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基于超声相控阵技术的车轮缺陷检测及定位研究
| 论文题名： | 基于超声相控阵技术的车轮缺陷检测及定位研究 |
| 关键词： | 超声相控阵;高速铁路;车轮缺陷;定位检测 |
| 摘要： | In recent years, along with continuously improving of China railway speed, especially running of high-speed motor train units, more rigorous and sophisticated maintenance and monitoring of rolling stock travelling parts are needed to implement, departments of rail safety inspection must accept new challenge.Currently, some developed countries have designed and established their own advanced wheel set inspection system.In our country, a mobile wheel set ultrasonic inspection system is researched and developed independently, which is based on phased array ultrasonic technology and general ultrasonic technology.On one hand, this thesis introduces the improvement of the existing inspection system for the mobile wheel rim, replacing the existing 1 dimensional phased array technology with the 1.5 dimensional phased array technology.Through simulation analysis, 1.5 dimensional phased array probe beam is wider than 1 dimensional phased array transducer beam, and the spoke area can be well covered, and the detection effect is better.Thus, the size of the probe cartier is reduced, which can better adapt to the detection of various types of vehicles.On the other hand, aiming at designing a set of flaw localization algorithms for the in-site wheel testing data of mobile wheel set ultrasonic system.Ultimately, the time performance of data analysis in practical inspection of system would be better, and the veracity of checking and calibrating would also be improved.In the thesis, on the premise of investigating and summarizing wheel testing technologies and devices at home and abroad, combining with analysis of China high-speed motor railway wheel's structural characteristics and ultrasonic phased array technology, the features of defects and interferences are extracted, and a set of defects localization algorithms are proposed based on region segmentation and growing,automatic contrast adjusting, periodic prolongation, relativity, KMEANS cluster and HOUGH transform.By using these methods, flaws in the testing image can be positioned accurately. |
| 作者： | 钱微冬 |
| 专业： | 物理学 |
| 导师： | 高晓蓉 |
| 授予学位： | 硕士 |
| 授予学位单位： | 西南交通大学 |
| 学位年度： | 2017 |
| 正文语种： | 中文 |
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