Method for monitoring state of machine

Abstract

The invention discloses a method for monitoring the state of a machine, comprising the following steps: presetting a density variation threshold value, calculating the density of the collected state point, and clustering the state point by a clustering method based on the density according to the preset density variation threshold value; then determining the relationship among classes; and finally determining the state of the current state point according to the relationship among classes and the class to which the current state point belongs. By using the invention, automatic detection can be performed on abnormal state deviation of the machine.

Description

technical field [0001] The invention relates to the technical field of CNC (Computer Numerical Control), in particular to a method for monitoring the state of a machine. Background technique [0002] Condition monitoring is playing an increasingly important role in ensuring the productivity and reliable uptime of critical production equipment. The most useful function of effective condition monitoring is to discover some abnormal state deviations in the machine at an early stage, so as to take timely countermeasures to prevent loss of productivity or major disasters before they happen. [0003] In order to implement state monitoring, the machine can be routinely measured repeatedly to collect signals, and extract characteristic quantities (CQ, CharacteristicQuantities) reflecting the monitored state from the collected signals, which are sensitive to changes in the monitored state . A variety of analysis methods can be used to extract the feature quantity by analyzing the s...

AI Technical Summary

Problems solved by technology

However, realizing the combination of feature quantities requires a sufficient understanding of the machine equipment itself, and with the increase in the complexity of the machine equipment itself, the difficulty of combining feature quantities is greater. Therefore, due to the complexity of the machine equipment itself, resulting in The theoretical relationship between the various feature quantities is not easy to find

[0009] To sum up, the existing technology either requires technicians to have a solid theoretical foundation for each machine, or needs to set appropriate thresholds for each feature. It can be seen that the existing methods for monitoring machine status are not universal enough. And the monitoring effect is not ideal

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