System and method for diagnosing and intelligently optimizing grinding processes

Abstract

The invention relates to the technical field of online monitoring on grinding processes, in particular to a system and a method for diagnosing and intelligently optimizing the grinding processes. The system comprises sensors, a data collecting card, a grinding process diagnosing system and an intelligent grinding technique optimizing system. The sensors include a power sensor and a displacement sensor, and are connected to the grinding process diagnosing system through the data collection card. The grinding process diagnosing system is further connected with the intelligent grinding technique optimizing system. The grinding processes are systematically thought, process data are analyzed on the basis of grinding science through monitoring on the grinding processes, and then optimization schemes are proposed. Therefore, optimization is not experimental but scientific.

Description

technical field [0001] The invention relates to the technical field of on-line monitoring of the grinding process, in particular to a grinding process diagnosis and intelligent optimization system and method. Background technique [0002] Due to the complexity of the grinding process, most of the current optimization methods for the grinding process are empirical methods. General applications will integrate this experience into expert systems or neural network systems, and optimize the grinding process by means of "learning, training, system prediction, correction, and actual verification" for a certain grinding process. See Chinese invention patent 200910152759.0 for the cylindrical grinding multi-parameter integrated quality monitoring device and method. This monitoring method requires a large amount of experimental data as support. Firstly, various sensor signals under different grinding input parameters are monitored, and then the experience between the signal character...

AI Technical Summary

Problems solved by technology

In fact, mathematical optimization has two disadvantages: 1. It is limited by the quality of the obtained data, which determines the basis of calculation; 2. The actual grinding process is a complex system engineering, which needs to comprehensively consider the influence of many aspects , including factors such as machines, abrasive tools, processed materials and processing parameters

Mathematically optimization is generally only based on the optimization of processing parameters, but it is possible that the optimization scheme may only be adjusted at the parameter level, or it may not be realized due to the influence of other factors.

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