EXTENSION KNOWLEDGE EVOLUTION AND KEY TECHNOLOGY OF GREEN PRODUCT DESIGN A CASE STUDY OF ELECTROSTATIC PRECIPITATOR

The construction of extension knowledge evolution system of green product design is an important guarantee for realizing intelligent environmental protection. In this study, the extension knowledge evolution model of green product is constructed based on the extension theory. The product information coverage of the evolutionary model is comprehensive, including five modules of product design task, process, resource, model and basic data maintenance and management. The controlling parameters through correlation relationship is adopted with the help of life cycle, elementary knowledge base and one-dimensional extension method. In order to evaluate the use value of the evolutionary model, the electrostatic precipitator is taken as an case. The results show that compared with the ERD and ETD methods, the knowledge classification accuracy of the evolutionary model designed in this paper is the highest, with the accuracy value of 93.1%. The evolutionary correlation degree is strong. and the error rate is only about 2.2%. The crossover and mutation control effect is the best, and through the design of green product electrostatic precipitator, the application effect of the designed model is verified. From the results of the particle collection efficiency, particle migration velocity and electric field intensity, it can be seen that the dust removal efficiency and environmental protection performance of EPSX1 optimized by the model are greatly improved compared with the previous products EPS4 and EPS 13.