Importance

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Abstract

The present disclosure provides a technology field of caking of crystal particles, and in particular relates to a method for predicting a critical caking cycle of crystal particle. The method includes: establishing a CHS crystal bridge growth model database of a crystal particle with a same type of crystal particle to be predicted firstly, selecting existed data in the corresponding CHS crystal bridge growth model database based on an equivalent particle radius, a stored ambient temperature, and an environmental high and low humidity cycle condition of the crystal particle to be predicted, respectively, and calculating the critical caking cycle according to experience calculation equations, wherein a result obtained by calculation is a predicted critical caking cycle of the crystal particle to be predicted. The present disclosure has characteristics of time-saving, convenience, good universality, and high prediction accuracy, which can quickly predict the critical caking cycle of multi-particle crystal particle products under different humidity storage conditions within a week, resulting in greatly reducing time costs and providing guidance for storage of industrial crystal particle products.

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First Claim