Non-destructive testing (NDT) techniques play a significant role in monitoring and diagnosing construction structures. Accurate characterization of the properties of reinforcing bars (rebars) in concrete structures is critical for the quality control during the construction phase, as well as for health monitoring and post-disaster safety evaluation during the operation phase [1
]. The parameters of rebars that need to be inspected include their location, spacing, diameter, cover thickness and the degree of corrosion. Among them, accurate determination of the rebar diameter and cover thickness in a non-destructive way is still challenging [2
], which is the objective of this paper.
Electromagnetic induction (EMI) is the principle of most of the commercially available rebar locators and cover meters [3
]. An EMI sensor consists of magnetic coils, which excite time-varying magnetic fields towards the concrete and receive the induced secondary magnetic fields from conductive objects [4
]. When an EMI sensor is used for rebar inspection, the induced secondary magnetic fields are sensitive to both the rebar diameter and cover thickness. Thus, a rebar locator or cover meter can estimate the rebar diameter or cover thickness, only if the other one is known, with the pre-calibrated data of the EMI strength stored in the instrument memory [6
]. A curvilinear model was developed to estimate the rebar diameter and cover thickness through the peak amplitude and the full width at half height (FWHH) extracted from the measured EMI pulse response, and the results show that the accuracy of the estimated cover thickness is much higher when the rebar diameter is given than that when the rebar diameter is unknown [8
]. A laboratory experiment was carried out to assess the capability of the commercial EMI instruments in estimating rebar diameter and cover thickness, and the results show that estimation errors rise with the increase of cover thickness and the instruments become unreliable [9
]. By acquiring two EMI readings at different measurement heights or employing two vertically-spaced coils, it is possible to simultaneously estimate the rebar diameter and cover thickness, but it is often inconvenient to scan in congested metal work areas and difficult to avoid the mutual interference of two sets of coils [10
]. Neural networks were trained to estimate rebar diameter and cover thickness respectively, and the estimation accuracy satisfies the industrial standards [11
]. Ultrasonic echo was combined with EMI measurement for mapping the meshed reinforced concrete and estimating the cover thickness, where better results were obtained than those from an alone EMI survey [12
]. However, this method requires to know rebar diameters in advance, and it cannot solve the rebar size.
Ground-penetrating radar (GPR) is another important NDT method based on the propagation and scattering of high-frequency electromagnetic (EM) waves. It has been successfully applied to utility detection [13
], pavement inspection [14
], environmental studies [16
], oil monitoring [17
], space exploration [18
], etc. Due to the great contrast of electrical properties between the steel rebars and the concrete background, rebar is a favorite target for GPR detection [19
]. Recently, increasing interests have been paid to the determination of the geometric properties of rebars (e.g., diameter, spacing and buried depth) [20
], the moisture of concrete [23
] and the degree of rebar corrosion [25
]. In a GPR profile with the survey line orthogonal to the rebar direction, the reflection from a rebar can be approximated as a hyperbola. Cover thickness can be estimated by the hyperbolic apex once the EM velocity in the concrete is accurately estimated [22
]. However, the EM velocity in concrete can hardly be accurately estimated by experience or a simple GPR measurement, since concrete is heterogeneous and its dielectric properties are dependent on the texture of the mixture [27
]. A conic equation relating the rebar diameter, cover thickness and EM velocity in concrete was developed [29
], and fitting between the extracted trajectory of the rebar reflection and the modelled hyperbolic curve was used to estimate the rebar diameter, cover thickness and wave velocity [30
]. However, studies find that the shape of the hyperbolic curve is insensitive to the rebar diameter, therefore it is not easy to straightforwardly infer the rebar diameter through the hyperbolic fitting [22
]. To avoid directly picking up or extracting the trajectory of the rebar reflection, Hough transform and its enhanced version were applied to estimate the diameter of a buried cylindrical object [33
]. An empirical procedure was presented to estimate rebar diameters by associating the antenna footprint with the power reflectivity from the rebar [20
]. However, the estimation accuracy may suffer from the instability of an impulse GPR system [34
]. Through a multi-polarization GPR measurement, the rebar diameter was estimated through the ratio of the reflection amplitudes recorded in different polarization channels. However, the authors acknowledge that the method is sensitive to the wavelength of the GPR employed and that the estimation accuracy depends on an optimal selection of the GPR frequency versus the rebar diameters [21
EMI is sensitive to both the depth and size of metallic buried objects. However, it is difficult to simultaneously and accurately obtain the two unknowns in a direct manner. GPR has a high sensitivity on the buried depth rather than the size of the objects, whereby a straightforward estimation of the buried depth is readily done by a time-depth conversion [22
]. Considering the respective advantages of EMI and GPR, an associated survey or designed system integrating EMI and GPR has been applied to landmine detection [35
], pollution evaluation [36
] and soil moisture prediction [38
]. This paper proposes to integrate EMI and GPR for simultaneous and accurate estimation of rebar diameter and cover thickness. Operating the separate EMI and GPR devices for synchronous data collection is feasible, but it has some disadvantages, such as low efficiency, location deviation and complicated data fusion [39
]. For that reason, we develop a compact and handheld prototype integrating EMI and GPR for convenient operations and fast measurements [40
], and a method for simultaneous estimation of rebar diameter and cover thickness is proposed.
In this paper, we propose the integration of EMI and GPR for simultaneous estimation of rebar diameter and cover thickness, which is of significance for quality control and safety evaluation of concrete structures. A prototype of GPR-EMI dual sensor has been developed, and a standard set of EMI data for calibration has been recorded using eleven rebars of different diameters buried at different depths in sand. The developed rebar detection device can synchronously record a GPR profile and an EMI response curve by a single scan in a handheld moving manner. The main contribution of this paper is the development of a data processing method for simultaneous estimation of rebar diameter and cover thickness. From the GPR data, a buried object is located and its cover thickness is roughly estimated from the apex of the hyperbolic reflection. The corresponding EMI data is extracted according to the GPR-determined location, and the detected object can be interpreted as a rebar or a plastic pipe by the EMI amplitude. The GPR-estimated cover thickness range is used as a constraint for further estimation of the rebar diameter and cover thickness by calculating the mean square errors between the measured and calibrated EMI data. A laboratory experiment demonstrates that integrating GPR and EMI data can greatly enhance the estimation accuracy. The field experiments on two concrete columns show that both the rebar diameter and cover thickness can be accurately estimated. We conclude that the developed EMI-GPR dual sensor can have a promising prospect in the practical NDT of concrete structures. The method of integrating GPR and EMI data can also be used for estimation of the diameter and buried depth of other cylindrical conductive objects, such as a metal pipe.
One of the limitations of the developed system and algorithm is that it is still difficult to implement an effective measurement and estimation of a rebars in a densely-meshed rebar net, where the GPR and EMI signals from the neighboring rebars severely interfere with each other. An attempt will be made to use advanced signal processing algorithms, and another attempt will aim to improve the system performance and enhance the directivity of the sensors. It is worth noting that the nominal frequency (corresponding to the bandwidth) of the pulse GPR has a significant impact on its resolution. The larger the bandwidth of the transmitting pulse is, the thinner the hyperbolic trajectory is, resulting in a more precise hyperbola extraction with Sobel operator as well as a more accurate cover thickness estimation in the following step. Thus, we are currently attempting to develop a prototype with a higher GPR center frequency of 2.6 GHz. In addition, the data processing is time- and labor-consuming with the increasing demands of field tests. We think artificial intelligent algorithms, such as deep learning, may have the potential in improving the efficiency of data analysis and processing.