Intelligent design method of concrete production matching ratio

Abstract

The invention relates to an intelligent design method of concrete production matching ratio, and belongs to the field of big data artificial intelligence. The method comprises the following steps thatS1, a concrete production matching ratio database is established, and the historical production matching ratio data of the concrete is input; S2, according to the part production matching ratio of the concrete input by users, expert system analysis is carried out, and the concrete production matching ratio with the highest score is primarily screened out; S3, a concrete production cost optimization model with constraint conditions is established; and S4, through the concrete production cost optimization model with the constraint conditions, fine adjustment on the concrete production cost optimization model with the highest initial screening score is carried out, the optimal concrete production matching ratio is output. According to the intelligent design method, the constraint conditionsare improved by combining historical production data, the production matching ratio reference is screened, the number of iterations of calculation can be effectively reduced, the intelligent design concrete production ratio can be efficient and real-time to carry out for the users, and the production cost is saved.

Description

technical field [0001] The invention relates to an intelligent design method of concrete production mix ratio, belongs to the field of big data artificial intelligence, and is especially suitable for the design of concrete production mix ratio in construction industry. Background technique [0002] Concrete is an important material for modern building materials. It uses cement as the main gel material, and aggregates and water. If necessary, chemical admixtures (water reducers, expansion agents, etc.) and mineral admixtures (fly ash , slag powder, etc.), mixed in an appropriate proportion, artificial stone formed by uniform pouring, mixing, compaction and curing hardening. Traditional concrete mix design is designed by experienced civil engineers using their previous experience and knowledge. In the laboratory, in order to obtain the ideal concrete strength and slump, experts must try several mix ratios , this time-consuming process not only increases the waste of materials...

AI Technical Summary

Problems solved by technology

In the fourth issue of 2003, the Journal of Hydroelectric Power published the paper "Research on Concrete Mix Proportion Optimization Design Based on Artificial Neural Network and Monte-Carlo Method", using neural network algorithm to establish a model to predict concrete compressive strength, combined with the experience of traditional mechanism design Knowledge is used as a constraint to design the amount of various materials in the mix ratio, but because the user's design requirement is only the concrete strength level and there is no reference to the national standard for the ratio of various ratio materials, this is not suitable for the production of concrete ratio actual

In the fifth issue of 2007, the Journal of Hydroelectric Power published the paper "Research on Concrete Mix Proportion Optimal Design Based on BPANN-GA Mixed Algorithm", using the prediction technology based on BP artificial neural network and the global optimization algorithm based on genetic algorithm (GA) , capable of predicting concrete strength and optimizing production costs, but its computational inefficiency

Since they do not have the support of big data in the industry, nor use the existing production data as a benchmark for further design, it is easy to fall into a bad local optimal solution. At the same time, the constraints are traditional empirical theory, and the scope is too broad

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