Work

Monitoring and abnormal diagnosis of flood discharge vibration state of radial gate based on improved permutation entropy

Year: 2025

Type: article

Abstract: ABSTRACT This study proposes an improved multivariate multiscale weighted permutation entropy (IMMWPE) combined with correlation variance dedication rate to monitor radial gate vibrations under discharge excitation, ensuring safe gate operation. A non-parametric test based on kernel density estimation is used to determine alarm thresholds for abnormal vibrations. The dung beetle optimization (DBO) algorithm optimizes the penalty coefficient and kernel parameters, constructing a least squares support vector machine (LSSVM) model to diagnose gate vibration states. Results show that IMMWPE offers greater accuracy and anti-interference capabilities than existing methods. This approach enables efficient data-level dynamic fusion of multi-sensor vibration signals for real-time monitoring of gate vibrations induced by flood discharge, providing early warnings of abnormal vibrations. It also diagnoses fault types in gate discharge vibrations through IMMWPE–DBO–LSSVM, improving diagnostic accuracy. This method offers a new solution for vibration monitoring during gate operation.

Source: Journal of Hydroinformatics

DOI: 10.2166/hydro.2025.280

Authors: Yangliang Lu, Liu Yakun, Ze Cao, Di Zhang, Xinmeng Zhao

Institution: Dalian University of Technology

Language: English

Topic: Machine Fault Diagnosis Techniques

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

Funder: National Natural Science Foundation of China