Multi-target micro-vibration frequency measurement method based on Euler visual angle

Abstract

The invention discloses a multi-target micro-vibration frequency measurement method based on an Euler visual angle, and the method comprises the steps: collecting micro-vibration video data of an object in an actual scene, and extracting brightness difference signals at N pixel points at the edge of a video image through an edge mask image Edge Mask; solving frequency spectrums of the N groups ofmicro vibration signals by utilizing Fourier transform; extracting signals interfering with motion from the video data, calculating an attenuation coefficient vector V(fq), and multiplying the vectorby the frequency spectrum points of all the tiny vibration signals; utilizing PCA to decompose all vibration signal frequency spectrums to obtain a group of principal components arranged according tovariance; selecting a group of principal components with large variance by using a characteristic value maximum ratio method, performing PCA regression on each principal component to obtain a mean frequency spectrum, and normalizing the mean frequency spectrum; and the frequency of the vibration mode corresponding to the principal component can be obtained by detecting the frequency correspondingto the peak value in the normalized frequency spectrum. The measurement method provided by the invention has the characteristics of high measuring speed, high measuring precision and the like.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to a multi-target micro-vibration frequency detection method based on Euler perspective in real scenes. Background technique [0002] Frequency information is an important basis for vibration analysis and is widely used in structural health testing and quality testing. People generally detect the vibration frequency by analyzing the vibration signal of the object. Traditional vibration signal detection methods include sensor-based contact vibration measurement and laser vibrometer-based non-contact vibration measurement, but these measurement methods are generally not suitable for simultaneous vibration measurement of multiple targets. [0003] The development of computer vision technology provides a new method for vibration signal detection. Visual measurement technology based on computer vision is based on modern optics and integrates modern science and technology such a...

AI Technical Summary

Problems solved by technology

However, this method has the following disadvantages: In terms of signal extraction, this processing method is time-consuming to calculate and is affected by the aperture problem. The signals extracted from flat areas are mostly low-frequency signals and do not contain effective vibration information; In terms of analysis, this method of globally averaging the spectrum cannot effectively distinguish the vibration frequencies from different targets, and when the video contains noise and interference vibrations such as camera motion, the effective peak in the average spectrum may be submerged in the interference spectrum. difficult to detect

However, this method still has some disadvantages: this method can only perform fixed-point measurement, and cannot perform multi-target measurement; when there is disturbing vibration or noise, the measurement accuracy of the displacement signal will also affect the accuracy of frequency analysis; when the ROI area contains flat area, the extracted signal may not contain valid vibration information

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