Intelligent machine tool working state identification system based on signal fusion

Abstract

The invention provides an intelligent machine tool working state identification system based on signal fusion. A sensor system is installed on a mechanical system of a machine tool and used for collecting a vibration signal, a temperature signal, a current signal and a speed signal of the machine tool; the vibration signal and the temperature signal are converted into digital signals through a data collecting system and then sent to a monitoring system, and the current signal and the speed signal are sent to the monitoring system through a numerical control system; and the monitoring system isused for controlling the vibration signal, the temperature signal, the current signal and the speed signal to be sent to a state signal database system and/or controlling the vibration signal, the temperature signal, the current signal and the speed signal to be sent to an intelligent data analysis system to achieve real-time data analysis and output an intelligent machine tool working state identification result. According to the intelligent machine tool working state identification system based on signal fusion, erroneous judgment brought by machine tool state identification obtained through signals measured by a power sensor singly is effectively eliminated, information fusion of multiple sensors is combined, a BP neural network method is adopted, therefore, errors in judgment are reduced, the system robustness is improved, and meanwhile basic conditions are provided for dynamic monitoring of the machining technology process.

Description

technical field [0001] The invention relates to the field of machine tool processing process monitoring, in particular to an intelligent identification system for machine tool working states at different processing stages in the processing process of a machining center based on signal fusion. Background technique [0002] The processing process identification of the machining center refers to the identification of the working state of the machine tool, especially the identification of different processing process stages in the processing process, which is an important basis for the monitoring of the processing process. The identification of the working state of the machine tool is of great significance for understanding and statistically analyzing the processing information of the equipment. The different working states of the machining center include shutdown, start-up, processing start, different processing process stages, processing end, tool change and other working stat...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the disadvantages of using only one power signal as the low accuracy and poor robustness in judging the state of the machine tool in the prior art, the present invention provides an intelligent identification system for the working state of the machine tool based on signal fusion, which uses a variety of sensor signals The method of fusion, by collecting vibration and load signals at different positions of the machine tool spindle and feed axis, based on artificial intelligence technology, multi-sensor signals are fused to automatically identify the working status of the machine tool, including shutdown, start-up, processing start, and processing corresponding to different processing stages Process, processing end, tool change and other working states provide new methods for automatic statistics of working states, especially to identify different processing processes of parts, such as specific processes and steps on the machining center, using different tools and processing technologies Parametric processing of different parts of the parts provides the basic conditions for the dynamic monitoring of the processing process

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