Influence of conductive materials on the crack sensing sensitivity and noise signal of smart concrete
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摘要: 采用四电极法测量了弯曲荷载作用下智能混凝土梁受拉侧裂缝扩展过程的电阻变化率(ρFCR),对比了碳黑(CB)、钢纤维(SF)、碳纤维(CF)不同组合及掺量对裂缝自监测灵敏度系数(K)的影响;并基于分形理论研究了归一化处理后的电阻变化率-裂缝扩展宽度曲线(ρ’FCR-w’COD)的粗糙程度,以反映不同导电材料对监测信号电阻变化率-裂缝扩展宽度曲线(ρFCR-wCOD)噪声水平的影响。研究表明:用线性函数拟合混凝土裂缝智能化自监测信号ρFCR-wCOD曲线的效果较好,K可用拟合直线的斜率来表征;随着SF掺量的增加,试件的K随之减小;双掺SF与纳米CB试件表现出最佳的裂缝智能化自监测性能,适量纳米CB的掺入对混凝土裂缝监测的K值有提升作用,同时可降低ρ’FCR-w’COD曲线的噪声水平,随着CB掺量的增加,试件的K值呈现先增后减、分形维数D值呈先减后增的规律,纳米CB的最佳掺量为1.0~1.5 kg/m3;CF的掺入对K值有一定的负面影响,但掺入CF的试件裂缝监测信号D值随导电相掺量变化而变化的程度不大。Abstract: The four-electrode method was used to measure the fraction change in resistance (ρFCR) during the crack propagation of the concrete beam subjected to bending. The effect of carbon black(CB), steel fiber (SF) and carbon fiber (CF) content and their combination on the crack self sensing gauge factor (K) of the concrete beam was compared and analyzed. Based on the fractal theory, the effect of different conductive materials on the noise level of the normalized fractional change in resistance - crack opening displacement curve (ρ’FCR-w’COD) was studied. The results show that the linear fitting analysis fit well with the fraction change in resistance-crack opening displacement curve (ρFCR-wCOD) and K can be characterized as the slope of the fitted line. In addition, K decreases with the increasing of the SF content. The specimens with the addition of SF and nano CB reveal the best crack self sensing ability among all the specimens. K can be improved while the tortuosity of the ρ’FCR-w’COD curve is reduced by the addition of nano CB. Specifically, the K values exhibit an increasing tendency till the CB increases to a certain content and then K decreases for even higher content of CB. However, the fractal dimensions (D) of the specimens and CB content show an inverse tendency. Furthermore, the optimum dosage of nano CB is 1.0-1.5 kg/m3. There exists a negative effect on the K value with the addition of CF, however, the standard deviation of D of the ρ'FCR-w'COD curves is reduced for the specimens with CF.
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Key words:
- smart concrete /
- crack sensing /
- gauge factor /
- fractal dimension /
- signal noise level
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表 1 混凝土基准配合比
Table 1. Mix proportions of concrete
kg/m3 Cement Fly ash Water Fine aggregate
(0-5 mm)Coarse aggregate
(5-10 mm)SP 390 155 272.5 848 822 5.5 Note: SP—Superplasticizer. 表 2 硅酸盐水泥化学组分[20]
Table 2. Chemical composition of portland cement
wt% Cement CaO SiO2 Al2O3 Fe2O3 MgO SO3 P·O 42.5 61.78 21.17 5.45 3.18 1.65 2.03 表 3 导电材料参数
Table 3. Parameters of conductive materials
Conductive
materialLength/
mmDiameter/
nmDensity/
(g·cm−3)Steel fiber(SF) 35 0.55×106 7.85 Carbon fiber(CF) 6 1.2×104-1.5×104 1.55-1.60 Carbon black(CB) − 30-120 0.3-0.5 表 4 混凝土试件的导电相掺量
Table 4. Dosages of the conductive admixtures of the concrete specimens
kg/m3 Specimen SF CB CF SF20CF0B0/concrete 20 0 0 SF40CF0B0/concrete 40 0 0 SF60CF0B0/concrete 60 0 0 SF20CF0B1concrete 20 1 0 SF40CF0B1/concrete 40 1 0 SF40CF0B1.5/concrete 40 1.5 0 SF40CF0B2/concrete 40 2 0 SF60CF0B1/concrete 60 1 0 SF20CF2B1/concrete 20 1 2 SF40CF2B1/concrete 40 1 2 SF60CF2B1/concrete 60 1 2 SF20CF4B1/concrete 20 1 4 SF40CF4B1/concrete 40 1 4 SF60CF4B1/concrete 60 1 4 表 5 混凝土试件智能化自监测的灵敏度系数
Table 5. Gauge factor of the self-sensing concrete specimens
Specimen K Average Standard deviation R2 SF20CF0B0/concrete 1.78 1.48 0.296 0.829 SF40CF0B0/concrete 1.08 0.967 SF60CF0B0/concrete 1.59 0.975 SF20CF0B1/concrete 4.68 2.35 1.374 0.991 SF40CF0B1/concrete 2.29 0.981 SF40CF0B1.5/concrete 2.11 0.920 SF40CF0B2/concrete 1.31 0.954 SF60 CF0B1/concrete 1.36 0.950 SF20CF2B1/concrete 0.77 1.51 0.697 0.915 SF40CF2B1/concrete 1.49 0.949 SF60CF2B1/concrete 2.64 0.988 SF20CF4B1/concrete 1.21 0.954 SF40CF4B1/concrete 1.98 0.981 SF60CF4B1/concrete 0.97 0.974 Notes: K—Sensing gauge factor; R2—Coefficient. 表 6 导电相掺杂强混凝土ρ'FCR-w'COD曲线分形维数D计算结果
Table 6. Fractal dimension D values of ρ'FCR-w'COD curve of the concrete specimens with different conductive materials
Specimen D Average Standard deviation SF20CF0B0/concrete 1.410 1.431 0.042 SF40CF0B0/concrete 1.480 SF60CF0B0/concrete 1.403 SF20CF0B1/concrete 1.251 1.290 0.040 SF40CF0B1/concrete 1.295 SF40CF0B1.5/concrete 1.254 SF40CF0B2/concrete 1.323 SF60CF0B1/concrete 1.329 SF20CF2B1/concrete 1.384 1.383 0.007 SF40CF2B1/concrete 1.373 SF60CF2B1/concrete 1.383 SF20CF4B1/concrete 1.392 SF40CF4B1/concrete 1.378 SF60CF4B1/concrete 1.387 -
[1] CHEN P W, CHUNG D. Carbon fiber reinforced concrete for smart structures capable of non-destructive flaw detection[J]. Smart Materials and Structures,1993,2(1):22-30. doi: 10.1088/0964-1726/2/1/004 [2] WEN S, CHUNG D. Self-sensing of flexural damage and strain in carbon fiber reinforced cement and effect of embedded steel reinforcing bars[J]. Carbon,2006,44(8):1496-1502. doi: 10.1016/j.carbon.2005.12.009 [3] YILDIRIM G, ÖZTÜRK O, AL-DAHAWI A, et al. Self-sensing capability of engineered cementitious composites: Effects of aging and loading conditions[J]. Construction and Building Materials,2020,231:117132. doi: 10.1016/j.conbuildmat.2019.117132 [4] 韩宝国, 关新春, 欧进萍. 导电掺和料形态与水泥基材料压敏性的相关性[J]. 复合材料学报, 2004, 21(3):137-141. doi: 10.3321/j.issn:1000-3851.2004.03.026HAN B G, GUAN X C, OU J P. Correlation between shape of electric admixtures and piezoresistive effect of cement based composite materials[J]. Acta Materiae Compositae Sinica,2004,21(3):137-141(in Chinese). doi: 10.3321/j.issn:1000-3851.2004.03.026 [5] DING Y, CHEN Z, HAN Z, et al. Nano-carbon black and carbon fiber as conductive materials for the diagnosing of the damage of concrete beam[J]. Construction & Building Materials,2013,43(3):233-241. [6] DING Y, HAN Z, ZHANG Y, et al. Concrete with triphasic conductive materials for self-monitoring of cracking development subjected to flexure[J]. Composite Structures,2016,138:184-191. doi: 10.1016/j.compstruct.2015.11.051 [7] DING Y, HUANG Y, ZHANG Y, et al. Self-monitoring of freeze-thaw damage using triphasic electric conductive concrete[J]. Construction & Building Materials,2015,101:440-446. [8] WEN S, CHUNG D. Partial replacement of carbon fiber by carbon black in multifunctional cement-matrix compo-sites[J]. Carbon,2007,45(3):505-513. doi: 10.1016/j.carbon.2006.10.024 [9] AZHARI F, BANTHIA N. Cement-based sensors with carbon fibers and carbon nanotubes for piezoresistive sensing[J]. Cement & Concrete Composites,2012,34(7):866-873. [10] MATERAZZI A, UBERTINI F, D’ ALESSANDRO A. Carbon nanotube cement-based transducers for dynamic sensing of strain[J]. Cement & Concrete Composites,2013,37(1):2-11. [11] HAN B, ZHANG K, XUN Y, et al. Nickel particle-based self-sensing pavement for vehicle detection[J]. Measurement,2011,44(9):1645-1650. doi: 10.1016/j.measurement.2011.06.014 [12] 范晓明, 董旭, 孙明清, 等. 掺CCCW的碳纤维石墨水泥基复合材料的导电及压阻特性[J]. 复合材料学报, 2009, 26(6):138-142. doi: 10.3321/j.issn:1000-3851.2009.06.023FAN X M, DONG X, SUN M Q, et al. Electrical characteristic and piezoresistivity of carbon fiber graphite cement-based composites containing CCCW[J]. Acta Materiae Compositae Sinica,2009,26(6):138-142(in Chinese). doi: 10.3321/j.issn:1000-3851.2009.06.023 [13] 杨波, 陈光顺, 李姜, 等. 多壁碳纳米管增强炭黑/聚丙烯导电复合材料导电行为[J]. 复合材料学报, 2009, 26(4):41-46. doi: 10.3321/j.issn:1000-3851.2009.04.007YANG B, CHEN G S, LI J, et al. Multi-wall carbon nanotubes enhanced conductive behaviors of CB/PP electrical conductive composites[J]. Acta Materiae Compositae Sinica,2009,26(4):41-46(in Chinese). doi: 10.3321/j.issn:1000-3851.2009.04.007 [14] WILSON J. Sensor technology handbook[M]. Burlington: Elsevier, 2004: 1-15. [15] UBERTINI F, D'ALESSANDRO A, MATERAZZI A L, et al. Novel nanocomposite clay brick for strain sensing in structural masonry[C]//2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I & CPS Europe). IEEE, 2017: 1-4. [16] 韩宝国. 压敏碳纤维水泥石性能、传感器制品与结构[D]. 哈尔滨: 哈尔滨工业大学, 2005.HAN Baoguo. Carbon fiber cement paste pressure-sensitive sensors and self-monitoring concrete structures[D]. Harbin: Harbin Institute of Technology, 2005(in Chinese). [17] ADRESI M, HASSANI A, TULLIANI J, et al. A study of the main factors affecting the performance of self-sensing concrete[J]. Advances in Cement Research,2016,29(5):216-226. [18] SUN M, LIEW R, ZHANG M, et al. Development of cement-based strain sensor for health monitoring of ultra high strength concrete[J]. Construction & Building Materials,2014,65(9):630-637. [19] UBERTINI F, MATERAZZI A, D’ ALESSANDRO A, et al. Natural frequencies identification of a reinforced concrete beam using carbon nanotube cement-based sensors[J]. Engineering Structures,2014,60(2):265-275. [20] 洪雷, 王苏岩. 超缓凝剂对硅酸盐水泥砂浆性能的影响[J]. 沈阳建筑大学学报(自然科学版), 2006(5):773-777.HONG L, WANG S Y. The influence of super-retarding agent on the properties of Portland cement mortar[J]. Journal of Shenyang Jianzhu University (Natural Science),2006(5):773-777(in Chinese). [21] American Society for Testing and Materials. Standard test method for flexural performance of fiber-reinforced concrete (using beam with third-point loading): ASTM C 1609—2019[S]. West Conshohocken: ASTM Internationa, 2019. [22] 中国工程建设标准化协会. 纤维混凝土试验方法标准: CECS 13—2009[S]. 北京: 中国计划出版社, 2010.China Association for Engineering Construction Standardization. Standard test method for fiber reinforced concrete: CECS 13—2009[S]. Beijing: China Planning Publishing House, 2010(in Chinese). [23] 彭瑞东, 谢和平, 鞠杨. 二维数字图像分形维数的计算方法[J]. 中国矿业大学学报, 2004, 33(1):19-24. doi: 10.3321/j.issn:1000-1964.2004.01.005PENG R D, XIE H P, JU Y. Computation method of fractal dimension for 2-D digital image[J]. Journal of China University of Mining & Technology,2004,33(1):19-24(in Chinese). doi: 10.3321/j.issn:1000-1964.2004.01.005 [24] 谢和平. 分形: 岩石力学导论[M]. 北京: 科学出版社, 1996.XIE H P. Fractal: Introduction to rock mechanics[M]. Beijing: Science Press, 1996(in Chinese).