| 田雨佳,祝彦,郭锰川,谢飞,李小亭.基于超声相控阵液固两相流固相含率测量[J].电子测量与仪器学报,2025,39(11):42-55 |
| 基于超声相控阵液固两相流固相含率测量 |
| Solid phase fraction measurement based on ultrasonic phasedarray in liquid-solid two-phase flow |
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| DOI： |
| 中文关键词: 液固两相流 阵列超声传感器 灰度共生矩阵 集成算法LGBM |
| 英文关键词:liquid-solid two-phase flow array ultrasonic sensors grayscale symbiosis matrix integrated algorithm LGBM |
| 基金项目:国家自然科学基金（62173122）项目资助 |
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| Author | Institution |
| Tian Yujia | College of Quality and Technical Supervision, Hebei University, Baoding 071002, China |
| Zhu Yan | 2.Engineering Research Center of
Zero-carbon Energy Building and Metering Technology, Ministry of Education, Baoding 071000, China |
| Guo Mengchuan | Hebei Provincial
Key Laboratory of Energy Metering and Safety Testing Technology, Hebei University, Baoding 071002, China |
| Xie Fei | College of Quality and Technical Supervision, Hebei University, Baoding 071002, China |
| Li Xiaoting | College of Quality and Technical Supervision, Hebei University, Baoding 071002, China |
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| 摘要点击次数: 301 |
| 全文下载次数: 6105 |
| 中文摘要: |
| 液固两相流作为一种复杂的流动现象,普遍存在于工业生产与日常生活的各种应用场景中。针对液固两相流中固相含率的测量问题,设计了基于超声相控阵的固相颗粒浓度测量系统,利用线扫探头进行扫查。分别在水箱中加入不同质量的固态示踪粒子模拟不同固相含率的流体,并设置不同的流量,共进行了140个不同工况点下的信号采集,并将采集得到的矩阵转化为图片信息,并采用灰度共生矩阵方法对图像进行特征提取,通过分析提取出的能量、熵特征值和两相流中固体粒子的浓度、流量之间的关系,对水中固体颗粒物的浓度进行模型拟合,采用不同集成算法对液体中的粒子含量进行拟合预测,并将预测效果进行对比。结果表明,使用LGBM模型的拟合效果最好，并使用鹈胡优化算法（POA）和正弦余弦算法（SCA）智能优化算法进行了优化，最终的模型拟合精度达到了92.85%，为液固两相流固相含率的测量提供了一种新的测量方法。 |
| 英文摘要: |
| Liquid solid two-phase flow, as a complex flow phenomenon, is widely present in various application scenarios of industrial production and daily life This article focuses on the measurement of solid content in liquid-solid two-phase flow. A solid particle concentration measurement device is designed, using an array ultrasonic sensor. The entire ultrasonic phased array testing system is designed, and the corresponding focusing rule is designed to determine the corresponding experimental parameters for scanning through a line scanning probe. Solid tracer particles of different masses were added to the water tank to simulate fluids with different solid content, and different flow rates were set. A total of 140 signal acquisition points were carried out under different operating conditions, and the collected matrices were converted into image information. The gray level co-occurrence matrix method was used to extract features from the images. By analyzing the extracted energy and entropy feature values and the relationship between the concentration and flow rate of solid particles in the two-phase flow, the concentration of solid particles in the water was modeled and fitted. Different ensemble algorithms were used to predict the particle content in the liquid, and the prediction effect was compared the results showed that the light gradient boosting machine (LGBM) model had the best fitting effect, and the intelligent optimization algorithm was used for optimization. The final model fitting accuracy reached 92.85%, providing a new measurement method for measuring the solid content of liquid-solid two-phase flow. |
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