公开(公告)号：US20220269955A1

公开(公告)日：2022-08-25

申请号：US17555464

申请日：2021-12-19

Applicant: INSTITUTE OF AUTOMATION, CHINESE ACADEMY OF SCIENCES

Inventor： Jie TAN ,  Chengbao LIU

IPC: G06N5/02 ,  G06N5/04 ,  G06F17/18

Abstract: Disclosed is an acquisition method for domain rule knowledge of an industrial process. The method comprises the steps of: establishing a domain rule base, establishing a semantic knowledge base, and combining the domain rule base and the semantic knowledge base so as to realize an augmented update of a domain rule knowledge base; describing the domain knowledge of the industrial process by using weighted first-order logic rules so as to form a training sample set of the first-order logic rules; performing a weight learning by applying probability soft logic and the training sample set of the first-order logic rules so as to realize weight to non-weighted rules; performing rule learning through a machine learning algorithm so as to obtain a first-order logic rule on a change in optimization decision-making semantic when multi-source data semantic information changes.

公开(公告)号：US20160042204A1

公开(公告)日：2016-02-11

申请号：US14784328

申请日：2014-04-08

Applicant: INSTITUTE OF AUTOMATION, CHINESE ACADEMY OF SCIENCES

Inventor： Jie TAN ,  Na MAO ,  Hongsheng ZHAO ,  Xiaofeng NING

IPC: G06K7/00

CPC classification number: G06K7/0095 ,  G01R31/2822 ,  G01V15/00 ,  G06K7/0008 ,  G06K7/10356 ,  G06K19/00 ,  G06K19/0723 ,  G06K2017/0045 ,  G06Q10/087 ,  G07B15/02 ,  G07C2009/0092 ,  G08G1/017 ,  G08G1/052 ,  G08G1/205 ,  H01Q1/12

Abstract: A system for testing performance of mobile Radio Frequency Identification tags, comprising: a test device including a mobile car and a test channel; the test channel comprises a magnetic label on a ground for labeling a test driving route of the mobile car and a framework fixed on to the ground and provided with a reading device for the RFID tags; a magnetic recognition device is provided at a bottom of the mobile car to identify to the magnetic label and the mobile car is driven along the test driving route; the plurality of RFID tags are fixed on under-test goods loaded on the mobile car; a testing equipment configured to control the reading device to identify the RFID tags fixed on under-test goods; wherein the RFID tags are fixed on to under-test goods which are loaded on the mobile car. The performance test experiment of identifying RFID tags is repeated to get the best recognition rate by adjusting the status of the reader and reader antennas and the speed of the mobile car. According to the present disclosure, individual customization on the position and angle of the reader antennas placed with and the moving speed of under-test goods may be obtained to identify all the RFID tags on the fixed position of the goods so as to provide a reference for using the RFID tags in the manufacturing lines and the logistics systems.

Abstract translation: 一种用于测试移动射频识别标签的性能的系统，包括：包括移动车和测试信道的测试设备; 测试通道包括用于标记可移动轿厢的测试行驶路线的地面上的磁性标签和固定在地面上的框架，并且具有用于RFID标签的读取装置; 磁性识别装置设置在移动式汽车的底部以识别磁性标签，并且移动式汽车沿着测试驾驶路线被驱动; 多个RFID标签被固定在装载在移动车上的未检测货物上; 被配置为控制读取装置以识别固定在不合格物品上的RFID标签的测试设备; 其中RFID标签被固定在装载在移动式轿厢上的低成本货物上。 重复识别RFID标签的性能测试实验，通过调整读取器和读取器天线的状态以及移动车的速度来获得最佳识别率。 根据本公开，可以获得对放置的读取器天线的位置和角度以及测试货物的移动速度的单独定制，以识别货物的固定位置上的所有RFID标签，以便提供参考 用于在生产线和物流系统中使用RFID标签。

公开(公告)号：US20220260981A1

公开(公告)日：2022-08-18

申请号：US17560878

申请日：2021-12-23

Applicant: INSTITUTE OF AUTOMATION, CHINESE ACADEMY OF SCIENCES

Inventor： Chengbao LIU ,  Jie TAN

IPC: G05B19/418 ,  G06N5/04 ,  G06N5/02

Abstract: Disclosed is an optimization decision-making method of an industrial process fusing domain knowledge and multi-source data. The method comprises the steps of: acquiring the domain knowledge of the industrial process by using probability soft logic, and building an domain rule knowledge base of the industrial process; fusing multi-source data semantics and multi-source data features to form a new semantic knowledge representation of the industrial process, and constructing a semantic knowledge base of the industrial process; under a posteriori regularization framework, utilizing the domain rule knowledge base of the industrial process and the semantic knowledge base of the industrial process to obtain an optimization decision-making model embedded with the domain rule knowledge and obtain a posteriori distribution model; and migrating knowledge in the optimization decision-making model embedded with the domain rule knowledge into the posteriori distribution model through the knowledge distillation technology.