Fault Diagnosis Method of CNC Machine Tool Based on Hierarchical Early Warning

Abstract

The invention relates to a graded-early-warning-based fault diagnosis method of a numerically-controlled machine tool. The method comprises: (a), information of a machine tool is collected; to be specific, original vibration and temperature data of the machine tool are obtained; (b), data processing and parameter extraction are carried out; to be specific, feature parameters containing a vibration amplitude, a vibration abrupt change value and a temperature are extracted; (c), whether a fault occurs is determined; to be specific, whether a fault occurs at the machine tool is determined according to a situation whether the feature parameters obtained by the step (b) exceed a preset lower limit value; (d), an early warning grade is determined; to be specific, if the early warning grade reaches the fourth grade, a machine tool shutdown command is executed; and if the early warning grade is in a range from the first grade to the third grade, a step (f) is executed; and (f), a fault factor is identified automatically. According to the method, requirements of rapidity of early fault early warning of the machine tool and diagnosis accuracy can be met; accuracy and reliability of the fault diagnosis of the numerically-controlled machine tool are improved; the shutdown time is reduced; the maintenance cost is effectively lowered; and the production efficiency of the numerically-controlled machine tool can be enhanced.

Description

technical field [0001] The present invention relates to a fault diagnosis method for CNC machine tools based on hierarchical early warning, more specifically, to a CNC machine tool based on hierarchical early warning for fault diagnosis by judging whether the vibration amplitude, sudden change value of vibration and temperature of a component exceed a threshold Fault diagnosis method. Background technique [0002] As the key equipment in the production of large and medium-sized enterprises, the failure of any part of the CNC machine tool may lead to the reduction of machining accuracy, or even the shutdown of the machine tool and production stoppage. Significant downtime losses not only cause huge economic losses, but also endanger personal safety in severe cases. Due to the advanced, complex and intelligent features of CNC machine tools, if the on-site operators do not have rich maintenance experience, they will have no way of diagnosing such faults. They can only stop and...

AI Technical Summary

Problems solved by technology

However, because the intelligent algorithm itself often has some inherent defects, such as large training sample size, complex calculation process, and large amount of calculation, etc., it affects the online fault detection of complex systems such as machine tools that require high real-time performance. The needs of rapid forecasting, diagnosis and real-time control

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