Novel woodworking tool wear online diagnosis method
A technology of tool wear and diagnosis method, which is applied in the field of diagnosis of tool wear, can solve problems such as improper selection of signal processing methods, low sensitivity, and large sensor signal interference, and achieve the effect of improving the accuracy of diagnostic signals and improving accuracy
Active Publication Date: 2020-06-23
BOSHENG PREWI SHANGHAI TOOLS
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Problems solved by technology
[0003] (1) Improper selection of signal processing methods, resulting in large sensor signal interference;
[0004] (2) The signal collected by the sensor has low sensitivity to tool wear, which affects the diagnostic accuracy of tool wear
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[0034] In order to make the objects and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.
[0035] Such as figure 1 As shown, the present invention provides a novel tool wear diagnosis system, comprising a CNC milling machine 1, a milling cutter 2, a workpiece 3, a power sensor 4, an infrared camera 5 and a PC 6 for data processing and analysis, wherein the milling cutter 2 is installed on The workpiece 3 is milled on the cutter shaft of the CNC machine tool 1, one end of the power sensor 4 is connected to the CNC milling machine control box 7, and the other end is connected to the PC 6, and the power signal collected by the power sensor 4 is transmitted to the PC 6 connected to the power sensor 4 Among them, the infrared camera 5 len...
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The invention provides a novel woodworking tool wear online diagnosis method. The novel woodworking tool wear online diagnosis method comprises the following steps: establishing a tool wear diagnosiscriterion: S1, acquiring a power signal P and an infrared image I of a milling cutter in different wear states during milling; S2, using a PC to performs data processing and analysis on the power signal P by adopting a discrete wavelet transform algorithm, and extracting a characteristic value of the power signal P; using the PC to performs data processing and analysis on the infrared image I by adopting an image gradient algorithm and the discrete wavelet transform algorithm, and extracting the characteristic value of the infrared image I; andS3, establishing the cutter wear diagnosis criterion in combination with the obtained characteristic values of the power signal P and the infrared image I. In the invention, the power signal P is processed by using a DWT algorithm, a frequency component of the signal hidden in a time domain signal is acquired, the infrared image I is functionalized by using the image gradient algorithm, then the functionalized infrared image I is simplified and calculated by using the DWT algorithm, the image information is enhanced, and diagnosis signal precision is improved.
Description
technical field [0001] The invention relates to the technical field of diagnosing tool wear, in particular to a novel online diagnosis method for woodworking tool wear. Background technique [0002] In mechanical processing, tool wear affects product productivity, production cost and product processing quality. Existing studies have found that one-fifth of machine tool shutdowns are caused by tool wear. Accurate and reliable tool wear diagnosis technology can improve machine tool utilization. 1.5 times, the maximum cutting speed is increased by 50%, and the total processing cost is saved by about 30%. Most of the existing tool wear diagnosis technologies use one-dimensional sensors (such as acoustic emission, vibration, power and cutting force signals) to diagnose tool wear conditions. For example, Hu Yuhong et al. use piezoelectric sensors to collect vibration signals to monitor tool wear (application No.: 201911203201.0), Li Bin et al. used Hall current sensors to collect...
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IPC IPC(8): G01D21/00G01L3/24G01N21/95G01B11/00
CPCG01B11/00G01D21/00G01L3/24G01N21/95
Inventor 郭晓磊朱兆龙董伟航
Owner BOSHENG PREWI SHANGHAI TOOLS