Abstract

The influence mechanism of different calcium content on the mechanical properties of cable protection pipe was studied, and the feasibility of feedback verification on the using performance of cable protection pipe through neural network learning method was also studied. Methods Shore hardness tester, universal electronic testing machine and densitometer were used to test the performance of cable protection tubes with different calcium content, and the quantitative relationship curve between cable protection tubes and performance was obtained. The database of hardness, density and composition was established through BP neural network, and the feasibility of feedback quality prediction was verified through test data. Results The hardness and density of the cable protective tube can be effectively improved by increasing the calcium element in the cable protective tube. Through the feedback prediction of performance by BP neural network, its qualification rate can be accurately predicted. Through this study, the content of calcium element can be adjusted appropriately according to the use conditions to make its performance meet the use conditions. Through Shore hardness tester and spectrometer, the quality of cable protection tube can be determined, and the nondestructive testing effect can be achieved.

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