Electromechanical equipment-oriented remote dynamic adaptive rule acquisition method

A technology of dynamic self-adaptation and method acquisition, applied in the direction of program control, computer control, instruments, etc., can solve the problems of not being able to support the optimal operation of the machine tool processing system, and the remote monitoring and diagnosis system cannot be sorted out and applied, so as to improve the failure rate. The effect of predicting diagnosis speed, satisfying remote fault diagnosis and improving diagnosis speed

Inactive Publication Date: 2012-10-17
BEIJING INFORMATION SCI & TECH UNIV
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AI Technical Summary

Problems solved by technology

At the same time, due to the lack of unified description and storage of these uncertain data, the remote monitoring and diagnosis

Method used

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  • Electromechanical equipment-oriented remote dynamic adaptive rule acquisition method
  • Electromechanical equipment-oriented remote dynamic adaptive rule acquisition method
  • Electromechanical equipment-oriented remote dynamic adaptive rule acquisition method

Examples

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Example Embodiment

[0048] Example: Taking the tool system of the high-end turning machining center DL-20MH as the test object, the YT15 tool is used to cut 45# steel, the cutting speed is given as Vc=200m / min, and the tool status during the machining process is the initial wear and mid-term respectively. For wear and serious wear, the 12 sets of current signals in different states are respectively subjected to variable-scale empirical mode decomposition, and the instantaneous frequency of each eigenmode function is obtained through Hilbert transform, which is used as a conditional attribute to construct the initial decision Information table (as shown in Table 1).

[0049] Table 1 Tool wear decision information table

[0050]

[0051] Perform dynamic hierarchical clustering discretization processing on the initial decision information table to obtain the discrete decision information table (as shown in Table 2);

[0052] Table 2 Discretization decision information table

[0053]

[0054] Then cal...

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Abstract

The invention relates to an electromechanical equipment-oriented remote dynamic adaptive rule acquisition method. The electromechanical equipment-oriented remote dynamic adaptive rule acquisition method comprises the steps as follows: (1) acquiring state signals of function parts of electromechanical equipment by a sensor group; (2) uploading the state signals into a remote data system through a remote network, converting and storing the state signals in a unified data format; (3) transmitting the data of the state signals to a fault diagnosis module of a remote network platform, obtaining intrinsic mode functions representing the characteristics of the state signals by a variable scale empirical mode decomposition method, and carrying out Hilbert conversion on the intrinsic mode functions respectively so as to obtain corresponding instantaneous frequencies; and (4) constructing a remote fault diagnosis knowledge base system, obtaining a rule base composed of rules, and transmitting to a tool fault diagnosis and prediction service platform through the remote network; and (5) carrying out dynamic adaptive optimization updating on the obtained rule base according to a dynamic coordination method by the tool fault diagnosis and prediction service platform, and taking degree of confidence as evaluation of the rules.

Description

technical field [0001] The invention relates to a method for acquiring a remote dynamic self-adaptive rule base, in particular to a method for acquiring a remote dynamic self-adaptive rule for electromechanical equipment. Background technique [0002] Mechanical and electrical equipment such as CNC machine tools with the theme of large-scale, high-speed, precision, and multi-combination have become the main processing equipment in my country's manufacturing industry. With the rapid development of the manufacturing industry, the mechanical structure of CNC equipment has become more and more complex, and the degree of integration, precision and intelligence has become higher and higher. This increases the possibility of accuracy degradation and mechanical failures during the processing of the equipment. At the same time, due to the uncertainty of the processing parameters and working conditions of the machine tool during the processing process and the influence of the surround...

Claims

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Application Information

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IPC IPC(8): G05B19/406
Inventor 徐小力王红军左云波任彬
Owner BEIJING INFORMATION SCI & TECH UNIV
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