使用Resper探头测量混凝土或陆地土壤的盐度和含水量的电Spectroscopy性能
Performance of Electrical Spectroscopy using a Resper Probe to Measure the Salinity and Water Content of Concrete or Terrestrial Soil
摘要：
本文讨论了利用电导率仪探头测量混凝土或陆地土壤中水的含盐量s和体积含量θW的电谱性能。电磁探针是一种用于光谱学的感应装置，可同时和非侵入性地测量地下介质的电阻率1/σ和相对介电常数εr。数值模拟表明，该测量仪可以测量σ和ε，其误差低于预定义的限值（10%），直到高频带（HF）。电导率与盐度和介电常数的体积含水量使用适当细化的理论模型，这是符合阿尔奇和托普的经验定律的预测。一致性越好，吸湿含水量越低，s越高;因此，发现与几乎不含键合水分子的混凝土更接近一致，前提是这些混凝土的特征在于高σ。本论文的一个新颖之处是应用数学物理模型的测量误差的传播，灵敏度函数工具的基础上。盐度（含水量）的不准确度是由探头指定的电导率（介电常数）不准确度与从介质的本构方程导出的盐度（含水量）相对于电导率（介电常数）的灵敏度函数之间的比率（乘积）。主要结果是模型的预测，s和θW的测量不准确度越低（从10%到1%减少一个数量级），σ越高;因此土壤的不准确度越低。
英文摘要：
This paper discusses the performance of electrical spectroscopy using a RESPER probe to measure the salinity s and volumetric content θW of the water in concrete or terrestrial soil. The RESPER probe is an induction device for spectroscopy which performs simultaneous and non invasive measurements of the electrical RESistivity 1/σ and relative dielectric PERmittivity εr of a subjacent medium. Numerical simulations establish that the RESPER can measure σ and ε with inaccuracies below a predefined limit (10%) up to the high frequency band (HF). Conductivity is related to salinity and dielectric permittivity to volumetric water content using suitably refined theoretical models which are consistent with the predictions of Archie's and Topp's empirical laws. The better the agreement, the lower the hygroscopic water content and the higher s; so closer agreement is found with concrete containing almost no bonded water molecules provided these are characterized by a high σ. A novelty of the present paper is the application of a mathematical- physical model to the propagation of errors in the measurements, based on a sensitivity functions tool. The inaccuracy of salinity (water content) is the ratio (product) between the conductivity (permittivity) inaccuracy, specified by the probe, and the sensitivity function of salinity (water content) relative to conductivity (permittivity), derived from the constitutive equations of the medium. The main result is the model's prediction that the lower the inaccuracy for the measurements of s and θW (decreasing by as much as an order of magnitude from 10% to 1%), the higher σ; so the inaccuracy for soil is lower.
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