CN-122017181-A - Wind power blade internal defect detection method and system based on robot

CN122017181ACN 122017181 ACN122017181 ACN 122017181ACN-122017181-A

Abstract

The invention relates to a method and a system for detecting internal defects of a wind power blade based on a robot. The method comprises the steps of obtaining and classifying wind power blade detection data to determine an abnormal type, dividing defect data associated with the abnormal type into a plurality of defect measuring points, defining an assessment area based on the defect measuring points, and carrying out risk assessment and risk check on the assessment area in a mode of carrying out weighting operation on the defect measuring points and comparing the risk threshold value to output a risk assessment result. The method and the device improve the accuracy of defect measuring point identification, realize effective definition of the evaluation area, objectively and quantitatively evaluate the risk of the evaluation area, thereby providing reliable data support for maintenance decision of the wind power blade and improving the operation and maintenance efficiency and safety.

Inventors

DING FENG
ZHENG XIANG
LI YAHUI
HAO YANFEI
DENG JINWEN
WU XIXIONG
LI BINGZHEN
JIA XIAOXIA
ZHANG QI
GAO HONGJIE

Assignees

国能山西新能源产业投资开发有限公司
国电山西兴能有限公司
国电山西洁能有限公司
国电洁能金科(山西)有限公司

Dates

Publication Date: 20260512
Application Date: 20260210

Claims (10)

1. A method for detecting internal defects of a wind power blade based on a robot is characterized by comprising the steps of obtaining wind power blade detection data, Identifying one or more defect measuring points from wind power blade detection data; Defining an evaluation zone based on one or more defect sites; The step of defining an assessment area comprises: collecting specific coordinate data of defects in the defect measuring points; Acquiring blade width data of a blade to which the defect belongs; calculating an evaluation area based on the specific coordinate data and the blade width data; performing risk assessment on the assessment area to generate a judgment result; and carrying out risk verification on the assessment area based on the judgment result to generate a risk assessment result.
2. The method for detecting defects in a wind power blade based on a robot according to claim 1, wherein the step of identifying one or more defect measuring points from the wind power blade detection data comprises: classifying wind power blade detection data into detection data presenting offset and detection data not generating offset; determining an anomaly type based on the detection data exhibiting the offset and the detection data not exhibiting the offset; Defect data associated with an anomaly type is partitioned into a plurality of defect sites.
3. The method for detecting defects in a wind power blade based on a robot according to claim 2, wherein the step of classifying the wind power blade detection data comprises: And comparing the variation amplitude of the detection data of the current node with a preset fluctuation amplitude threshold value to determine the wind power blade detection data as the detection data presenting offset or the detection data without offset.
4. The method for detecting defects in a wind power blade according to claim 2, wherein the step of determining the type of abnormality based on the detection data exhibiting the deviation and the detection data not generating the deviation comprises: Setting an alarm threshold value based on corrected offset detection data obtained by correcting the detection data exhibiting offset and detection data not generating offset; And determining the abnormality type corresponding to the detection data presenting the offset according to the alarm threshold value.
5. The method for detecting defects in a wind power blade based on a robot according to claim 1, wherein the step of performing risk assessment on the assessment area comprises: calculating the data to be processed associated with the defect measuring points based on the calculation weights set for the defect measuring points so as to generate calculation results; And comparing the calculated result with a set risk threshold value to generate a judging result for indicating whether the non-conventional defect exists in the evaluation area.
6. The method for detecting defects in a wind power blade based on a robot according to claim 5, wherein the data to be processed comprises defect elevation data of the defect measuring points extracted from a defect distribution group arranged based on the defect measuring points and corresponding risk levels.
7. The method for detecting the internal defects of the wind power blade based on the robot according to claim 2, wherein the step of dividing the defect data into a plurality of defect measuring points comprises the steps of: grouping the defect data with the distance smaller than a preset distance threshold according to the space position to form a defect group; each defect group is defined as a defect site.
8. Wind-powered electricity generation blade internal defect detecting system based on robot, characterized by comprising: the defect identification module is used for responding to the acquired wind power blade detection data and identifying one or more defect measuring points from the wind power blade detection data; An evaluation area definition module for defining an evaluation area based on the one or more defect measurement points identified by the defect identification module; The risk assessment module is used for carrying out risk assessment on the assessment area defined by the assessment area definition module so as to generate a judgment result; And the risk checking module is used for responding to the judging result generated by the risk evaluating module and checking the defect risk in the evaluating area so as to output a risk evaluating result.
9. The method for detecting defects inside a wind power blade based on a robot according to claim 8, wherein the defect recognition module is configured to classify wind power blade detection data into detection data exhibiting an offset and detection data not exhibiting an offset; determining an anomaly type based on the detection data exhibiting the offset and the detection data not exhibiting the offset; Defect data associated with an anomaly type is partitioned into a plurality of defect sites.
10. The method for detecting the internal defects of the wind power blade based on the robot according to claim 8, wherein the evaluation area definition module is configured to collect specific coordinate data of defects in defect measuring points; Acquiring blade width data of a blade to which the defect belongs; calculating an evaluation area based on the specific coordinate data and the blade width data; performing risk assessment on the assessment area to generate a judgment result; and carrying out risk verification on the assessment area based on the judgment result to generate a risk assessment result.

Description

Wind power blade internal defect detection method and system based on robot Technical Field The invention belongs to the technical field of wind power blade internal defect detection, and particularly relates to a wind power blade internal defect detection method and system based on a robot. Background Along with the transformation of the global energy structure, wind power generation is used as a renewable energy technology, blades in the wind generating set are core components for capturing wind energy, and the structural integrity and the running state of the wind generating set directly determine the generating efficiency, the running stability and the service life of the whole generating set, so that the internal defect detection of the wind power blades is a key link for guaranteeing the safe and efficient operation of a wind power plant. The method for detecting the internal defects of the wind power blades in the prior art relies on manual visual inspection or handheld equipment to carry out inspection, is high in labor intensity and operation risk, is low in detection efficiency, is difficult to meet the operation and maintenance requirements of a large-scale wind power plant, and the detection result depends on experience and subjective judgment of detection personnel, so that detection standards are different and repeatability is poor, missed detection and misjudgment are generated, hidden dangers are hidden in safety of a machine set, the existing automatic detection system has limitation on data processing and analysis capability although efficiency is improved to a certain extent, on one hand, in the process of collecting data, the interference of a field complex environment is caused, the signal-to-noise ratio of original detection data is low, a large amount of noise and artifacts are mixed, on the other hand, rear-end processing logic is simpler, the defect judgment is carried out by adopting a fixed threshold value or a simple mode matching algorithm, intelligent evaluation and dynamic correction capability on data quality are lacked, and the defect cannot effectively distinguish real internal cracks and benign characteristics of the surface, systematic data offset caused by equipment vibration or positioning misalignment in the scanning process is also not recognized and corrected, and the problems of defect positioning misalignment, size judgment and the like are caused. Based on the problems, the application provides a method and a system for detecting internal defects of a wind power blade based on a robot. Disclosure of Invention The invention aims to provide a wind power blade internal defect detection method and system based on a robot, which can be used for classifying detection data generated in the wind power blade detection process to obtain detection data and internal defect classification corresponding to the detection data, dividing a plurality of detection areas according to the distribution trend of the internal defects, and evaluating the internal defect risk value of each detection area, so that a concentrated distribution area of the internal defects in the wind power blade internal defect distribution process can be effectively identified, and the area is set as a key detection area, so that the problem of whether the internal defects exist in the areas is focused. In order to achieve the purpose, the technical scheme adopted by the invention is that the method for detecting the internal defects of the wind power blade based on the robot comprises the following steps: the detection data of the wind power blade are obtained, Identifying one or more defect measuring points from wind power blade detection data; Defining an evaluation zone based on one or more defect sites; The step of defining an assessment area comprises: collecting specific coordinate data of defects in the defect measuring points; Acquiring blade width data of a blade to which the defect belongs; calculating an evaluation area based on the specific coordinate data and the blade width data; performing risk assessment on the assessment area to generate a judgment result; and carrying out risk verification on the assessment area based on the judgment result to generate a risk assessment result. Preferably, the step of identifying one or more defect points from the wind blade detection data comprises: classifying wind power blade detection data into detection data presenting offset and detection data not generating offset; determining an anomaly type based on the detection data exhibiting the offset and the detection data not exhibiting the offset; Defect data associated with an anomaly type is partitioned into a plurality of defect sites. Preferably, the step of classifying the wind power blade detection data includes: And comparing the variation amplitude of the detection data of the current node with a preset fluctuation amplitude threshold value to determine the wind power blade detection data as the de