Diamond press anvil crack online detection method based on acoustic emission signal

Abstract

The invention discloses a novel diamond press anvil crack online detection method. By using a backtracking search optimization algorithm (BSA), a support vector machine model parameter is optimized and selected to avoid blindness of parameter selection; in the application of a K-SPWVD method, a template matching method and K-S inspection are utilized to avoid complicated time-frequency analysis of each signal to be detected and enhance the efficiency of the algorithm; and good time-frequency analysis performance of smooth pseudo Wigner-Ville distribution is also sufficiently unitized. The novel diamond press anvil crack online detection method disclosed by the invention has high accuracy and high computing speed and is beneficial for online detection of diamond press anvil cracks.

Description

technical field [0001] The invention relates to the field of hard alloy defect detection, in particular to an online detection method for cracks of a top hammer of a diamond press based on acoustic emission signals. Background technique [0002] Synthetic diamond has high hardness and good wear resistance, and can be widely used in machining industries such as cutting, grinding, drilling, and electronic industries such as semiconductors. my country's synthetic diamond production ranks first in the world, mainly using six-sided top presses for production. The anvil of the diamond press is made of hard alloy material, which is a brittle material, and is prone to cracks under high temperature and high pressure environment. If the crack is not detected in time, it will often cause a hammer collapse accident and bring huge economic losses to the enterprise. [0003] There are two main methods for detecting cracks in the top hammer of a traditional diamond press. One is to use a...

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Problems solved by technology

[0007] In the above two patents, the processing process of the acquired signal data does not establish an intelligent identification mode, there is no self-learning ability, and its scope of application is limited. For the diamond press anvil, the amount of data in the online detection process is large , the above two patented methods, in the case of a large amount of data, their reaction speed must have limitations, and they cannot judge dangerous situations in time, so it is difficult to directly use them for reference.

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