aerial vehicle, a data acquiring component and a three-dimensional navigation map construction system, wherein the three-dimensional navigation map construction system comprises an image set input system, a feature point extraction system, a sparse three-dimensional point cloud reconstruction system, a dense three-dimensional point cloud reconstruction system, a point cloud model optimization system and a three-dimensional navigation map reconstruction system. A scene image set is input into the three-dimensional navigation map construction system, feature point detection is carried out on all images, a sparse point cloud model of the scene and a dense point cloud model of the scene are reconstructed, the model is optimized by removing a miscellaneous point and reconstructing the surface, and a three-dimensional navigation map of the scene is reconstructed.
    Type: Application
    Filed: March 9, 2021
    Publication date: November 18, 2021
    Inventors: Yongduan SONG, Xiao CAO
  • Publication number: 20210350800
    Abstract: In some embodiments, methods and systems for pushing audiovisual playlists based on a text-attentional convolutional neural network include a local voice interactive terminal, a dialog system server and a playlist recommendation engine, where the dialog system server and the playlist recommendation engine are respectively connected to the local voice interactive terminal. In some embodiments, the local voice interactive terminal includes a microphone array, a host computer connected to the microphone array, and a voice synthesis chip board connected to the microphone array. In some embodiments, the playlist recommendation engine obtains rating data based on a rating predictor constructed by the neural network; the host computer parses the data into recommended playlist information; and the voice terminal synthesizes the results and pushes them to a user in the form of voice.
    Type: Application
    Filed: January 5, 2021
    Publication date: November 11, 2021
    Inventors: Yongduan Song, Junfeng Lai, Xin Zhou
  • Publication number: 20210008732
    Abstract: The present disclosure discloses an automated dispensing machine adopting local coverage type sucker array and a control method thereof. The automated dispensing machine adopting local coverage type sucker array comprises a rack. A medicine obtaining device and a medicine weighing and discharging device are arranged on the rack. The control method comprises: (1), after receiving medicine grasping and discharging commands, a single-chip microprocessor firstly selects a current medicine obtaining station according to a medicine obtaining station circulation sequence, and then controls the first linear driver to push the slide to move forwards to the selected medicine obtaining station; (2), the single-chip microprocessor transmits the control signal to a fifth relay to control the second linear driver to drive the vacuum medicine sucking mechanical arm to move downwards.
    Type: Application
    Filed: April 1, 2020
    Publication date: January 14, 2021
    Inventors: Yongduan Song, Zhixi Shen, Xiaohu Pan, Li Chen, Xiao Chen, Zhilin Wang
  • Patent number: 10889008
    Abstract: The present disclosure discloses an automated dispensing machine adopting local coverage type sucker array and a control method thereof. The automated dispensing machine adopting local coverage type sucker array comprises a rack. A medicine obtaining device and a medicine weighing and discharging device are arranged on the rack. The control method comprises: (1), after receiving medicine grasping and discharging commands, a single-chip microprocessor firstly selects a current medicine obtaining station according to a medicine obtaining station circulation sequence, and then controls the first linear driver to push the slide to move forwards to the selected medicine obtaining station; (2), the single-chip microprocessor transmits the control signal to a fifth relay to control the second linear driver to drive the vacuum medicine sucking mechanical arm to move downwards.
    Type: Grant
    Filed: April 1, 2020
    Date of Patent: January 12, 2021
    Assignee: Chongqing University
    Inventors: Yongduan Song, Zhixi Shen, Xiaohu Pan, Li Chen, Xiao Chen, Zhilin Wang