3D-RPDM: A Method for Measuring Packing Density of Gas–Solid Two-Phase Flow Based on 3-D Reconstruction

IF 4.3 2区综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Sensors Journal Pub Date : 2025-03-11 DOI:10.1109/JSEN.2025.3548564

Qihang Ma;Gaoliang Peng;Wei Zhang

{"title":"3D-RPDM: A Method for Measuring Packing Density of Gas–Solid Two-Phase Flow Based on 3-D Reconstruction","authors":"Qihang Ma;Gaoliang Peng;Wei Zhang","doi":"10.1109/JSEN.2025.3548564","DOIUrl":null,"url":null,"abstract":"This article introduces the 3D-RPDM framework, a method based on 3-D reconstruction for measuring the packing density of gassolid two-phase flow using a structured light system. Packing density, crucial for the manufacturing of gassolid two-phase flow materials, presents challenges in terms of intrusiveness, efficiency, and precision in sensing. The 3D-RPDM comprises calibration, volume estimation, and density calculation. Calibration aligns the structured light sensors system with container and measurement coordinates, capturing accurate particle surface data. Volume estimation is divided into irregular and regular types, accommodating various material shapes for volume calculation. Incorporating material mass data into density models yields accurate packing density measurements. This article evaluates the 3D-RPDM’s performance in terms of measurement, robustness, parameter ablation, and time consumption. The experiments confirmed an average packing density measurement error of up to 0.95%, with a maximum deviation of 2.9%, while achieving an average efficiency improvement of 77.21%, underscoring the enhanced efficiency, accuracy, and reliability of the proposed method over traditional approaches.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 9","pages":"15511-15524"},"PeriodicalIF":4.3000,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/10922856/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}

引用次数: 0

Abstract

This article introduces the 3D-RPDM framework, a method based on 3-D reconstruction for measuring the packing density of gassolid two-phase flow using a structured light system. Packing density, crucial for the manufacturing of gassolid two-phase flow materials, presents challenges in terms of intrusiveness, efficiency, and precision in sensing. The 3D-RPDM comprises calibration, volume estimation, and density calculation. Calibration aligns the structured light sensors system with container and measurement coordinates, capturing accurate particle surface data. Volume estimation is divided into irregular and regular types, accommodating various material shapes for volume calculation. Incorporating material mass data into density models yields accurate packing density measurements. This article evaluates the 3D-RPDM’s performance in terms of measurement, robustness, parameter ablation, and time consumption. The experiments confirmed an average packing density measurement error of up to 0.95%, with a maximum deviation of 2.9%, while achieving an average efficiency improvement of 77.21%, underscoring the enhanced efficiency, accuracy, and reliability of the proposed method over traditional approaches.

查看原文本刊更多论文

3D-RPDM：一种基于三维重构的气固两相流堆积密度测量方法

本文介绍了一种基于三维重建的结构光系统测量气固两相流堆积密度的方法3D-RPDM框架。填料密度对于气固两相流材料的制造至关重要，在传感的侵入性、效率和精度方面提出了挑战。3D-RPDM包括校准、体积估计和密度计算。校准将结构光传感器系统与容器和测量坐标对齐，捕获精确的颗粒表面数据。体积估算分为不规则型和规则型，可适应各种材料形状进行体积计算。将材料质量数据纳入密度模型，可获得准确的包装密度测量结果。本文从测量、稳健性、参数消融和时间消耗方面评估了3D-RPDM的性能。实验结果表明，该方法的平均密度测量误差为0.95%，最大偏差为2.9%，平均效率提高了77.21%，与传统方法相比，该方法的效率、准确性和可靠性都得到了提高。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE Sensors Journal 工程技术-工程：电子与电气

CiteScore

7.70

自引率

14.00%

发文量

2058

审稿时长

5.2 months

期刊介绍： The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice