Research on integrated monitoring and early warning system for large-diameter pile foundation construction

Abstract:

To address the problems in large-diameter pile foundation construction， such as experience-dependent parameter control， scattered monitoring data， and outliers easily caused by electromagnetic interference， which further lead to delayed early warning and lack of real-time quantitative characterization of construction status， an integrated system is proposed. This system combines condition monitoring， risk warning， fuzzy PID-based parameter adaptive regulation， and limited closed-loop control for over-limit emergency shutdown. Constructed upon a layered Internet of Things （IoT） architecture， the system integrates sensing units for rig attitude， power systems， drilling parameters， environmental conditions， mud level， and mud density. It is equipped with a non-contact hole depth monitoring unit based on infrared ranging and infrared mutual beam detection， along with an intelligent monitoring platform. A two-level data fusion method， a graded early warning model based on a comprehensive risk index R （with weights determined by the analytic hierarchy process）， and an adaptive optimization strategy for drilling parameters are established for pile foundation construction scenarios. Field test results indicate that， compared with manual sounding rope measurements， the average error of hole depth monitoring is ±6.2 mm； the response time for mud level alarms is less than 2.1 s； the early warning accuracy reaches 92.3% when validated against actual risk events； and the average hole completion time per pile is reduced by approximately 18% compared to manual empirical operation. The research results can provide technical support for intelligent decision-making， refined operation， and safe construction of large-diameter pile foundations under complex geological conditions.