Product classification analysis method based on binary density clustering
A technology of density clustering and analysis method, applied in the field of product classification algorithm, which can solve the problems of sensitivity to light change and shape deformation, production data cannot be effectively analyzed and used, and unfavorable product classification analysis.
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[0030] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings.
[0031] Such as figure 1 As shown, the embodiment of the present invention is to propose a binary density clustering product classification analysis method, which can process, cluster analysis, and regularize the time series of all products recorded by sensors on the same production line, Get the number of product types and the total amount of each product that have appeared on the production line. The method specifically includes the following steps:
[0032] Step 1: Use the electrical signal sensor to detect the electrical signal during the machining process of the CNC machine tool, and then record the waveforms of all products on a certain production line to obtain the initial product waveform data set. Electrical signal sensors are mainly current and voltage ...
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