Neural network-based grinding machining working condition detection method

A neural network and grinding technology, applied in the field of mechanical processing, can solve the problems of workpiece burn, processing efficiency and quality impact, workpiece and tool damage, etc., to avoid unnecessary damage, improve processing efficiency, and reduce dependence. Effect

Active Publication Date: 2010-09-01
NANJING UNIV +1
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Problems solved by technology

[0003] However, the current CNC grinding machines still require relatively skilled workers to operate, and the operator judges based on work experience whether the tool is in contact with the workpiece, whether the tool (that is, the grinding

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  • Neural network-based grinding machining working condition detection method
  • Neural network-based grinding machining working condition detection method
  • Neural network-based grinding machining working condition detection method

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[0038] The present invention will be further explained below in conjunction with the drawings.

[0039] Such as figure 1 , 2 As shown in and 3, the mechanical grinding condition detection system based on neural network of the present invention includes a sensor information acquisition module, a neural network learning module and a neural network operation output module.

[0040] The sensor information collection module is an acoustic emission sensor, which mainly collects various acoustic emission signals during processing according to a preset sampling frequency.

[0041] The neural network learning module is used to determine the weight threshold parameter of the neural network and pass it to the neural network operation output module for use. In the learning and training stage, the sample library is formed by collecting the acoustic emission signal when the tool is in contact with the processed workpiece, the acoustic emission signal when the tool (grinding wheel) is passivated, ...

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Abstract

The invention discloses a neural network-based grinding machining working condition detection method, which comprises the following steps of: establishing a neural network model; acquiring field acoustic emission information under a standard working condition by using a sensor information acquisition module, inputting a sample library consisting of the acquired acoustic emission data and standard working condition data into a neural network learning module, obtaining a weight threshold parameter by using an error back propagation algorithm and outputting the weight threshold parameter to a neural network operation and output module; according to a received real-time data vector, performing an operation and outputting a real-time working condition vector by using the neural network operation and output module; and judging the conditions of a cutter and a work piece according to definitions of each component in the working condition vector. The method has the advantages that: by utilizing a learning and intelligent judgment function of a neural network, the machining conditions of the work piece and the cutter can be automatically judged, dependence on specialized workers is greatly reduced and machining efficiency is improved, artificial judgment factors can be effectively reduced, machining efficiency and machining quality are improved and unnecessary damages to the work piece and the cutter are avoided.

Description

technical field [0001] The invention relates to a detection method in the field of mechanical processing, in particular to a neural network-based detection method for grinding processing conditions. Background technique [0002] In mechanical processing, grinding is an important processing method, and the grinding lathe is the main tool for implementing this processing method. With the development of science and technology, computer-aided grinding lathes (hereinafter referred to as CNC grinding machines) are gradually being used. The CNC grinding machine completes the processing of the workpiece according to the preset computer instructions and the processing drawings, which greatly improves the processing efficiency and processing accuracy. [0003] However, the current CNC grinding machines still require relatively skilled workers to operate, and the operator judges based on work experience whether the tool is in contact with the workpiece, whether the tool (that is, the ...

Claims

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Application Information

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IPC IPC(8): B24B49/00G01N29/14
Inventor 杨京徐水竹程建春刘翔雄
Owner NANJING UNIV
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