Model construction method and device and concrete compressive strength prediction method and device

Abstract

The invention discloses a model construction method and device and a concrete compressive strength prediction method and device. The model construction method comprises the following steps: establishing a database about cubic concrete compressive strength influence factors; preprocessing the data in the database; constructing a prediction model through an adaptive neural fuzzy inference system; and training a prediction model by using the preprocessed data to obtain a prediction training model, wherein the prediction training model is used for concrete compressive strength prediction. The concrete compressive strength can be efficiently and accurately predicted in a short time, and the method can be applied to artificial sand concrete and also can be applied to common concrete.

Description

technical field [0001] The application relates to concrete strength measurement technology, in particular to a model building method and device, and a concrete compressive strength prediction method and device. Background technique [0002] The quality control and evaluation of concrete is an important technical issue in water conservancy and civil engineering, and the compressive strength of concrete is an important index to measure the characteristics and performance of concrete. [0003] At present, the commonly used detection methods for the compressive strength of concrete include the 1-hour coagulation-promoting pressure steaming method, neural network prediction method, gray theory prediction method, on-site detection method of fresh concrete, and ultrasonic rebound comprehensive method. [0004] Among them, although the gray theory and the current neural network method can realize timely evaluation according to the characteristic parameters, their accuracy is related...

AI Technical Summary

Problems solved by technology

[0004] Among them, although the gray theory and the current neural network method can realize timely evaluation according to the characteristic parameters, their accuracy is related to the original database and the rationality of the algorithm, and the fluctuation may be large; Due to the need to prepare samples in advance, it takes a certain amount of time, and the 1h accelerated coagulation and pressure steaming method uses the rapid hardening strength of mortar to estimate the concrete strength, without considering the role of stones in grading, the interface structure and size effect between stones and cement mortar, and its accuracy Insufficient, the on-site detection method of fresh concrete is affected by the limitations of the testing equipment and the testing environment, and there are precision problems; the test piece structure prepared in the ultrasonic rebound comprehensive method can only be tested after it has been formed and has a certain strength, and the time required The longest, and this method is also affected by the limitations of the detection instrument and the detection environment, and there are accuracy problems

[0005] It is difficult for the above methods to obtain high-precision strength prediction results in a short period of time.

Images