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A group intelligent coal mining machine cutting mode recognition system based on integrated learning

A pattern recognition and integrated learning technology, applied in the field of signal processing, can solve problems such as the impact of recognition rate, difficult maintenance of the system, and increase in the cost of detection equipment, so as to solve the problem of accuracy and confidence decline, ensure safe operation, and achieve good optimization results Effect

Active Publication Date: 2019-06-14
ZHEJIANG UNIV
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AI Technical Summary

Problems solved by technology

On the one hand, the recognition rate is affected by geological conditions, which greatly increases the cost of detection equipment
On the other hand, the installation of the above-mentioned method equipment is too complicated and requires specific geological conditions, making the system difficult to maintain
The above problems lead to low recognition accuracy and poor robustness of traditional methods, which cannot be put into actual production use

Method used

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  • A group intelligent coal mining machine cutting mode recognition system based on integrated learning
  • A group intelligent coal mining machine cutting mode recognition system based on integrated learning
  • A group intelligent coal mining machine cutting mode recognition system based on integrated learning

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Embodiment Construction

[0044] The present invention will be described in detail below according to the accompanying drawings.

[0045]refer to figure 1 , figure 2 , image 3 As shown, the swarm intelligent shearer cutting pattern recognition system based on integrated learning includes data preprocessing module 5, shearer cutting pattern recognition limit gradient boosting (eXtreme Gradient Boosting, XGBoost) model modeling module 6, swarm intelligence optimization Module 7 and coal mining machine unknown cutting pattern recognition module 8. The data acquisition sensor 1, the database 2, the group intelligent shearer cutting pattern recognition system 3 based on integrated learning, and the result display module 4 are connected in sequence, and the data acquisition sensor 1 works on the speed, current, voltage, etc. when the shearer is cutting. Parameters are collected, and part of the data can be manually marked as tags, and the data is stored in the database 2. The historical shearer cutting...

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Abstract

The invention discloses a group intelligence coal mining machine cutting mode recognition system based on integrated learning. The method is used for identifying the cutting model of the coal mining machine, and comprises a data preprocessing module, a coal mining machine cutting mode identification limit gradient boost(eXtreme Gradient Boost) model modeling module, a group intelligence optimization module and a coal mining machine cutting unknown signal identification module. According to the method, the cutting mode of the coal mining machine can be accurately identified, the integrated learning algorithm is adopted to establish the cutting mode identification model of the coal mining machine, and the problem that the model accuracy and confidence degree are reduced due to randomness ofmanual parameter selection is avoided by adding a group intelligence optimization process to the modeling process.

Description

technical field [0001] The invention relates to the fields of signal processing, swarm intelligence optimization and integrated learning, in particular to a shearer cutting pattern recognition system combining integrated learning and swarm intelligence optimization algorithms. Background technique [0002] my country is making every effort to develop its economy, and its demand for energy is increasing day by day. Coal accounts for about 70% of the primary energy consumption and is one of the important pillars of the national economy. It is the development direction and trend of the coal mining industry to vigorously improve the automation, mechanization and informationization level of the coal mining process and reduce the number of underground workers. As the key equipment of the coal mining face, the shearer is of great significance in the process of coal production. Solving the problem of cutting pattern recognition of coal shearer is the premise of improving the degre...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N20/20G06N3/00
Inventor 徐志鹏古有志刘兴高张泽银
Owner ZHEJIANG UNIV
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