Research on interface recognition technology for drilled concrete pile based on PSO-GA-BP neural network

The drilling grouting pile, with its mature construction technology, high bearing capacity, and wide range of applications, has been widely used in the foundation of road, railway, and bridge structures. Nonetheless, improper placement of the concrete injection interface within the drilling hole can easily cause issues like over-injection and other engineering difficulties, leading to wasted materials and higher expenses. The traditional method of judge cement covering using a rope and a weighty mallet is both time-overwhelming and labor-intensive, creation it difficult to achieve accurate consequence. To direction this topic, this newspaper current a novel technology for identify the cement vaccination connection, which leverages a multi-sensor data acquisition cloud platform in conjunction with the PSO-GA-BP neural network approach. By collecting and analyzing data on turbidity, conductivity, and pH levels, the PSO-GA-BP neural network model effectively identifies the injection interface, determines its position and height, and facilitates intelligent monitoring of the concrete injection process. This innovation effectively resolves challenges associated with both over-injection and under-injection.