Real-time video recognition for assessing plastic viscosity of ultra-high-performance concrete (UHPC)
Real-time video recognition for assessing plastic viscosity of ultra-high-performance concrete (UHPC)
复制标题
DOI：
10.1016/j.measurement.2022.110809
复制
发表时间：
2022-03
期刊：
影响因子：
5.6
通讯作者：
Pengwei Guo;Jiang Du;Yi Bao;Weina Meng
中科院分区：
文献类型：
--
作者：
Pengwei Guo;Jiang Du;Yi Bao;Weina Meng
塑性粘度是超高性能混凝土（UHPC）的关键性能，必须在搅拌过程中进行控制，以实现所需的新鲜和硬化性能。本文提出了一种视频识别技术，用于实时评估塑料粘度使用的视频拍摄的UHPC混合过程中。提出了一种长期递归卷积网络来从视频中提取流动UHPC的空间和时间特征，并将这些特征与流变仪测量的塑性粘度相关联，从而能够使用视频评估塑性粘度。本研究亦探讨塑性黏度对超高混凝土纤维分散及定向、含气量及弯曲性质之影响。结果表明，塑性粘度显著影响纤维分布和空隙率，从而影响UHPC的弯曲性能。该方法能够实时评估塑性粘度，以控制UHPC的弯曲性能和空隙率。该研究对超高性能混凝土的质量控制具有重要意义。
Plastic viscosity is a key property of ultra-high-performance concrete (UHPC) and must be controlled during the mixing to achieve desired fresh and hardened properties. This paper presents a video recognition technology for real-time assessment of plastic viscosity using a video captured by a camera during the mixing of UHPC. A long-term recurrent convolutional network is proposed to extract spatial and temporal features of flowing UHPC from the video and correlate the features with plastic viscosity measured from a rheometer, thus enabling assessment of plastic viscosity using videos. This research also investigates the effects of plastic viscosity on the fiber dispersion and orientation, air content, and flexural properties of UHPC. The results show that the plastic viscosity significantly influences fiber distribution and air void content, thus affecting the flexural properties of UHPC. The presented method enables real-time assessment of plastic viscosity for control of flexural properties and air void content of UHPC. This study will greatly facilitate quality control for production of UHPC.