Work

Pile Integrity Testing Using Non-Destructive Testing Techniques and Artificial Intelligence: A Review

Year: 2025

Type: article

Abstract: As civil engineering projects grow increasingly complex, ensuring pile integrity is essential for pile bearing capacity and structural safety. Pile integrity testing (PIT) has long been a focal point for researchers and engineers. With the rapid development of industrial-level advancements and artificial intelligence technology, PIT methods have undergone significant technological advancements. This paper reviews traditional PIT techniques, including low-strain integrity testing and thermal integrity profiling. The review covers the principles, advantages, limitations, and recent developments of various testing techniques. Additionally, recent advances in artificial intelligence (AI) techniques, particularly in signal processing and data-driven recognition methods, are discussed. Finally, the advantages, limitations, and potential future research directions of existing methods are summarized. This paper aims to offer a systematic reference for researchers and engineers in PIT, synthesizing technical details of traditional methods and their AI-enabled advancements. Furthermore, it explores potential directions for integrating AI with PIT, with a focus on key challenges such as noisy signal interpretation and regulatory barriers in applications.

Source: Applied Sciences

DOI: 10.3390/app15158580

Authors: Peiyun Qiu, Liang Yang, Yilong Xie, Xinghao Liu, Zaixian Chen

Institutions: Guangzhou Metro Group (China), Harbin Institute of Technology

Language: English

Topic: Geotechnical Engineering and Soil Mechanics

Subfield: Civil and Structural Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,896