Motion amplification extraction method for vibration modes of power grid facilities based on principal component analysis

doi:10.13474/j.cnki.11-2246.2025.0422

Abstract

Abstract: In the safe operation and inspection of power systems, modal health monitoring of power infrastructure is very important. Due to the advantages of high precision, high efficiency, flexibility and reliability, the machine vision method has become an important means of structural health monitoring. In this paper, a vibration modal extraction method based on the principal component analysis and blind source complexity tracking method, aiming to solve the problem of frequency passband empirical setting in the machine vision motion magnification method, is proposed, which can extract the micro motion signals automatically. Meanwhile, the mean subtracted contrast normalized (MSCN) coefficient is proposed as an evaluation index of image quality, which can identify and remove the blurry image in real-time and exactly. It is verified by the experiments on the overhead cable support system that the performance of the proposed method show consistency with that of the vibration accelerometer data, and the absolute error of the extracted vibration frequency is within 0.2 Hz. This indicates that the proposed method in this paper can extract the high precision micro motion signals of the power facilities in real-time, thus can provide high-quality structural modal monitoring data for the automatic operation and inspection of power systems.

Key words: machine vision, motion magnification, principal component analysis, power facility, vibration modal

CLC Number:

P237

ZHANG Ke, TONG Yang, HUANG Wenli, HU Shang, TAO Tingye, DAI Ju. Motion amplification extraction method for vibration modes of power grid facilities based on principal component analysis[J]. Bulletin of Surveying and Mapping, 2025, 0(4): 134-138,151.

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