Development of an Algorithm for Determining Defects in Cast-in-Place Piles Based on the Data Analysis of Low Strain Integrity Testing

Abstract

Low strain integrity testing for pile quality control, based on the analysis of elastic waves, is one of the most common methods, due to its high efficiency. However, it also has a number of limitations that should be taken into account during pile testing. For additional study of the method and its effectiveness, an experimental site was constructed, consisting of ten cast-in-place piles with embedded defects. When analyzing field data, pile defects were not identified. For further analysis of the problem, as well as for interpreting the results and identifying pile defects, a cluster analysis method, the so-called ANN-classifier, is proposed. This paper describes the results of creating an algorithm for the recognition of defects and their localization in cast-in-place piles. It is proposed that use of the characteristic points of the spectrum of the signal as the input vector of the ANN classifier, and the type of pile defect as the output vector, is optimal. The results of the study led to the conclusion that the ANN-classifier can be used as the main tool for automatic interpretation of the results obtained by low strain integrity testing.