GTGuochao Tu

Guochao Tu

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Guochao Tu has a total of 16 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    The Design and Application of a Digital Portable Acoustic Teaching System

    by Xiuquan Li, Guochao Tu, Qingzhao Kong, Lin Chen, Xin Zhang, Ruiyan Wang

    To address the limitations of traditional acoustic experimental equipment, such as large volume, discrete modules, and complex operation, this paper proposes and implements a set of digital portable acoustic teaching systems. The hardware component is based on an FPGA, enabling a highly integrated design for signal source excitation and multi-channel synchronous acquisition. It supports the output of various signals, including pulses, sine waves, chirps, and arbitrary waveforms. The software component is developed based on the Qt framework, offering cross-platform compatibility and excellent graphical interaction capabilities. It supports signal configuration, data acquisition, real-time processing, result visualization, and historical playback, establishing a closed-loop experimental workflow of signal excitation–synchronous acquisition–real-time processing–data storage–result visualization. The system supports both local USB connection and remote TCP operation modes, accommodating scenarios such as real-time classroom experiments and cross-regional collaborative teaching. The verification results of three typical experiments, namely, multi-media sound velocity measurement, TDOA hydrophone positioning, and remote acoustic detection, demonstrate that the system performs well in terms of measurement accuracy, positioning stability, and the feasibility of remote detection. This study demonstrates the technical advantages and engineering adaptability of a digital teaching platform in acoustic experimental education. It provides a scalable system solution for cross-regional hybrid teaching models and practice-oriented education under the framework of emerging engineering disciplines. Future work will focus on expanding experimental scenarios, enhancing system intelligence, and improving multi-user collaboration capabilities, aiming to develop a more comprehensive and efficient platform to support acoustic teaching.


  • Acoustic Sensing-Based Detection Methodology for Downhole Fallen Objects in Oil and Gas Wells

    by Haihui Shen, Chuang Hei, Mingzhang Luo, Dong Yang, Guochao Tu, Changhe Sun, Luoyu Zhou, Hu Han

    In oil and gas exploration and production, downhole fallen objects in wells represent a significant operational challenge that demands immediate attention. Timely detection of such fallen objects is crucial to ensuring the safe and efficient operation of oil wells. This study adopts a comprehensive approach that integrates finite element simulations with experimental validation to investigate the potential application of ultrasonic imaging technology for downhole fallen objects detection. The study first employed finite element simulations to model the impact of fallen objects on acoustic wave propagation, with a focus on examining the correlations between the reflected signal and the fallen objects’ spatial position, size, and the probe’s excitation frequency. Based on the simulation results, an innovative ultrasonic imaging method for detecting fallen objects was proposed. Building upon the insights gained from numerical simulations, a dedicated experimental platform was developed to validate the proposed approach. Both simulations and experiments successfully generated two-dimensional overhead images of the fallen objects, facilitating the identification and characterization of their properties. The findings underscore the feasibility and effectiveness of ultrasonic imaging technology for detecting downhole fallen objects in the water and mud, but are theoretically extensible to oil/gas via simulation. This research not only demonstrates the practical application of this technique but also offers valuable insights for advancing future studies in ultrasonic fallen object detection.