| CPC G01M 3/04 (2013.01) | 7 Claims |
|
1. An underwater detection method for contact leakage of a tunnel joint of a dam culvert, comprising:
Step S1, obtaining an underwater image sequence of the culvert by an underwater robot;
Step S2, preprocessing and registering the underwater image sequence;
Step S3, extracting particle information appearing in the underwater image sequence based on the registered underwater image sequence;
Step S4, constructing a three-dimensional fluid velocity distribution map based on the particle information, and determining leakage situation according to the three-dimensional fluid velocity distribution map; and
Step S5, superimposing the three-dimensional fluid velocity distribution map on a preconfigured three-dimensional culvert model, and rendering and displaying it,
wherein the Step S3 comprises:
Step S31, obtaining a registered image sequence, reading registered image frames one by one, identifying particle clusters of similar size and shape from the registered image frames as particles for velocity measurement;
Step S32, calculating an instantaneous velocity vector of each particle based on a mass center displacement of the particle between the registered image frames and a shooting interval of a camera;
Step S33, dividing the registered image frames into a predetermined number of grids, and counting mean and variance of the velocity vectors of the particles in each grid;
Step S34, adopting a fluid mechanics inversion algorithm, and considering particle characteristics and turbulent pulsation effects to correct velocity fields of the particles; and
Step S35, retrieving internal and external parameters of the camera, converting the velocity fields of the particles from a pixel coordinate system to a world coordinate system, and obtaining the velocity fields of the particles in the world coordinate system,
wherein the Step S4 comprises:
Step S41, obtaining velocity field data of the particles from at least 3 registered image frames, and superimposing them to obtain the three-dimensional fluid velocity distribution map;
Step S42, extracting an area where the velocity of the particles is greater than a preset threshold, from the three-dimensional fluid velocity distribution map, that is, a local high-speed area, and recording spatial coordinates, and seeking for a suspected leakage point based on the local high-speed area;
Step S43, estimating leakage flow rate and change trend according to a velocity distribution near the suspected leakage point;
Step S44, for each suspected leakage point, extracting an image near the suspected leakage point, extracting grayscale co-occurrence matrix features based on the image near the suspected leakage point, and obtaining morphological characteristics of a leakage channel; and
Step S45, giving out a leakage degree index by comprehensively analyzing leakage position, flow rate and leakage channel morphology,
in the Step S34, considering the effect of turbulent pulsation, the process of correcting the velocity fields of the particles comprises:
Step S341, performing time averaging on at least three consecutive frames of particle images, to eliminate pulsating component, and obtaining a stable background velocity field;
Step S342, adopting a LES simulation method and a SGS stress model to perform a numerical solution on a pulsating flow field, to obtain a spatiotemporal distribution of turbulent pulsation velocity;
Step S343, compensating and correcting the original velocity field with analyzed average flow field and turbulent pulsation to restore true turbulent velocity vector distribution;
wherein the Step S43 further comprises separating multiple leakage points, specifically comprising:
Step S431, for the compensated and corrected velocity field, extracting an area where a local velocity vector direction gradient is greater than a certain threshold, and identifying it as a potential leakage area;
Step S432, for all suspected leakage areas preliminarily identified, performing a three-dimensional clustering based on a regional growing method, and merging the areas with spatial proximity and consistent velocity direction to form an independent leakage cluster;
Step S433, estimating flow rate and direction of each leakage cluster respectively, and replace leakage cross-sectional areas by a cross-sectional area of the leakage cluster; if an angle and a distance between two leakage clusters are both less than thresholds, merging them into one leakage point.
|