Roller compacted concrete compaction degree evaluation method based on GA-BP network

Abstract

The invention discloses a roller compacted concrete compaction degree evaluation method based on a GA-BP network. The method comprises the following steps: selecting the moisture content, the rollinglayer surface stress transverse wave velocity, the rolling material grading factor and the rubber sand ratio of a rolling material at each measuring point of a construction site as input index parameters of a real-time evaluation model; Determining a neural network structure of the compaction degree real-time evaluation model; Optimizing an initial weight value and a threshold value by utilizing agenetic algorithm; Substituting the determined initial weight value and the threshold value into a BP neural network for fine tuning to establish an optimal neural network model; And performing real-time evaluation to obtain a compaction degree value. According to the method, BP neural network is adopted on the basis of the moisture content of the roller compaction material before concrete rolling compaction, the surface stress wave velocity of a measuring point after rolling compaction is completed and corresponding concrete rolling compaction material grading characteristic parameters; TheGA-BP neural network constructs a compaction degree prediction model, predicts and evaluates concrete compaction degree indexes at real-time measurement points of rolling compaction, and can provide amethod for reliably judging the accuracy of the real-time compaction degree in the on-site construction process.

Description

technical field [0001] The invention belongs to the technical field of concrete construction quality monitoring, in particular to the technical field of roller compacted concrete construction quality evaluation, and relates to a method for evaluating the degree of compaction of roller compacted concrete based on a GA-BP network. Background technique [0002] Roller compacted concrete is ultra-dry hard concrete compacted by vibrating rollers. Due to the particularity of RCC construction methods and dam materials, in the process of layered RCC construction, low compaction of the construction layer and weak links in the layer will have a great impact on the permeability and dam strength. It poses a threat to the safety and durability of the dam body. Therefore, it is of great significance to strictly control the degree of compaction of the roller compacted hot layer for the quality of the roller compacted concrete dam. [0003] In current practice, the control methods for the...

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Problems solved by technology

In the gradation of RCC, coarse aggregate, fine aggregate (sand), cement and other multiphase mixtures, during the rolling process, the aggregate gradation factor of different gradations has a strong correlation with the aggregate density , has a strong correlation with the compactness after compaction; the moisture content of the roller compacted concrete is different from the moisture content of ordinary soil and rock due to the composition of the cement slurry, and the moisture content under the action of vibratory rolling has a great effect on improving the mutual dislocation and mutual dislocation between coarse and fine materials. The optimal filling and the improvement of the compaction effect all have important influences; however, due to the complexity of the raw materials of the RCC RCC, it is difficult to accurately predict and evaluate its compaction degree with certain specific parameters under site conditions

The surface stress wave velocity is used to detect the compaction degree when the hot layer is rolled. Due to the constraint

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