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Coal mining machine memory cutting system with strong robustness and long and short term memory capability

A long-short-term memory and shearer technology, applied in the field of signal processing and deep learning, can solve problems such as low accuracy

Active Publication Date: 2019-04-19
ZHEJIANG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In response to the urgent need for automatic prediction of shearer cutting height under the complex working conditions of the current coal mining industry, the purpose of the present invention is to provide a strong and robust shearer memory with high prediction accuracy, good universality, and long-term and short-term memory capabilities. Cutting system, in order to overcome the shortcomings of manual adjustment such as low precision and slow speed, and provide a technical basis for improving productivity and resource utilization in the coal mining process

Method used

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  • Coal mining machine memory cutting system with strong robustness and long and short term memory capability
  • Coal mining machine memory cutting system with strong robustness and long and short term memory capability
  • Coal mining machine memory cutting system with strong robustness and long and short term memory capability

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Embodiment 1

[0051] refer to figure 1 , figure 2 , image 3 , a shearer memory cutting system with strong long-short-term memory capability, including data preprocessing module 5, shearer cutting height long-short-term memory network model (LSTM) modeling module 6, shearer cutting Highly long short-term memory network model (LSTM) prediction module 7 and online correction module 8. The data acquisition sensor 1, the database 2, the robust shearer memory cutting system 3 with long-short-term memory capability and the result display module 4 are connected in sequence, and the data acquisition sensor 1 performs the historical cutting height signal of the shearer. The data is collected and stored in the database 2. The database 2 contains historical shearer cutting height data to provide data support for a robust shearer memory cutting system 3 with long and short-term memory capabilities. The results predicted by the strong and robust shearer memory cutting system 3 with long and short-te...

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Abstract

The invention discloses a coal mining machine memory cutting system with strong robustness and long and short term memory capability. The method is used for predicting the cutting height of the coal mining machine and comprises a data preprocessing module, a coal mining machine cutting height long-short term memory network model (LSTM) modeling module, a coal mining machine cutting height long-short term memory network model (LSTM) prediction module and an online correction module. According to the method, the cutting height of the coal mining machine can be predicted quickly and accurately, and the method has high environmental adaptability.

Description

technical field [0001] The present invention relates to the field of signal processing and the field of deep learning, in particular, to a strong and robust shearer memory cutting system with long and short-term memory capabilities Background technique [0002] At present, countries around the world are striving to develop their economies, and energy demand continues to grow. Coal accounts for a large proportion of the world's primary energy consumption. However, coal safety production has always been an important factor restricting coal production. Therefore, it is very important to vigorously improve the automation, mechanization and informatization level of the coal mining process. As the key equipment of the coal mining face, the shearer is of great significance in the coal mining production process. The adjustment and control of the cutting drum height is the key process of manually controlling the shearer when the shearer is mining coal in the underground working fac...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/08G06K9/62G06F16/248
CPCG06N3/08G06N3/048G06F18/214Y02P90/30
Inventor 徐志鹏古有志刘兴高张泽银
Owner ZHEJIANG UNIV
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